48 results on '"ROBUST control"'
Search Results
2. Robust Consensus for Nonlinear Multiagent Systems with Uncertainty and Disturbance.
- Author
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Li, Zhiqiang, Xu, Chengjie, Liu, Chen, and Xu, Haichuan
- Subjects
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ROBUST control , *MULTIAGENT systems , *LYAPUNOV stability , *MATRICES (Mathematics) , *MATHEMATICAL optimization - Abstract
This paper investigates robust consensus for nonlinear multiagent systems with uncertainty and disturbance. The consensus evolution behavior is studied under general consensus protocol when each node is disturbed by the relative states between the node and its neighbors. At first, the robust consensus condition is obtained and the convergency analysis is given by using Lyapunov stability theory and matrix theory. Then, the practical consensus is investigated and the bound of the error states is presented. Finally, two numerical simulation examples are given to illustrate the proposed theoretical results. [ABSTRACT FROM AUTHOR]
- Published
- 2018
- Full Text
- View/download PDF
3. Robust Model of Discrete Competitive Facility Location Problem with Partially Proportional Rule
- Author
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Wuyang Yu
- Subjects
Scheme (programming language) ,Mathematical optimization ,021103 operations research ,Article Subject ,Computer science ,General Mathematics ,0211 other engineering and technologies ,General Engineering ,Sorting ,Robust optimization ,02 engineering and technology ,Engineering (General). Civil engineering (General) ,Facility location problem ,Simulated annealing ,QA1-939 ,0202 electrical engineering, electronic engineering, information engineering ,020201 artificial intelligence & image processing ,TA1-2040 ,Robust control ,Market share ,computer ,Mathematics ,computer.programming_language - Abstract
When consumers faced with the choice of competitive chain facilities that offer exclusive services, current rules cannot describe these customers’ behaviors very well. So we propose a partially proportional rule to represent this kind of customer behavior. In addition, the exact demands of customers in many real-world environments are often difficult to determine. This is contradicting to the assumption in most studies of the competitive facility location problem. For the competitive facility location problem with the partially proportional rule, we establish a robust optimization model to handle the uncertainty of customers’ demands. We propose two methods to solve the robust model by studying the properties of the counterpart problem. The first method MIP is presented by solving a mixed-integer optimization model of the counterpart problem directly. The second method SAS is given by embedding a sorting subalgorithm into the simulated annealing framework, in which the sorting subalgorithm can easily solve the subproblem. The effects of the budget and the robust control parameter to the location scheme are analyzed in a quasi-real example. The result shows that changes in the robust control parameter can affect the customer demands that were captured by the new entrants, thereby changing the optimal solution for facility location. In addition, there is a threshold of the robust control parameter for any given budget. Only when the robust control parameter is larger than this threshold, the market share captured by the new entering firm increases with the increases of this parameter. Finally, numerical experiments show the superiority of the algorithm SAS in large-scare competitive facility location problems.
- Published
- 2020
4. The Application of Time-Delay Dependent H∞ Control Model in Manufacturing Decision Optimization.
- Author
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Guo, Haifeng, Wang, Bo, Zhang, Jianhua, Chen, Song, and Qiu, Yi
- Subjects
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TIME delay systems , *MATHEMATICAL optimization , *PRODUCTION management (Manufacturing) , *ROBUST control , *MATHEMATICAL proofs , *MATHEMATICAL models - Abstract
This paper uses a time-delay dependent H∞ control model to analyze the effect of manufacturing decisions on the process of transmission from resources to capability. We establish a theoretical framework of manufacturing management process based on three terms: resource, manufacturing decision, and capability. Then we build a time-delay H∞ robust control model to analyze the robustness of manufacturing management. With the state feedback controller between manufacturing resources and decision, we find that there is an optimal decision to adjust the process of transmission from resources to capability under uncertain environment. Finally, we provide an example to prove the robustness of this model. [ABSTRACT FROM AUTHOR]
- Published
- 2015
- Full Text
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5. Method for Determining the Maximum Allowable Capacity of Wind Farm Based on Box Set Robust Optimization.
- Author
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Guo, Lihui and Bai, Hao
- Subjects
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WIND power plants , *ROBUST control , *SET theory , *MATHEMATICAL optimization , *FLUCTUATIONS (Physics) , *DUALITY theory (Mathematics) - Abstract
With the increasing penetration of wind power, the randomness and volatility of wind power output would have a greater impact on safety and steady operation of power system. In allusion to the uncertainty of wind speed and load demand, this paper applied box set robust optimization theory in determining the maximum allowable installed capacity of wind farm, while constraints of node voltage and line capacity are considered. Optimized duality theory is used to simplify the model and convert uncertainty quantities in constraints into certainty quantities. Under the condition of multi wind farms, a bilevel optimization model to calculate penetration capacity is proposed. The result of IEEE 30-bus system shows that the robust optimization model proposed in the paper is correct and effective and indicates that the fluctuation range of wind speed and load and the importance degree of grid connection point of wind farm and load point have impact on the allowable capacity of wind farm. [ABSTRACT FROM AUTHOR]
- Published
- 2015
- Full Text
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6. A Multiobjective Genetic Algorithm Based on a Discrete Selection Procedure.
- Author
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Long, Qiang, Wu, Changzhi, Wang, Xiangyu, Jiang, Lin, and Li, Jueyou
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GENETIC algorithms , *MATHEMATICAL optimization , *PARETO analysis , *ROBUST control , *SEARCH algorithms - Abstract
Multiobjective genetic algorithm (MOGA) is a direct search method for multiobjective optimization problems. It is based on the process of the genetic algorithm; the population-based property of the genetic algorithm is well applied in MOGAs. Comparing with the traditional multiobjective algorithm whose aim is to find a single Pareto solution, the MOGA intends to identify numbers of Pareto solutions. During the process of solving multiobjective optimization problems using genetic algorithm, one needs to consider the elitism and diversity of solutions. But, normally, there are some trade-offs between the elitism and diversity. For some multiobjective problems, elitism and diversity are conflicting with each other. Therefore, solutions obtained by applying MOGAs have to be balanced with respect to elitism and diversity. In this paper, we propose metrics to numerically measure the elitism and diversity of solutions, and the optimum order method is applied to identify these solutions with better elitism and diversity metrics. We test the proposed method by some well-known benchmarks and compare its numerical performance with other MOGAs; the result shows that the proposed method is efficient and robust. [ABSTRACT FROM AUTHOR]
- Published
- 2015
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7. Robust Fault Detection for a Class of Uncertain Nonlinear Systems Based on Multiobjective Optimization.
- Author
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Yan, Bingyong, Wang, Huifeng, and Wang, Huazhong
- Subjects
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ROBUST control , *SET theory , *NONLINEAR systems , *MATHEMATICAL optimization , *ALGORITHMS , *MATRICES (Mathematics) - Abstract
A robust fault detection scheme for a class of nonlinear systems with uncertainty is proposed. The proposed approach utilizes robust control theory and parameter optimization algorithm to design the gain matrix of fault tracking approximator (FTA) for fault detection. The gain matrix of FTA is designed to minimize the effects of system uncertainty on residual signals while maximizing the effects of system faults on residual signals. The design of the gain matrix of FTA takes into account the robustness of residual signals to system uncertainty and sensitivity of residual signals to system faults simultaneously, which leads to a multiobjective optimization problem. Then, the detectability of system faults is rigorously analyzed by investigating the threshold of residual signals. Finally, simulation results are provided to show the validity and applicability of the proposed approach. [ABSTRACT FROM AUTHOR]
- Published
- 2015
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8. Short-Term Wind Speed Hybrid Forecasting Model Based on Bias Correcting Study and Its Application.
- Author
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Niu, Mingfei, Sun, Shaolong, Wu, Jie, and Zhang, Yuanlei
- Subjects
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WIND speed measurement , *BIAS correction (Topology) , *WIND power , *MATHEMATICAL optimization , *ROBUST control - Abstract
The accuracy of wind speed forecasting is becoming increasingly important to improve and optimize renewable wind power generation. In particular, reliable short-term wind speed forecasting can enable model predictive control of wind turbines and real-time optimization of wind farm operation. However, due to the strong stochastic nature and dynamic uncertainty of wind speed, the forecasting of wind speed data using different patterns is difficult. This paper proposes a novel combination bias correcting forecasting method, which includes the combination forecasting method and forecasting bias correcting model. The forecasting result shows that the combination bias correcting forecasting method can more accurately forecast the trend of wind speed and has a good robustness. [ABSTRACT FROM AUTHOR]
- Published
- 2015
- Full Text
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9. Finding Robust Assailant Using Optimization Functions (FiRAO-PG) in Wireless Sensor Network.
- Author
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Shukla, Piyush Kumar, Goyal, Sachin, Wadhvani, Rajesh, Rizvi, M. A., Sharma, Poonam, and Tantubay, Neeraj
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ROBUST control , *MATHEMATICAL optimization , *MATHEMATICAL functions , *WIRELESS sensor networks , *DATA transmission systems , *COMPUTER algorithms - Abstract
Wireless sensor network consists of hundreds or thousands of low cost, low power, and self-organizing tiny sensor nodes that are deployed within the sensor network. Sensor network is susceptible to physical attacks due to deprived power and restricted resource capability and is exposed to external environment for transmitting and receiving data. Node capture attack is one of the most menacing attack in the wireless sensor network and may be physically captured by an adversary for extracting confidential information regarding cryptographic keys, node’s unique id, and so forth, from its memory to eliminate the confidentiality and integrity of the wireless links. Node capture attack suffers from severe security breach and tremendous network cost. We propose an empirically designed multiple objectives node capture attack algorithm based on optimization functions as an effective solution against the attacking efficiency of node capture attack. Finding robust assailant optimization-particle swarm optimization and genetic algorithm (FiRAO-PG) consists of multiple objectives: maximum node participation, maximum key participation, and minimum resource expenditure to find optimal nodes using PSO and GA. It will leverage a comprehensive tool to destroy maximum portion of the network realizing cost-effectiveness and higher attacking efficiency. The simulation results manifest that FiRAO-PG can provide higher fraction of compromised traffic than matrix algorithm (MA) so the attacking efficiency of FiRAO-PG is higher. [ABSTRACT FROM AUTHOR]
- Published
- 2015
- Full Text
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10. The Evolutionary Algorithm to Find Robust Pareto-Optimal Solutions over Time.
- Author
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Chen, Meirong, Guo, Yinan, Liu, Haiyuan, and Wang, Chun
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EVOLUTIONARY algorithms , *ROBUST control , *MATHEMATICAL optimization , *DYNAMICAL systems , *GLOBAL environmental change , *PROBLEM solving - Abstract
In dynamic multiobjective optimization problems, the environmental parameters change over time, which makes the true pareto fronts shifted. So far, most works of research on dynamic multiobjective optimization methods have concentrated on detecting the changed environment and triggering the population based optimization methods so as to track the moving pareto fronts over time. Yet, in many real-world applications, it is not necessary to find the optimal nondominant solutions in each dynamic environment. To solve this weakness, a novel method called robust pareto-optimal solution over time is proposed. It is in fact to replace the optimal pareto front at each time-varying moment with the series of robust pareto-optimal solutions. This means that each robust solution can fit for more than one time-varying moment. Two metrics, including the average survival time and average robust generational distance, are present to measure the robustness of the robust pareto solution set. Another contribution is to construct the algorithm framework searching for robust pareto-optimal solutions over time based on the survival time. Experimental results indicate that this definition is a more practical and time-saving method of addressing dynamic multiobjective optimization problems changing over time. [ABSTRACT FROM AUTHOR]
- Published
- 2015
- Full Text
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11. Parallel and Cooperative Particle Swarm Optimizer for Multimodal Problems.
- Author
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Zhang, Geng and Li, Yangmin
- Subjects
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PARTICLE swarm optimization , *PROBLEM solving , *MATHEMATICAL optimization , *MATHEMATICAL functions , *ORTHOGONAL functions , *ROBUST control - Abstract
Although the original particle swarm optimizer (PSO) method and its related variant methods show some effectiveness for solving optimization problems, it may easily get trapped into local optimum especially when solving complex multimodal problems. Aiming to solve this issue, this paper puts forward a novel method called parallel and cooperative particle swarm optimizer (PCPSO). In case that the interacting of the elements in D-dimensional function vector X=[x1,x2,…,xd,…,xD] is independent, cooperative particle swarm optimizer (CPSO) is used. Based on this, the PCPSO is presented to solve real problems. Since the dimension cannot be split into several lower dimensional search spaces in real problems because of the interacting of the elements, PCPSO exploits the cooperation of two parallel CPSO algorithms by orthogonal experimental design (OED) learning. Firstly, the CPSO algorithm is used to generate two locally optimal vectors separately; then the OED is used to learn the merits of these two vectors and creates a better combination of them to generate further search. Experimental studies on a set of test functions show that PCPSO exhibits better robustness and converges much closer to the global optimum than several other peer algorithms. [ABSTRACT FROM AUTHOR]
- Published
- 2015
- Full Text
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12. Robust Optimisation Approach for Vehicle Routing Problems with Uncertainty.
- Author
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Sun, Liang and Wang, Bing
- Subjects
- *
UNCERTAINTY (Information theory) , *ROBUST control , *MATHEMATICAL optimization , *VEHICLE routing problem , *TRANSPORTATION costs , *PROBLEM solving - Abstract
We formulated a solution procedure for vehicle routing problems with uncertainty (VRPU for short) with regard to future demand and transportation cost. Unlike E-SDROA (expectation semideviation robust optimisation approach) for solving the proposed problem, the formulation focuses on robust optimisation considering situations possibly related to bidding and capital budgets. Besides, numerical experiments showed significant increments in the robustness of the solutions without much loss in solution quality. The differences and similarities of the robust optimisation model and existing robust optimisation approaches were also compared. [ABSTRACT FROM AUTHOR]
- Published
- 2015
- Full Text
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13. Observer-Based Robust Fault Detection Filter Design and Optimization for Networked Control Systems.
- Author
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Jiang, Weilai, Dong, Chaoyang, Niu, Erzhuo, and Wang, Qing
- Subjects
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ROBUST control , *FAULT tolerance (Engineering) , *FILTERS & filtration design & construction , *MATHEMATICAL optimization , *MARKOVIAN jump linear systems , *LINEAR matrix inequalities - Abstract
The problem of robust fault detection filter (FDF) design and optimization is investigated for a class of networked control systems (NCSs) with random delays. The NCSs are modeled as Markovian jump systems (MJSs) by assuming that the random delays obey a Markov chain. Based on the model, an observer-based residual generator is constructed and the corresponding fault detection problem is formulated as an H∞ filtering problem by which the error between the residual signal and the fault is made as small as possible. A sufficient condition for the existence of the desired FDF is derived in terms of linear matrix inequalities (LMIs). Furthermore, to improve the performance of the robust fault detection systems, a time domain optimization approach is proposed. The solution of the optimization problem is given in the form of Moore-Penrose inverse of matrix. A numerical example is provided to illustrate the effectiveness and potential of the proposed approach. [ABSTRACT FROM AUTHOR]
- Published
- 2015
- Full Text
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14. Reliability-Based Robust Design Optimization of Structures Considering Uncertainty in Design Variables.
- Author
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Wang, Shujuan, Li, Qiuyang, and Savage, Gordon J.
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ROBUST control , *MATHEMATICAL optimization , *UNCERTAINTY , *SENSITIVITY analysis , *COST analysis - Abstract
This paper investigates the structural design optimization to cover both the reliability and robustness under uncertainty in design variables. The main objective is to improve the efficiency of the optimization process. To address this problem, a hybrid reliability-based robust design optimization (RRDO) method is proposed. Prior to the design optimization, the Sobol sensitivity analysis is used for selecting key design variables and providing response variance as well, resulting in significantly reduced computational complexity. The single-loop algorithm is employed to guarantee the structural reliability, allowing fast optimization process. In the case of robust design, the weighting factor balances the response performance and variance with respect to the uncertainty in design variables. The main contribution of this paper is that the proposed method applies the RRDO strategy with the usage of global approximation and the Sobol sensitivity analysis, leading to the reduced computational cost. A structural example is given to illustrate the performance of the proposed method. [ABSTRACT FROM AUTHOR]
- Published
- 2015
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15. A Problem-Reduction Evolutionary Algorithm for Solving the Capacitated Vehicle Routing Problem.
- Author
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Liu, Wanfeng and Li, Xia
- Subjects
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EVOLUTIONARY algorithms , *VEHICLE routing problem , *MATHEMATICAL optimization , *ALGORITHMS , *STOCHASTIC convergence , *ROBUST control - Abstract
Assessment of the components of a solution helps provide useful information for an optimization problem. This paper presents a new population-based problem-reduction evolutionary algorithm (PREA) based on the solution components assessment. An individual solution is regarded as being constructed by basic elements, and the concept of acceptability is introduced to evaluate them. The PREA consists of a searching phase and an evaluation phase. The acceptability of basic elements is calculated in the evaluation phase and passed to the searching phase. In the searching phase, for each individual solution, the original optimization problem is reduced to a new smaller-size problem. With the evolution of the algorithm, the number of common basic elements in the population increases until all individual solutions are exactly the same which is supposed to be the near-optimal solution of the optimization problem. The new algorithm is applied to a large variety of capacitated vehicle routing problems (CVRP) with customers up to nearly 500. Experimental results show that the proposed algorithm has the advantages of fast convergence and robustness in solution quality over the comparative algorithms. [ABSTRACT FROM AUTHOR]
- Published
- 2015
- Full Text
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16. Grain Emergency Vehicle Scheduling Problem with Time and Demand Uncertainty.
- Author
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Jiang DongQing and Zhu QunXiong
- Subjects
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PROBLEM solving , *UNCERTAINTY (Information theory) , *SUPPLY chain management , *ROBUST control , *MATHEMATICAL optimization - Abstract
Grain transportation plays an important role in many relief and emergency supply chains. In this paper, we take the grain emergency vehicle scheduling model between multiware houses as the research object. Under the emergency environment, the aim of the problem is to maximize the utilization of vehicles and minimize the delay time. The randomness of the key parameters in grain emergency vehicle scheduling, such as time and demand, is determined through statistical analysis and the model is solved through robust optimization method. Besides, we apply the numerical examples for experimental analysis. We compare the robust optimization model with classic model to illustrate the differences and similarities between them. The results show that the uncertainty of both time and demand has great influence on the efficiency of grain emergency vehicle scheduling problem. [ABSTRACT FROM AUTHOR]
- Published
- 2014
- Full Text
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17. A Free Search Krill Herd Algorithm for Functions Optimization.
- Author
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Liangliang Li, Yongquan Zhou, and Jian Xie
- Subjects
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SEARCH algorithms , *MATHEMATICAL optimization , *STOCHASTIC convergence , *ROBUST control , *PRECISION (Information retrieval) , *MATHEMATICAL analysis - Abstract
To simulate the freedom and uncertain individual behavior of krill herd, this paper introduces the opposition based learning (OBL) strategy and free search operator into krill herd optimization algorithm (KH) and proposes a novel opposition-based free search krill herd optimization algorithm (FSKH). In FSKH, each krill individual can search according to its own perception and scope of activities. The free search strategy highly encourages the individuals to escape from being trapped in local optimal solution. So the diversity and exploration ability of krill population are improved. And FSKH can achieve a better balance between local search and global search. The experiment results of fourteen benchmark functions indicate that the proposed algorithm can be effective and feasible in both low-dimensional and high-dimensional cases. And the convergence speed and precision of FSKH are higher. Compared to PSO, DE, KH, HS, FS, and BA algorithms, the proposed algorithm shows a better optimization performance and robustness. [ABSTRACT FROM AUTHOR]
- Published
- 2014
- Full Text
- View/download PDF
18. Quasipolynomial Approach to Simultaneous Robust Control of Time-Delay Systems.
- Author
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SemeniI, Nikolaj, Sarjaý, Andrej, Chowdhury, Amor, and SveIko, Rajko
- Subjects
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POLYNOMIALS , *ROBUST control , *CLOSED loop systems , *TIME delay systems , *SENSITIVITY analysis , *MATHEMATICAL optimization , *ALGORITHMS - Abstract
A control law for retarded time-delay systems is considered, concerning infinite closed-loop spectrum assignment. An algebraic method for spectrum assignment is presented with a unique optimization algorithm for minimization of spectral abscissa and effective shaping of the chains of infinitely many closed-loop poles. Uncertainty of plant delays of a certain structure is considered in a sense of a robust simultaneous stabilization. Robust performance is achieved using mixed sensitivity design, which is incorporated into the addressed control law. [ABSTRACT FROM AUTHOR]
- Published
- 2014
- Full Text
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19. Robust Homography Estimation Based on Nonlinear Least Squares Optimization.
- Author
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Wei Mou, Han Wang, and Seet, Gerald
- Subjects
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ROBUST control , *COST functions , *ESTIMATION theory , *LEAST squares , *MATHEMATICAL optimization , *NONLINEAR analysis - Abstract
The homography between image pairs is normally estimated by minimizing a suitable cost function given 2D keypoint correspondences. The correspondences are typically established using descriptor distance of keypoints. However, the correspondences are often incorrect due to ambiguous descriptors which can introduce errors into following homography computing step. There have been numerous attempts to filter out these erroneous correspondences, but it is unlikely to always achieve perfect matching. To deal with this problem, we propose a nonlinear least squares optimization approach to compute homography such that false matches have no or little effect on computed homography. Unlike normal homography computation algorithms, our method formulates not only the keypoints' geometric relationship but also their descriptor similarity into cost function. Moreover, the cost function is parametrized in such a way that incorrect correspondences can be simultaneously identified while the homography is computed. Experiments show that the proposed approach can perform well even with the presence of a large number of outliers. [ABSTRACT FROM AUTHOR]
- Published
- 2014
- Full Text
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20. Robust Missing Traffic Flow Imputation Considering Nonnegativity and Road Capacity.
- Author
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Huachun Tan, Yuankai Wu, Bin Cheng, Wuhong Wang, and Bin Ran
- Subjects
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ROBUST control , *TRAFFIC flow , *MATHEMATICAL optimization , *ALGORITHMS , *HIGHWAY capacity - Abstract
There are increasing concerns about missing traffic data in recent years. In this paper, a robust missing traffic flow data imputation approach based on matrix completion is proposed. In the proposed method, the similarity of traffic flow from day to day is exploited to impute missing data by the low-rank hypothesis of constructed traffic flow matrix. And the physical limitation of road capacity and nonnegativity is also considered through the optimization process, which avoids the possibility of producing negative and overcapacity values. Moreover, the proposed algorithm can impute missing data and recover outlier in a unify framework. The experiment results show that the proposed method is more accurate, stable, and reasonable. [ABSTRACT FROM AUTHOR]
- Published
- 2014
- Full Text
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21. A Novel Adaptive Elite-Based Particle Swarm Optimization Applied to VAR Optimization in Electric Power Systems.
- Author
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Ying-Yi Hong, Faa-Jeng Lin, Syuan-Yi Chen, Yu-Chun Lin, and Fu-Yuan Hsu
- Subjects
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PARTICLE swarm optimization , *ELECTRIC power , *MATHEMATICAL optimization , *PRUNING , *GENETIC algorithms , *ROBUST control - Abstract
Particle swarm optimization (PSO) has been successfully applied to solve many practical engineering problems. However, more efficient strategies are needed to coordinate global and local searches in the solution space when the studied problem is extremely nonlinear and highly dimensional. This work proposes a novel adaptive elite-based PSO approach. The adaptive elite strategies involve the following two tasks: (1) appending the mean search to the original approach and (2) pruning/cloning particles. The mean search, leading to stable convergence, helps the iterative process coordinate between the global and local searches. The mean of the particles and standard deviation of the distances between pairs of particles are utilized to prune distant particles. The best particle is cloned and it replaces the pruned distant particles in the elite strategy. To evaluate the performance and generality of the proposed method, four benchmark functions were tested by traditional PSO, chaotic PSO, differential evolution, and genetic algorithm. Finally, a realistic loss minimization problem in an electric power system is studied to show the robustness of the proposed method. [ABSTRACT FROM AUTHOR]
- Published
- 2014
- Full Text
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22. Fixed-Order Robust H∞ Estimator Design for Side-Slip Angle of Vehicle.
- Author
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Delibşı, Akιn
- Subjects
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VEHICLE design & construction , *ROBUST control , *MATHEMATICAL optimization , *PROBLEM solving , *NONLINEAR theories , *OPTIMAL designs (Statistics) , *APPROXIMATION theory - Abstract
We present a novel linear observer with an extension dealing with polytopic uncertainties in a vehicle dynamic system to identify the side-slip angle. The performance optimization issue is addressed by the minimization of H∞ norm of the system considering the estimation error as an output and the steer angle as an input. Contrary to the standard robust optimal design approaches, we use a convex inner approximation technique to reduce the order of the observer and this enables us to derive suboptimal, fixed-order, and efficiently practicable estimators. Moreover, the numerical examples performed on two-track nonlinear model of the system are provided to illustrate the impacts of design parameters on the optimization results and the efficiency of the technique. [ABSTRACT FROM AUTHOR]
- Published
- 2014
- Full Text
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23. A Modified Conjugacy Condition and Related Nonlinear Conjugate Gradient Method.
- Author
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Shengwei Yao, Xiwen Lu, and Bin Qin
- Subjects
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CONJUGATE gradient methods , *NONLINEAR theories , *PROBLEM solving , *ROBUST control , *MATHEMATICAL optimization - Abstract
The conjugate gradient (CG) method has played a special role in solving large-scale nonlinear optimization problems due to the simplicity of their very low memory requirements. In this paper, we propose a new conjugacy condition which is similar to Dai-Liao (2001). Based on this condition, the related nonlinear conjugate gradient method is given. With some mild conditions, the given method is globally convergent under the strong Wolfe-Powell line search for general functions. The numerical experiments show that the proposed method is very robust and efficient. [ABSTRACT FROM AUTHOR]
- Published
- 2014
- Full Text
- View/download PDF
24. A Robust Probability Classifier Based on the Modified χ2-Distance.
- Author
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Yongzhi Wang, Yuli Zhang, Jining Yi, Honggang Qu, and Jinli Miu
- Subjects
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DISTRIBUTION (Probability theory) , *ROBUST control , *DUALITY theory (Mathematics) , *MATHEMATICAL optimization , *NUMERICAL analysis , *COMPUTER programming - Abstract
We propose a robust probability classifier model to address classification problems with data uncertainty. A class-conditional probability distributional set is constructed based on the modified χ2-distance. Based on a "linear combination assumption" for the posterior class-conditional probabilities, we consider a classification criterion using the weighted sum of the posterior probabilities. An optimal robust minimax classifier is defined as the one with the minimal worst-case absolute error loss function value over all possible distributions belonging to the constructed distributional set. Based on the conic duality theorem, we show that the resulted optimization problem can be reformulated into a second order cone programming problem which can be efficiently solved by interior algorithms. The robustness of the proposed model can avoid the "overlearning" phenomenon on training sets and thus keep a comparable accuracy on test sets. Numerical experiments validate the effectiveness of the proposed model and further show that it also provides promising results on multiple classification problems. [ABSTRACT FROM AUTHOR]
- Published
- 2014
- Full Text
- View/download PDF
25. Wolf Pack Algorithm for Unconstrained Global Optimization.
- Author
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Hu-Sheng Wu and Feng-Ming Zhang
- Subjects
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MATHEMATICAL optimization , *COMPUTER algorithms , *STOCHASTIC convergence , *ROBUST control , *HEURISTIC algorithms - Abstract
The wolf pack unites and cooperates closely to hunt for the prey in the Tibetan Plateau, which shows wonderful skills and amazing strategies. Inspired by their prey hunting behaviors and distribution mode, we abstracted three intelligent behaviors, scouting, calling, and besieging, and two intelligent rules, winner-take-all generation rule of lead wolf and stronger-survive renewing rule of wolf pack. Then we proposed a new heuristic swarm intelligent method, named wolf pack algorithm (WPA). Experiments are conducted on a suit of benchmark functions with different characteristics, unimodal/multimodal, separable/nonseparable, and the impact of several distance measurements and parameters on WPA is discussed. What is more, the compared simulation experiments with other five typical intelligent algorithms, genetic algorithm, particle swarm optimization algorithm, artificial fish swarm algorithm, artificial bee colony algorithm, and firefly algorithm, show that WPA has better convergence and robustness, especially for high-dimensional functions. [ABSTRACT FROM AUTHOR]
- Published
- 2014
- Full Text
- View/download PDF
26. Robust Filtering for Networked Stochastic Systems Subject to Sensor Nonlinearity.
- Author
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Guoqiang Wu, Jianwei Zhang, and Yuguang Bai
- Subjects
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ROBUST control , *STOCHASTIC systems , *NONLINEAR theories , *LINEAR systems , *RANDOM variables , *BERNOULLI equation , *MATHEMATICAL optimization - Abstract
The problem of network-based robust filtering for stochastic systems with sensor nonlinearity is investigated in this paper. In the network environment, the effects of the sensor saturation, output quantization, and network-induced delay are taken into simultaneous consideration, and the output measurements received in the filter side are incomplete. The random delays are modeled as a linear function of the stochastic variable described by a Bernoulli randombinary distribution. The derived criteria for performance analysis of the filtering-error system and filter design are proposed which can be solved by using convex optimization method. Numerical examples show the effectiveness of the design method. [ABSTRACT FROM AUTHOR]
- Published
- 2013
- Full Text
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27. Robust Distributed Model Predictive Load Frequency Control of Interconnected Power System.
- Author
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Xiangjie Liu, Huiyun Nong, Ke Xi, and Xiuming Yao
- Subjects
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INTERCONNECTED power systems , *ROBUST control , *PREDICTION models , *ELECTRICAL load , *UNCERTAINTY (Information theory) , *ELECTRIC power production , *MATHEMATICAL optimization , *LINEAR matrix inequalities - Abstract
Considering the load frequency control (LFC) of large-scale power system, a robust distributed model predictive control (RDMPC) is presented. The system uncertainty according to power system parameter variation alone with the generation rate constraints (GRC) is included in the synthesis procedure. The entire power system is composed of several control areas, and the problem is formulated as convex optimization problem with linear matrix inequalities (LMI) that can be solved efficiently. It minimizes an upper bound on a robust performance objective for each subsystem. Simulation results showgood dynamic response and robustness in the presence of power system dynamic uncertainties. [ABSTRACT FROM AUTHOR]
- Published
- 2013
- Full Text
- View/download PDF
28. An Improved Harmony Search Based on Teaching-Learning Strategy for Unconstrained Optimization Problems.
- Author
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Shouheng Tuo, Longquan Yong, and Tao Zhou
- Subjects
- *
SEARCH algorithms , *MATHEMATICAL optimization , *METAHEURISTIC algorithms , *MUSIC improvisation , *STOCHASTIC convergence , *ROBUST control , *MACHINE learning - Abstract
Harmony search (HS) algorithm is an emerging population-based metaheuristic algorithm, which is inspired by the music improvisation process. The HS method has been developed rapidly and applied widely during the past decade. In this paper, an improved global harmony search algorithm, named harmony search based on teaching-learning (HSTL), is presented for high dimension complex optimization problems. InHSTL algorithm, four strategies (harmonymemory consideration, teaching-learning strategy, local pitch adjusting, and random mutation) are employed to maintain the proper balance between convergence and population diversity, and dynamic strategy is adopted to change the parameters. The proposed HSTL algorithm is investigated and compared with three other state-of-the-art HS optimization algorithms. Furthermore, to demonstrate the robustness and convergence, the success rate and convergence analysis is also studied. The experimental results of 31 complex benchmark functions demonstrate that the HSTL method has strong convergence and robustness and has better balance capacity of space exploration and local exploitation on high dimension complex optimization problems. [ABSTRACT FROM AUTHOR]
- Published
- 2013
- Full Text
- View/download PDF
29. A Hybrid Multiobjective Genetic Algorithm for Robust Resource-Constrained Project Scheduling with Stochastic Durations.
- Author
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Jian Xiong, Ying-wu Chen, Ke-wei Yang, Qing-song Zhao, and Li-ning Xing
- Subjects
- *
GENETIC algorithms , *PERTURBATION theory , *APPROXIMATION theory , *FUNCTIONAL analysis , *MATHEMATICAL optimization , *ROBUST control - Abstract
We study resource-constrained project scheduling problems with perturbation on activity durations. With the consideration of robustness and stability of a schedule, we model the problem as a multiobjective optimization problem. Three objectives-- makespan minimization, robustness maximization, and stability maximization--are simultaneously considered. We propose a hybrid multiobjective evolutionary algorithm (H-MOEA) to solve this problem. In the process of the H-MOEA, the heuristic information is extracted periodically from the obtained nondominated solutions, and a local search procedure based on the accumulated information is incorporated. The results obtained from the computational study show that the proposed approach is feasible and effective for the resource-constrained project scheduling problems with stochastic durations. [ABSTRACT FROM AUTHOR]
- Published
- 2012
- Full Text
- View/download PDF
30. Enhancement of the Quality and Robustness in Synchronization of Nonlinear Lur'e Dynamical Networks.
- Author
-
Shiyun Xu, Yong Tang, Huadong Sun, Ziguan Zhou, and Ying Yang
- Subjects
- *
DYNAMICAL systems , *SYNCHRONIZATION , *MATRIX inequalities , *MATHEMATICAL optimization , *ASYMPTOTIC theory of system theory , *ROBUST control - Abstract
In order to improve the synchronous reliability and dependability of complex dynamical networks, methods need to be proposed to enhance the quality and robustness of the synchronization scheme. The present study focuses on the robust fault detection issue within the synchronization for a class of nonlinear dynamical networks composed by identical Lur'e systems. Sufficient conditions in terms of linear matrix inequalities (LMIs) are established to guarantee global robust ...-/...∞ synchronization of the network. Under such a synchronization scheme, the error dynamical system is globally asymptotically stable, the effect of external disturbances is suppressed, and at the same time, the network is sensitive to possible faults based on a mixed ...-/H∞ performance. The fault sensitivity ...- index, moreover, can be optimized via a convex optimization algorithm. The effectiveness and applicability of the analytical results are demonstrated through a network example composed by the Chua's circuit, and it shows that the quality and robustness of synchronization has been greatly enhanced. [ABSTRACT FROM AUTHOR]
- Published
- 2012
- Full Text
- View/download PDF
31. Quality Improvement and Robust Design Methods to a Pharmaceutical Research and Development.
- Author
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Byung Rae Cho and Sangmun Shin
- Subjects
- *
DRUG design , *RESEARCH & development , *ROBUST control , *MATHEMATICAL optimization , *MANUFACTURING processes , *MANUFACTURING execution systems - Abstract
Researchers often identify robust design, based on the concept of building quality into products or processes, as one of the most important systems engineering design concepts for quality improvement and process optimization. Traditional robust design principles have often been applied to situations in which the quality characteristics of interest are typically time-insensitive. In pharmaceutical manufacturing processes, time-oriented quality characteristics, such as the degradation of a drug, are often of interest. As a result, current robust design models for quality improvement which have been studied in the literature may not be effective in finding robust design solutions. In this paper, we show how the robust design concepts can be applied to the pharmaceutical production research and development by proposing experimental and optimization models which should be able to handle the time-oriented characteristics. This is perhaps the first attempt in the robust design field. An example is given, and comparative studies are discussed for model verification. [ABSTRACT FROM AUTHOR]
- Published
- 2012
- Full Text
- View/download PDF
32. Robust Design Optimization of an Aerospace Vehicle Prolusion System.
- Author
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Raza, Muhammad Aamir and Wang Liang
- Subjects
- *
MULTIDISCIPLINARY design optimization , *ROBUST control , *AEROSPACE engineering , *MATHEMATICAL optimization , *SENSITIVITY analysis , *AEROSPACE propulsion systems - Abstract
This paper proposes a robust design optimization methodology under design uncertainties of an aerospace vehicle propulsion system. The approach consists of 3D geometric design coupled with complex internal ballistics, hybrid optimization, worst-case deviation, and efficient statistical approach. The uncertainties are propagated through worst-case deviation using first-order orthogonal design matrices. The robustness assessment is measured using the framework of mean-variance and percentile difference approach. A parametric sensitivity analysis is carried out to analyze the effects of design variables variation on performance parameters. A hybrid simulated annealing and pattern search approach is used as an optimizer. The results show the objective function of optimizing the mean performance and minimizing the variation of performance parameters in terms of thrust ratio and total impulse could be achieved while adhering to the system constraints. [ABSTRACT FROM AUTHOR]
- Published
- 2011
- Full Text
- View/download PDF
33. Game Approach for H∞ Robust Control Strategy to Follow the Production in the Singularly Perturbed Bilinear Dynamic Input-Output Systems
- Author
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Cheng-ke Zhang, Huai-nian Zhu, Qiyou Liu, and Ning Bin
- Subjects
Input/output ,Mathematical optimization ,National economy ,Control theory ,General Mathematics ,Differential game ,General Engineering ,Bilinear interpolation ,Production (economics) ,Robust control ,Social production ,Saddle ,Mathematics - Abstract
For simulating and analyzing the input and output problem of national economy more accurately, this paper considers the fast and slow production processes during the course of social production development, takes stochastic economic risks into consideration, and constructs a H∞ robust control model to follow the production in the singularly perturbed dynamic input-output systems. Further introducing ideas of noncooperative differential game theory, the H∞ robust control model is transformed into a saddle-point equilibrium game model, and a new method for solving dynamic input-output problem by using saddle-point equilibrium strategies is obtained. A numerical result is presented in the end to illustrate the effectiveness of the method.
- Published
- 2017
34. Robust Stabilization andH∞Control for Uncertain Neural Networks with Mixed Time Delays
- Author
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Bin Wen, Li Liang, and Hui Li
- Subjects
Lyapunov stability ,Mathematical optimization ,Adaptive control ,Artificial neural network ,Control theory ,General Mathematics ,General Engineering ,Stability (learning theory) ,Linear matrix inequality ,Convex combination ,Robust control ,Mathematics - Abstract
This paper is concerned with the problem of robust stabilization andH∞control for a class of uncertain neural networks. For the robust stabilization problem, sufficient conditions are derived based on the quadratic convex combination property together with Lyapunov stability theory. The feedback controller we design ensures the robust stability of uncertain neural networks with mixed time delays. We further design a robustH∞controller which guarantees the robust stability of the uncertain neural networks with a givenH∞performance level. The delay-dependent criteria are derived in terms of LMI (linear matrix inequality). Finally, numerical examples are provided to show the effectiveness of the obtained results.
- Published
- 2015
35. RobustH∞Control for a Class of Uncertain Switched Fuzzy Time-Delay Systems Based on T-S Models
- Author
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Xue Wang, Yang Cui, Kaiqing Liu, and Yang Zhao
- Subjects
Computer Science::Machine Learning ,Lyapunov function ,Mathematical optimization ,Article Subject ,lcsh:Mathematics ,General Mathematics ,General Engineering ,Linear matrix inequality ,Fuzzy control system ,lcsh:QA1-939 ,Computer Science::Digital Libraries ,Fuzzy logic ,Statistics::Machine Learning ,symbols.namesake ,Exponential stability ,lcsh:TA1-2040 ,Control theory ,Computer Science::Mathematical Software ,symbols ,Fuzzy number ,Robust control ,lcsh:Engineering (General). Civil engineering (General) ,Mathematics - Abstract
The problem of robustH∞control for a class of uncertain switched fuzzy time-delay systems is discussed for system described by T-S fuzzy model with Lyapunov stable theory and linear matrix inequality approach. A sufficient condition in terms of the LMI is derived such that the stability of the closed-loop systems is guaranteed. The continuous state feedback controller is built to ensure the asymptotically stable closed-loop system for all allowable uncertainties, with the switching law designed to implement the global asymptotic stability of uncertain switched fuzzy time-delay systems. In this model, each and every subsystem of the switched systems is an uncertain fuzzy one to which the parallel distributed compensation (PDC) controller of each sub fuzzy system system is proposed with its main condition given in a more solvable form of convex combinations. Such a switched control system is highly robust to varying parameters. A simulation shows the feasibility and effectiveness of the design method.
- Published
- 2013
36. RobustH∞Control for Discrete-Time Stochastic Interval System with Time Delay
- Author
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Guici Chen, Shengchun Yu, and Yi Shen
- Subjects
Mathematical optimization ,Correctness ,Discrete time and continuous time ,Control theory ,General Mathematics ,General Engineering ,Linear matrix inequality ,Interval (mathematics) ,Robust control ,Mathematics - Abstract
The robustH∞control problem for discrete-time stochastic interval system (DTSIS) with time delay is investigated in this paper. The stochastic interval system is equivalently transformed into a kind of stochastic uncertain time-delay system firstly. By constructing the appropriate Lyapunov-Krasovskii functional, the sufficient conditions for the existence of the robustH∞controller for DTSIS are obtained in terms of linear matrix inequality (LMI) form, and the robustH∞controller is designed. Finally, a numerical example with simulation is given to show the effectiveness and correctness of the designed robustH∞controller.
- Published
- 2013
37. Robust Passivity and Feedback Design for Nonlinear Stochastic Systems with Structural Uncertainty
- Author
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Yuguang Niu, Zhongwei Lin, and Jizhen Liu
- Subjects
Mathematical optimization ,Lemma (mathematics) ,Article Subject ,lcsh:Mathematics ,General Mathematics ,Passivity ,General Engineering ,lcsh:QA1-939 ,Nonlinear system ,lcsh:TA1-2040 ,Control theory ,Stability theory ,Minimum phase ,Robust control ,lcsh:Engineering (General). Civil engineering (General) ,Passivity theory ,Mathematics - Abstract
This paper discusses the robust passivity and global stabilization problems for a class of uncertain nonlinear stochastic systems with structural uncertainties. A robust version of stochastic Kalman-Yakubovitch-Popov (KYP) lemma is established, which sustains the robust passivity of the system. Moreover, a robust strongly minimum phase system is defined, based on which the uncertain nonlinear stochastic system can be feedback equivalent to a robust passive system. Following with the robust passivity theory, a global stabilizing control is designed, which guarantees that the closed-loop system is globally asymptotically stable in probability (GASP). A numerical example is presented to illustrate the effectiveness of our results.
- Published
- 2013
38. RobustH∞Control of Uncertain T-S Fuzzy Time-Delay System: A Delay Decomposition Approach
- Author
-
Chunsong Han and Cheng Gong
- Subjects
Mathematical optimization ,Control theory ,General Mathematics ,General Engineering ,Decomposition (computer science) ,Fuzzy control system ,Robust control ,Linear matrix ,Fuzzy logic ,System a ,Mathematics - Abstract
This paper is concerned with the problem of robustH∞control for a class of uncertain time-delay fuzzy systems with norm-bounded parameter uncertainties. By utilizing the instrumental idea of delay decomposition, the decomposed Lyapunov-Krasovskii functional is introduced to uncertain T-S fuzzy system, and some delay-dependent conditions for the existence of robust controller are formulated in the form of linear matrix inequalities (LMIs). When these LMIs are feasible, a controller is presented. A numerical example is given to demonstrate the effectiveness of the proposed method.
- Published
- 2013
39. Robust control of discrete-time hybrid systems with uncertain modal dynamics
- Author
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Thordur Runolfsson
- Subjects
020301 aerospace & aeronautics ,0209 industrial biotechnology ,Mathematical optimization ,Engineering ,Markov chain ,business.industry ,General Mathematics ,lcsh:Mathematics ,General Engineering ,02 engineering and technology ,lcsh:QA1-939 ,Automaton ,Variable (computer science) ,020901 industrial engineering & automation ,Modal ,0203 mechanical engineering ,Discrete time and continuous time ,Control theory ,lcsh:TA1-2040 ,Hybrid system ,Sensitivity (control systems) ,Robust control ,business ,lcsh:Engineering (General). Civil engineering (General) - Abstract
We study systems that are subject to sudden structural changes due to either changes in the operational mode of the system or failure. We consider linear dynamicalsystems that depend on a modal variable which is either modeled as a finite-state Markov chain or generated by an automaton that is subject to an external disturbance. In the Markov chain case, the objective of the control is to minimize a risk-sensitive cost functional. The risk-sensitive cost functional measures the risk sensitivity of the system to transitions caused by the random modal variable. In the case when a disturbed automaton describes the modal variable, the objective of the control is to make the system as robust to changes in the external disturbance as possible. Optimality conditions for both problems are derived and it is shown that the disturbance rejection problem is closely related to a certain risk-sensitive control problem for the hybrid system.
- Published
- 2004
40. Robust stochastic maximum principle: Complete proof and discussions
- Author
-
Alexander S. Poznyak
- Subjects
Continuous-time stochastic process ,Mathematical optimization ,lcsh:Mathematics ,General Mathematics ,General Engineering ,lcsh:QA1-939 ,Optimal control ,Minimax ,Stochastic programming ,Stochastic partial differential equation ,Stochastic differential equation ,Maximum principle ,lcsh:TA1-2040 ,Stochastic optimization ,Robust control ,Minimax problem ,Stochastic processes ,lcsh:Engineering (General). Civil engineering (General) ,Mathematics - Abstract
This paper develops a version of Robust Stochastic Maximum Principle (RSMP) applied to the Minimax Mayer Problem formulated for stochastic differential equations with the control-dependent diffusion term. The parametric families of first and second order adjoint stochastic processes are introduced to construct the corresponding Hamiltonian formalism. The Hamiltonian function used for the construction of the robust optimal control is shown to be equal to the Lebesque integral over a parametric set of the standard stochastic Hamiltonians corresponding to a fixed value of the uncertain parameter. The paper deals with a cost function given at finite horizon and containing the mathematical expectation of a terminal term. A terminal condition, covered by a vector function, is also considered. The optimal control strategies, adapted for available information, for the wide class of uncertain systems given by an stochastic differential equation with unknown parameters from a given compact set, are constructed. This problem belongs to the class of minimax stochastic optimization problems. The proof is based on the recent results obtained for Minimax Mayer Problem with a finite uncertainty set [14,43-45] as well as on the variation results of [53] derived for Stochastic Maximum Principle for nonlinear stochastic systems under complete information. The corresponding discussion of the obtain results concludes this study.
- Published
- 2002
41. Robust stability and stabilization of a class of uncertain nonlinear systems with delays
- Author
-
Magdi S. Mahmoud
- Subjects
Mathematical optimization ,General Mathematics ,lcsh:Mathematics ,General Engineering ,Continuous stirred-tank reactor ,Linear matrix ,lcsh:QA1-939 ,Nonlinear system ,Robustness (computer science) ,Control theory ,lcsh:TA1-2040 ,Robust control ,lcsh:Engineering (General). Civil engineering (General) ,Mathematics - Abstract
A class of nonlinear systems with norm-bounded uncertainties and state-delay is considered. Two criteria are developed for the robust stability analysis: one is delay-independent and the other is delay-dependent. Methods for robust feedback synthesis are then examined. It is established that linear memoryless controllers are capable of guaranteeing the delay-dependent and delay-independent stabilizability of the closed-loop systems. All the results are expressed in the form of linear matrix inequalities which can be solved by efficient and numerically-stable routines. The developed theory is applied to the stability robustness problem of an industrial jacketed continuous stirred tank reactor.
- Published
- 1998
42. Robust performance results for discrete-time systems
- Author
-
Magdi S. Mahmoud
- Subjects
Mathematical optimization ,lcsh:Mathematics ,General Mathematics ,Feedback control ,Robust performance ,Uncertain sytems ,Linear matrix inequalities ,General Engineering ,Stability (learning theory) ,Linear matrix ,lcsh:QA1-939 ,Performance results ,Discrete time and continuous time ,lcsh:TA1-2040 ,Control theory ,Robust control ,lcsh:Engineering (General). Civil engineering (General) ,Mathematics ,Parametric statistics - Abstract
The problems of robust performance and feedback control synthesis for a class of linear discrete-time systems with time-varying parametric uncertainties are addressed in this paper. The uncertainties are bound and have a linear matrix fractional form. Based on the concept of strongly robust H∞-performance criterion, results of robust stability and performance are developed and expressed in easily computable linear matrix inequalities. Synthesis of robust feedback controllers is carried out for several system models of interest.
- Published
- 1998
43. Robust Quadratic Regression and Its Application to Energy-Growth Consumption Problem
- Author
-
Yongzhi Wang, Fuliang Zhang, Yuli Zhang, and Jining Yi
- Subjects
Polynomial regression ,Semidefinite programming ,Mathematical optimization ,Article Subject ,General Mathematics ,lcsh:Mathematics ,General Engineering ,Robust optimization ,Residual ,lcsh:QA1-939 ,Robust regression ,lcsh:TA1-2040 ,Norm (mathematics) ,Outlier ,Robust control ,lcsh:Engineering (General). Civil engineering (General) ,Mathematics - Abstract
We propose a robust quadratic regression model to handle the statistics inaccuracy. Unlike the traditional robust statistic approaches that mainly focus on eliminating the effect of outliers, the proposed model employs the recently developed robust optimization methodology and tries to minimize the worst-case residual errors. First, we give a solvable equivalent semidefinite programming for the robust least square model with ball uncertainty set. Then the result is generalized to robust models underl1- andl∞-norm critera with general ellipsoid uncertainty sets. In addition, we establish a robust regression model for per capital GDP and energy consumption in the energy-growth problem under the conservation hypothesis. Finally, numerical experiments are carried out to verify the effectiveness of the proposed models and demonstrate the effect of the uncertainty perturbation on the robust models.
- Published
- 2013
- Full Text
- View/download PDF
44. Observer-Based Robust Adaptive Fuzzy Control for MIMO Nonlinear Uncertain Systems with Delayed Output
- Author
-
Chiang-Cheng Chiang
- Subjects
Lyapunov function ,Mathematical optimization ,Adaptive control ,Article Subject ,Observer (quantum physics) ,General Mathematics ,lcsh:Mathematics ,General Engineering ,Fuzzy control system ,lcsh:QA1-939 ,Fuzzy logic ,symbols.namesake ,Control theory ,lcsh:TA1-2040 ,symbols ,State observer ,Robust control ,lcsh:Engineering (General). Civil engineering (General) ,Mathematics - Abstract
An observer-based robust adaptive fuzzy control scheme is presented to tackle the problem of the robust stability and the tracking control for a class of multiinput multioutput (MIMO) nonlinear uncertain systems with delayed output. Because the nonlinear system functions and the uncertainties of the controlled system including structural uncertainties are supposed to be unknown, fuzzy logic systems are utilized to approximate these nonlinear system functions and the upper bounded functions of the uncertainties. Moreover, the upper bound of uncertainties caused by these fuzzy modeling errors is also estimated. In addition, the state observer based on state variable filters is designed to estimate all states which are not available for measurement in the controlled system. By constructing an appropriate Lyapunov function and using strictly positive-real (SPR) stability theorem, the proposed robust adaptive fuzzy controller not only guarantees the robust stability of a class of multivariable nonlinear uncertain systems with delayed output but also maintains a good tracking performance. Finally, some simulation results are illustrated to verify the effectiveness of the proposed control approach.
- Published
- 2013
45. Adaptive Fuzzy Robust Control for a Class of Nonlinear Systems via Small Gain Theorem
- Author
-
Shaoping Wang and Xingjian Wang
- Subjects
Mathematical optimization ,Adaptive control ,Article Subject ,General Mathematics ,lcsh:Mathematics ,General Engineering ,Fuzzy control system ,lcsh:QA1-939 ,Fuzzy logic ,Small-gain theorem ,Robustness (computer science) ,Control theory ,lcsh:TA1-2040 ,Backstepping ,Control system ,Robust control ,lcsh:Engineering (General). Civil engineering (General) ,Mathematics - Abstract
Practical nonlinear systems can usually be represented by partly linearizable models with unknown nonlinearities and external disturbances. Based on this consideration, we propose a novel adaptive fuzzy robust control (AFRC) algorithm for such systems. The AFRC effectively combines techniques of adaptive control and fuzzy control, and it improves the performance by retaining the advantages of both methods. The linearizable part will be linearly parameterized with unknown but constant parameters, and the discontinuous-projection-based adaptive control law is used to compensate these parts. The Takagi-Sugeno fuzzy logic systems are used to approximate unknown nonlinearities. Robust control law ensures the robustness of closed-loop control system. A systematic design procedure of the AFRC algorithm by combining the backstepping technique and small-gain approach is presented. Then the closed-loop stability is studied by using small gain theorem, and the result indicates that the closed-loop system is semiglobally uniformly ultimately bounded.
- Published
- 2013
46. A unified approach to fixed-order controller design via linear matrix inequalities
- Author
-
Tetsuya Iwasaki and Robert E. Skelton
- Subjects
Controller design ,Mathematical optimization ,Inequality ,lcsh:Mathematics ,General Mathematics ,media_common.quotation_subject ,linear systems ,General Engineering ,Linear matrix inequality ,Linear matrix ,Covariance ,lcsh:QA1-939 ,Control theory ,lcsh:TA1-2040 ,Robustness (computer science) ,Linear algebra ,lcsh:Engineering (General). Civil engineering (General) ,robust control ,media_common ,Mathematics - Abstract
We consider the design of fixed-order (or low-order) linear controllers which meet certain performance and/or robustness specifications. The following three problems are considered; covariance control as a nominal performance problem,𝒬-stabilization as a robust stabilization problem, and robustL∞control problem as a robust performance problem. All three control problems are converted to a single linear algebra problem of solving a linear matrix inequality (LMI) of the typeBGC+(BGC)T+Q<0for the unknown matrixG. Thus this paper addresses the fixed-order controller design problem in a unified way. Necessary and sufficient conditions for the existence of a fixed-order controller which satisfies the design specifications for each problem are derived, and an explicit controller formula is given. In any case, the resulting problem is shown to be a search for a (structured) positive definite matrixXsuch thatX∈𝒞1andX−1∈𝒞2where𝒞1and𝒞2are convex sets defined by LMIs. Computational aspects of the nonconvex LMI problem are discussed.
- Published
- 1995
47. Nonlinear Nonconvex Optimization by Evolutionary Algorithms Applied to Robust Control
- Author
-
Joaquín Cervera and Alfonso Baños
- Subjects
Mathematical optimization ,Article Subject ,General Mathematics ,lcsh:Mathematics ,General Engineering ,Evolutionary algorithm ,Context (language use) ,Function (mathematics) ,lcsh:QA1-939 ,Nonlinear system ,Quantitative feedback theory ,Local optimum ,Control theory ,lcsh:TA1-2040 ,Robust control ,Heuristics ,lcsh:Engineering (General). Civil engineering (General) ,Mathematics - Abstract
This work focuses on the problem of automatic loop shaping in the context of robust control. More specifically in the framework given by Quantitative Feedback Theory (QFT), traditionally the search of an optimum design, a non convex and nonlinear optimization problem, is simplified by linearizing and/or convexifying the problem. In this work, the authors propose a suboptimal solution using a fixed structure in the compensator and evolutionary optimization. The main idea in relation to previous work consists of the study of the use of fractional compensators, which give singular properties to automatically shape the open loop gain function with a minimum set of parameters, which is crucial for the success of evolutionary algorithms. Additional heuristics are proposed in order to guide evolutionary process towards close to optimum solutions, focusing on local optima avoidance.
- Published
- 2009
- Full Text
- View/download PDF
48. Constrained regulator problem for linear uncertain systems: Control of a pH process
- Author
-
Fouad Mesquine, Fernando Tadeo, and Abdellatif Benlamkadem
- Subjects
Mathematical optimization ,Engineering ,Adaptive control ,business.industry ,General Mathematics ,lcsh:Mathematics ,Control (management) ,General Engineering ,Process (computing) ,Regulator ,Uncertain systems ,Linear-quadratic-Gaussian control ,lcsh:QA1-939 ,Exponential stability ,Control theory ,lcsh:TA1-2040 ,Robust control ,business ,lcsh:Engineering (General). Civil engineering (General) - Abstract
The regulator problem for linear uncertain continuous-time systems having control constraints is considered. Necessary and sufficient conditions of positive invariance of polyhedral domains are extended to the case of continuous-time uncertain systems. Robust constrained regulators are then derived. An application to the control of pH in a stirred tank is then presented. First, the uncertainty in the pH process is evaluated from first-principle models, then the design of a robust constrained regulator is presented. Simulation results show that this control law is easy to implement and that robust asymptotic stability and control admissibility are guaranteed.
- Published
- 2006
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