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Abstract: Good cross-directional control of sheet variables in a paper machine depends on a number of factors. One such factor is the correct alignment of actuators with their corresponding responses. The alignment changes with time either locally or across the whole paper sheet due to a variety of reasons. In this paper, we provide an online mapping technique based on estimating the cross-correlation between actuator movement and the measurements. This procedure involves two steps–in the first step (called alignment monitoring) we determine if the current mapping is wrong at any CD position, and in the second step (called re-mapping), the alignment of actuators is corrected. The main advantage of this method is in its ability to re-align under closed loop conditions with minimal operational disruption. [Copyright &y& Elsevier]

A mechanistic nonlinear model of the wet end of paper machine 6 (PM6) at Norske Skog Saugbrugs, Norway has been developed, and used in an industrial MPC implementation. The MPC uses an infinite horizon criterion, successive linearization of the model, and estimation of states and parameters by an augmented Kalman filter. Variation in important quality variables and consistencies in the wet end have been reduced substantially, compared to the variation prior to the MPC implementation. The MPC also provides better efficiency through faster grade changes, control during sheet breaks and start ups, and better control during periods of poor measurements. From May 2002 of the MPC has been the preferred controller choice for the process operators at PM6.In this paper we also study if the model can be applied to PM4 at Norske Skog Saugbrugs, and PM3 at Norske Skog Skogn, Norway. No structural changes were necessary in order to fit the model to PM4 and PM3 data. The time spent on fitting the PM6 model to PM4 and PM3 is approximately 1% of the time spent on developing the original model. This should be a strong incentive for focusing on mechanistic modeling in industries were there are many similar production lines or units. [Copyright &y& Elsevier]

A multivariable, time invariant model for a Fourdrinier machine headbox is considered. Analysis procedures enabling safe, economical closed loop response regulation are outlined. An optimum, minimum control effort strategy is proposed. Simulated open and closed loop response records are computed. The effectiveness of the design procedure, which minimises the power consumption for regulation purposes improving reliability and reducing refit and maintenance costs thereby, is commented upon. [Copyright &y& Elsevier]

This paper takes a reaction-diffusion predator-prey system with ratio-dependent Holling III functional response function and Leslie-Gower term into consideration. First of all, the system model is proposed on the basis of basic biological assumptions and previous work, and the existence conditions of the equilibrium point of the system are discussed. Secondly, under the assumption of the existence of equilibrium point, the Turing instability necessary conditions induced by diffusion are investigated. Thirdly, optimal control theory is derived, and the adjoint system and the first-order optimization condition are established. Fourthly, parameter identification based on optimal control is studied, and the technique is extended to network structure. Finally, extensive numerical simulations, including Turing pattern, Normalized Population High Distribution Area (NPHDA) diagram and parameter identification, are carried out to illustrate and validate the analytical results. For the system dynamics phenomena, the results from different perspectives effectively demonstrate that the theoretical findings, numerical simulations and natural reality are identical. In terms of the parameter identification of continuous model and network model, the efficiency and accuracy of various algorithms are fully tested. • This paper proposes and investigates index normalized population height distribution area. • The optimal control problem of reaction-diffusion predator-prey system is formally derived. • The parameter identification research is extended to population network structure space. [ABSTRACT FROM AUTHOR]

The application of optimal control theory in practical engineering is often limited by the modeling cost and complexity of the mathematical model of the controlled plant, and various constraints. To bridge the gap between the theory and practice, this paper proposes a model-free direct method based on the sequential sampling and updating of surrogate model, and extends the ability of direct method to solve model-free optimal control problems with general constraints. The algorithm selects sample points from the current actual trajectory data to update the surrogate model of controlled plant, and solve the optimal control problem of the constantly refined surrogate model until the result converges. The presented initial and subsequent sampling strategies eliminate the dependence on the model. Furthermore, the new stopping criteria ensure the overlap of final actual and planned trajectories. The several examples illustrate that the presented algorithm can obtain constrained solutions with greater accuracy and require fewer sample data. • The proposed sampling strategies do not depend on the models of controlled plant. • New stopping criteria ensure the overlap of final actual and planned trajectories. • Model-free direct method can deal with constrained optimal control problems well. [ABSTRACT FROM AUTHOR]

This paper investigates the problem of finite-time H ∞ synchronization (H ∞ FTS) for complex dynamical networks (CDNs) with time-varying delays(TVDs) and unknown internal coupling matrices. External disturbances are also considered into this model. By applying the adaptive control theory, this paper presents the adaptive control method to solve the H ∞ FTS of CDNs with external disturbances and TVDs. Some criteria are obtained by utilizing appropriate adaptive controllers and devising a special Lyapunov–Krasovskii function (LKF), which ensure the H ∞ FTS of CDNs based on passivity theory. Finally, using some effective mathematical techniques, comparative numerical example and Chua's circuit system are used to explain the advantages and applicability of the results and approaches. • Firstly, the main results in this thesis about finite-time H ∞ synchronization problem are obtained based on the finite-time synchronization theory. Meanwhile, a set of augmented LKF is established, which greatly improves the flexibility of the functions. • Secondly, the control method is different from that in Ma and Ma (2016), the new adaptive feedback controller utilized in this thesis make it easy to achieve finite-time H ∞ synchronization. And by introducing some uncertainty matrices, the conditions obtained have less conservative. • Thirdly, different from Jing et al., (2019), considering the inner-coupling strength d l , l = 1 , 2 , ... , n is unknown in this thesis, we describe the inner-coupling matrix D as D = D 0 + Γ D 1 . By appropriately adjusting the unknown internal coupling strength, the conservative of the conditions we obtained is reduced, at the same time, the synchronization time of the system is shortened. • Three simulation examples are submitted to illuminate the validity of the consequences. Chua's circuit system can verify this result, and it manifests the applicability of the results and approaches. [ABSTRACT FROM AUTHOR]

Interior Permanent Magnet Synchronous Motors (IPMSMs) offer excellent features, however, the dynamic complexity of these motors has always caused a challenge to control them. In addition, Field Oriented Control (FOC) method developed using Proportional–Integral (PI) regulators, which is the most implemented approach to control the IPMSM, is associated with slow dynamic response and saturation in the controller. This paper presents a novel control algorithm based on State Feedback (SF) regulator for IPMSM drives. The focus of the paper is on simplifying the dynamic of the IPMSM using nonlinear analysis methods and enhancing the response of the designed control approach. The development of the control system starts with linearizing the dynamics of the IPMSM. A linearization approach based on Quadratic Linearization Method (QLM) is proposed and then the linear model is used for designing a state feedback controller optimized by Linear Quadratic Regulator (LQR) method. Applying control constraints is a challenge in systems controlled by state feedback theory. Hence, the proposed control method offers a novel solution based on hysteresis control theory. The proposed hysteresis technique offers several advantages such as lowering overshoot in speed step response in addition to applying constraints and it eliminates all drawbacks of hysteresis controllers. To control the IPMSM in the whole speed range (constant torque and constant power regions), the proposed approach adopts Maximum Torque per Ampere (MTPA) and Voltage Constraint Tracking (VCT) control strategies. Finally, simulations are carried out in MATLAB/SIMULINK environment to compare the performance of the proposed controller with the conventional FOC method. • Quadratic linearization creates a singularity-free linearization for IPMSM. • Quadratic Linearization is an exact linearization method for second-order systems. • State feedback control is used to eliminate problems associated with PI controller. • A reference reforming-based technique is proposed to apply control constraints. • The defects of hysteresis controllers do not exist in hysteresis reference reformer. [ABSTRACT FROM AUTHOR]

In this paper, a novel compound fault-tolerant attitude control (FTC) scheme is proposed for reentry hypersonic vehicles with aerodynamic surfaces and reaction control systems (RCS) in the presence of parameter uncertainties, external disturbances and aerodynamic surfaces faults. Aerodynamic surfaces work as the primary actuators and RCS serve as auxiliary actuators. When aerodynamic surfaces cannot provide the required attitude control torque due to low dynamic pressure or faults, RCS are activated to assist aerodynamic surfaces to generate the residual torque. A nonlinear disturbance observer-based sliding mode controller is designed to calculate the required attitude control torque which can handle the parametric uncertainties and external disturbances together. The quadratic programming method is applied to obtain the optimal aerodynamic surfaces deflections from the required control torque. An innovative fuzzy rule-based decision-making system is design to solve the RCS control allocation problem, which is conceptually easy to understand and computationally efficiently compared with existing approaches. Based on quantized control theory, the closed-loop control system stability is rigorously analyzed. Simulation results are given to demonstrate the effectiveness and efficiency of developed FTC scheme. • This paper proposes a novel actuator fault-tolerant control scheme for reentry hypersonic vehicle equipped with aerodynamic surfaces and RCS and subject to uncertain modeling errors, unknown external disturbances and actuator faults. A nonlinear disturbance observer-based sliding mode controller is designed to calculate the required attitude control torque which can handle system uncertainties and external disturbances together. • When the aerodynamic surfaces are not capable of providing the required attitude control torque due to low dynamic pressure or faults, RCS are activated to assist aerodynamic surfaces to provide the residual torque. A novel fuzzy rule based RCS allocation scheme is proposed to solve the problem of complex mappings from control torques to the on/off states of thrusters. Compared with existing RCS allocation methods, the designed fuzzy rule based control allocation scheme reduces computational cost and has better practicability. • The closed-loop system stability under continuous torque provided by aerodynamic surfaces and discrete torque provided by RCS is rigorously analyzed based on quantized control theory. [ABSTRACT FROM AUTHOR]

Abstract This paper is concerned with state estimation approach to track aircraft engine gas-path health condition in an advanced distributed architecture. The sensor measurements are divided into several subsets by installation position along gas path, and they are integrated to estimate engine health state changes with sensor fusion uncertainty. The uncertain sensor fusion is characterized by time delay and packet dropout in the fusion behavior of sensor measurements, and the delay steps occur randomly. A novel distributed extended Kalman filter with the data buffer bank (DEKF) is developed, and self-tuning buffer strategy of recursive fusion estimation is combined to the DEKF to form the self-tuning DEKF (SDEKF) algorithm for improving state estimation performance. The lengths of data buffer bank related to the local filters of SDEKF are different, and they are independently adaptive to the information loss level and local estimation accuracy. Local states are calculated using the measurements collected at the latest steps in self-tuning buffer banks, and then sent to master filter to yield global state and covariance by fusion estimation. The contribution of this study is to propose a novel EKF algorithm for state estimation in the distributed framework with sensor fusion uncertainty, and it achieves better trade-off between the estimation accuracy and computational efforts. The systematical comparisons of basic EKF, constant buffer DEKF and SDEKF algorithms are carried out for aircraft engine gas-path health estimation with sensor fusion uncertainty. The simulation results show the superiority of the SDEKF, and it confirms our viewpoints in this paper. [ABSTRACT FROM AUTHOR]

This work is focused on the application of functional-type a posteriori error estimates and corresponding indicators to a class of time-dependent problems. We consider the algorithmic part of their derivation and implementation and also discuss the numerical properties of these bounds that comply with obtained numerical results. This paper examines two different methods of solution approximation for evolutionary models, i.e., a time-marching technique and a space–time approach. The first part of the study presents an algorithm for global minimisation of the majorant on each of discretisation time-cylinders (time-slabs), the effectiveness of this approach to error estimation is confirmed by extensive numerical tests. In the second part of the publication, the application of functional error estimates is discussed with respect to a space–time approach. It is followed by a set of extensive numerical tests that demonstrates the efficiency of proposed error control method. The numerical results obtained in this paper rely on the implementation carried out using open source software, which allows formulating the problem in a weak setting. To work in a variational framework appears to be very natural for functional error estimates due to their derivation method. The search for the optimal parameters for the majorant is done by a global functional minimisation, which to the authors’ knowledge is the first work using this technique in an evolutionary framework. [ABSTRACT FROM AUTHOR]

A symplectic semitoric manifold is a symplectic 4-manifold endowed with a Hamiltonian ( S 1 × R ) -action satisfying certain conditions. The goal of this paper is to construct a new symplectic invariant of symplectic semitoric manifolds, the helix, and give applications. The helix is a symplectic analogue of the fan of a nonsingular complete toric variety in algebraic geometry, that takes into account the effects of the monodromy near focus–focus singularities. We give two applications of the helix: first, we use it to give a classification of the minimal models of symplectic semitoric manifolds, where “minimal” is in the sense of not admitting any blowdowns. The second application is an extension to the compact case of a well known result of Vũ Ngọc about the constraints posed on a symplectic semitoric manifold by the existence of focus–focus singularities. The helix permits to translate a symplectic geometric problem into an algebraic problem, and the paper describes a method to solve this type of algebraic problem. [ABSTRACT FROM AUTHOR]

In control theory and practical engineering fields, such as the controllability, observability, input–output finite-time stability of the linear systems, it is a significant problem to study the properties of the solution for the Lyapunov matrix differential equation where there are no restrictions on the system matrix. In this paper, by constructing an equivalent form of the Lyapunov matrix differential equation and utilizing some important matrix eigenvalue inequalities, lower and upper bounds for the matrix solution of the Lyapunov matrix differential equation that remove the strict restrictions for the system matrix are proposed. As an application in linear systems, we show that our bounds can be used to discuss the input–output finite-time stability for linear systems. Finally, we give some corresponding numerical examples to illustrate the effectiveness and superiority of our results. [ABSTRACT FROM AUTHOR]

Abstract: Optimization of the steady state economic efficiency of an industrial process is a specific task because the decision variables of the optimization (setpoints of the control system) affect the process through the control strategy. Thus, the effects of saturation of a control system must be taken into account when the gradient of the objective function is estimated and the necessary optimality conditions are checked. In particular, because the optimality conditions cannot be checked directly in the presence of active constraints on the manipulated variables, approximations of the steady state values of the manipulated variables as functions of the setpoints (static plant model) are needed in order to be able to evaluate the optimality conditions. In this paper an iterative method for optimization of the plant profit rate is proposed avoiding the control saturation and is applied to the Pulp Mill benchmark model optimization. Three different static models describing the steady state values of the manipulated variables are constructed and used in the optimization. The results of the optimization are presented and compared against the straightforward single-step optimization of the plant economic efficiency. [ABSTRACT FROM AUTHOR]

This paper studies the control of flexible chaser spacecraft to track and rendezvous with a rotating non-cooperative target accompanied by translational maneuver. The problem is formulated that the chaser spacecraft is required to track target position and be synchronized with its attitude precisely. Meanwhile, the elastic vibration, induced by large angular maneuver in the tracking process, needs to be reduced. With respect to this unique movement of target, a novel modified θ − D control method, derived by standard θ − D algorithm and Lyapunov min-max value theorem , is proposed to incorporate position, attitude and flexural motion into one united control frame. The modification term in the proposed control method is dealt with target translational maneuver, which is the primary contribution in this paper. The asymptotically stability of closed-loop system is proved via the Lyapunov theory and Lyapunov min-max value theorem . Numerical results demonstrate an excellent tracking performance of proposed united control frame even under large inertia uncertainties. [ABSTRACT FROM AUTHOR]

In this paper, a novel nonlinear control strategy along with its simulation for a quadrotor helicopter is proposed. The normal 6-DOF dynamic model of the quadrotor based on the Newton–Euler formula as well as the model with external uncertain disturbances are established. Considering the underactuated and strongly coupled characteristics of quadrotor helicopter, we design a nonlinear control method by using integral backstepping combined with the sliding mode control (integral BS-SMC) to stabilize the quadrotor attitude and to accomplish the task of trajectory tracking. The designed controllers based on the hierarchical control scheme can be divided into rotational controller and translational controller and their stability are validated by the Lyapunov stability theorem. By means of the proposed controllers, the chattering phenomenon and discontinuousness of control inputs faced by traditional sliding mode control (SMC) can be avoided. The feasibility of the control approach presented in this paper is verified by the simulations under different scenarios. The results show that the nonlinear control method not only has a better tracking performance than others but also has a higher robustness when unknown disturbances occur. [ABSTRACT FROM AUTHOR]

A new multi-sided surfacing scheme – the Generalized Bézier (GB) patch – has been introduced recently by Várady et al. (2016) . The patch is created over a polygonal domain, its parameterization is defined by means of generalized barycentric coordinates. It has a simple control structure; the control points are associated with a combination of bi-parametric Bernstein functions, multiplied by rational terms. GB patches are compatible with adjacent quadrilateral Bézier patches and inherit most of their properties. In this paper we present an enhanced version of the former scheme. The control structure has been slightly modified, yielding a perfect generalization of quadrilateral patches. The parameterization has also been altered, matching a concept of how quadrilateral domains transform to n -sided polygons. We propose improved blending functions and investigate how the weight deficiency of the basis functions can be distributed amongst control points. The former rational weighting functions have been modified to support not only G 1 , but higher degree continuity between adjacent patches. After briefly discussing how degree reduction and elevation proceed, we present algorithms to automatically create and optimize the internal control points of GB patches. A few simple examples and suggestions for future work conclude the paper. [ABSTRACT FROM AUTHOR]

Nowadays, the microcomputer performs calculations at an incredibly high rate of billions of instructions per second. That represents an exponential increase in the processing speed since the early days of the computer development, eventhough such growth did not show complex reasoning that even the simple biological organisms can make. The artificial intelligence techniques as an attempt to work about those limitations, are a promising alternative. Each intelligent technique has its particular strengths and weaknesses and cannot be universally implemented to any problem. Mixed together, these techniques can improve the solutions quality and allow application to various tasks. It is the reason why the AI is used increasingly in order to solve complex problems in engineering. Where, it is still necessary to make progress in the controller tuning. The idea proposed in this paper is simple and original. It is the result of a study that compared the performances of two controls based on the artificial intelligence techniques: the artificial neural networks and the fuzzy logic. The control proposed in this paper combines in a different manner these two techniques in the form of a hybrid control. The aim is to benefit from performances of each of these techniques, by using them in the same control block at the most suitable place. The performances of the this proposed hybrid control; applied to the three-phase induction motor supplied by voltage source inverter; are investigated and compared to those obtained from the controls based on artificial neural networks; fuzzy logic and conventional techniques. The results of simulation show the feasibility and the good performances achieved by the proposed control. [ABSTRACT FROM AUTHOR]

This paper presents a signal processing algorithm to remove different types of noise from a gyroscopic head-borne computer mouse. The proposed algorithm is a combination of a Kalman filter (KF), a Weighted-frequency Fourier Linear Combiner (WFLC) and a threshold with delay method (TWD). The gyroscopic head-borne mouse was developed to assist persons with movement disorders. However, since MEMS-gyroscopes are usually sensitive to environmental disturbances such as shock, vibration and temperature change, a large portion of noise is added at the same time as the head movement is sensed by the MEMS-gyroscope. The combined method is applied to the specially adapted mouse, to filter out different types of noise together with the offset and drift, with marginal need of the calculation capacity. The method is examined with both static state tests and movement operation tests. Angular position is used to evaluate the errors. The results demonstrate that the combined method improved the head motion signal substantially, with 100.0% error reduction during the static state, 98.2% position error correction in the case of movements without drift and 99.9% with drift. The proposed combination in this paper improved the static stability and position accuracy of the gyroscopic head-borne mouse system by reducing noise, offset and drift, and also has the potential to be used in other gyroscopic sensor systems to improve the accuracy of signals. [ABSTRACT FROM AUTHOR]

This paper is concerned with the H ∞ control problem for a class of singular systems. The systems under consideration involve state time-varying delay. The aim of this paper is to design a dynamic feedback controller such that the resultant closed-loop system is regular, impulse-free and stable with given H ∞ performance index. By using the Lyapunov–Krasovskii functional method, some delay-dependent sufficient criteria which guarantee the existence of the dynamic feedback controller and determine explicitly the parameters of the dynamic feedback controller are presented. Finally, some numerical examples are provided to show the effectiveness of the presented approaches. [ABSTRACT FROM AUTHOR]

To more accurately describe the evolution process of traffic flow, a novel method was proposed on the basis of the polynomial trend model and the Kalman filtering theory in the paper. The state variables were defined as the deviations of the actual OD flow from the historical values. These deviations were presented as a stochastic evolution process with a sliding trend. Furthermore, the dynamic OD matrix was estimated and predicated by establishing a polynomial trend filtering model. A large number of simulation results prove that the performance of the algorithm proposed in this paper is better than the traditional method, and this algorithm can acquire more accurate estimation and prediction information for OD matrix. [ABSTRACT FROM AUTHOR]

This paper gives new results on iterative learning control (ILC) design and experimental verification using the stability theory of linear repetitive processes. Using this theory a control law can be designed in one step to force error convergence and produce acceptable transient dynamics. Previous research developed algorithms for the design of a static control law with supporting experimental verification. Should a static law not give the required levels of performance one option is to allow the control law to have internal dynamics. This paper develops a procedure for the design of such a control law with supporting experimental verification on a gantry robot, including a comparative performance against a static law applied to the same robot. The resulting ILC design is an efficient combination of linear matrix inequalities and optimization algorithms. [ABSTRACT FROM AUTHOR]

Business environment is dynamic and volatile. Changes are due to strategic factors like growth, regulations, mergers & acquisitions, diversification, geo-politics and business innovations etc. Sometimes change or innovation could be technology led also. For any business change or innovation to be deployed in practice, it must be developed (built) and operationalized and run as business as usual (BAU). This paper presents a systemic design based on Systems engineering and cybernetics principles. A systemic approach was adopted to re-inforce and establish connect between development and operations functions in delivering an organizational program of customer contact transformation. This paper also leverages experience of deploying the same to overcome the challenges of lack of collaboration between Development and Operations silos in delivering changes in programs. This systemic model described here was implemented successfully for enhancing synergy of Development and Operations functions of a customer contact program of a major telecommunications services provider in the EMEA (Europe, Middle East and Africa) region operating in more than ten markets. Key stakeholders from DevOps were involved during the surveys conducted and assessment done. The approach involved discovery, diagnosis and design iterations in onsite and offshore model. It also presents a case, which deployed this approach, provides conclusion and future direction. Results of application of above approach to address the problem are also illustrated. The approach helped in reinforcing collaboration between the DevOps resulting in enhanced synergy, productivity and reduced time to market of telecom products and services considerably. [ABSTRACT FROM AUTHOR]

This paper addresses design of model predictive control (MPC) for dynamic systems in the presence of disturbances. For the systems with disturbances, it is common to use observers to estimate states and disturbances, allowing control algorithm to reject disturbances. In this paper, we demonstrate how one can extend model predictive control for systems with disturbances by applying full state and disturbance observer. To this aim, a two-stage approach is proposed where the observer design procedure is completely decoupled from the MPC problem, known as the separation principle. We focus on the decoupling principal and it is shown that the observer can be designed independently via a norm minimization problem to reduce effects of disturbances and model mismatch. On the other hand, the MPC law is obtained using the multi-parametric quadratic programming approach where the parameters are the components of the state vector. [ABSTRACT FROM AUTHOR]

Feedback control of constrained non-linear dynamical systems satisfying a certain optimality criterion and meeting a specified transfer objective in the state space is recognized as one of the most challenging problems in control theory. One approach to computing optimal feedback policies is the dynamic programming route of numerically solving the Hamilton–Jacobi–Bellman (HJB) partial differential equation directly. In this paper an alternate and more tractable dynamic programming approach, the optimal feedback synthesis method, is utilized. The effectiveness of this method is demonstrated through an explicit guidance scheme for the heating-rate-constrained maneuver of an Aeroassisted Transfer Vehicle (AOTV). In optimal feedback synthesis, a feedback chart is constructed from a family of open-loop extremals, thus ensuring optimality with respect to any initial condition in the family. This paper presents a solution to the AOTV optimal feedback synthesis problem using the Gaussian process spatial prediction method of universal kriging. A closed-form expression for a near-optimal guidance law is derived. Its performance is found to be very promising; initial atmospheric entry errors due to simulated thruster misfiring are seen to be accurately corrected while the algebraic state-inequality constraint is closely respected. [ABSTRACT FROM AUTHOR]

This paper presents an adaptive supervisory controller, based on Pontryagin’s Minimum Principle (PMP), for on-line energy management optimization of a plug-in hybrid electric vehicle. Using minimum driving information, such as the total trip length and the average cycle speed, the proposed algorithm relies on adaptation of the control parameter from state of charge feedback. The proposed strategy is referred in the paper to as Adaptive-PMP (A-PMP). The new controller is applied to a detailed forward vehicle simulator of the plug-in hybrid Chevrolet Volt manufactured by General Motors, where an experimentally validated LG Chem battery model is used. The strategy we propose aims at achieving a blended trajectory of the state of charge to minimize the consumed fuel, resulting in an overall better performance than the actual Charge Depleting/Charge Sustaining (CD/CS) strategy currently used on-board of the vehicle. A comparative analysis of three strategies, i.e. , the optimal one (PMP), the proposed one (A-PMP) and the in-vehicle one (CD/CS), is conducted in simulation which shows that improvement above 20% in fuel consumption may be achieved when the proposed algorithm is used instead of the current on-board strategy. [ABSTRACT FROM AUTHOR]

This paper deals with Hamilton–Jacobi–Bellman (HJB) equation based stabilized optimal control of hybrid dynamical systems (HDS). This paper presents the fuzzy clustering based event wise multiple linearized modeling approaches for HDS to describe the continuous dynamic in each event. In the present work a fuzzy clustering validation approach is presented for the selection of number of linearized models which span entire HDS. The method also describes how to obtain event wise operating point using fuzzy membership function, which is used to find the event wise model bank by linearizing the first principles model. The event wise linearized models are used for the formulation of the optimal control law. The HJB equation is formulated using a suitable quadratic term in the objective function. By use of the direct method of Lyapunov stability, the control law is shown to be optimal with respect to objective functional and stabilized the event wise linearized models. The global Lyapunov function is proposed with discrete variables which stabilized the HDS. The proposed modeling and control algorithm have been applied on two HDSs. Necessary theoretical and simulation experiments are presented to demonstrate the performance and validation of the proposed algorithm. [ABSTRACT FROM AUTHOR]

In this paper, a new tuning method of variable-order fractional fuzzy PID controller (VOFFLC) is proposed for a class of fractional-order and integer-order control plants. Fuzzy logic control (FLC) could easily deal with parameter variations of control system, but the fractional-order parameters are unable to change through this way and it has confined the effectiveness of FLC. Therefore, an attempt is made in this paper to allow all the five parameters of fractional-order PID controller vary along with the transformation of system structure as the outputs of FLC, and the influence of fractional orders λ and μ on control systems has been investigated to make the fuzzy rules for VOFFLC. Four simulation results of different plants are shown to verify the availability of the proposed control strategy. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of suboptimal control for repointing maneuver of a staring-mode spacecraft where the optical axis is required to point to the target orientation. Different from the traditional reorientation maneuver, the angle of the spacecraft around the optical axis does not need to be controlled. First, a simple yet efficient representation for repointing error is introduced and kinematical descriptions are established correspondingly. Then, two different control algorithms are proposed for repointing control of a staring-mode spacecraft. The first one is the inverse optimal PD-like controller that drives the spacecraft to complete repointing maneuver and the optimality properties of the proposed control law are investigated by using dynamic programming theory. The other one is a control Lyapunov function (CLF) based suboptimal control scheme incorporated with the idea of equivalent control in sliding mode control theory. The switch mechanism between CLF control and sliding mode control is established where only one control switch is needed when the state reach the sliding surface. Compared with the classical CLF method, the sliding mode based CLF approach not only guarantees the optimality, but also enhances the system robustness against model uncertainties and disturbances. Finally, numerical investigations are conducted to demonstrate the utility and optimality of the proposed control algorithm. • The rotation of the spacecraft around the optical axis doesn't need to be controlled for repointing maneuver. • A new simple yet efficient attitude description for repointing maneuver is presented. • The PD like control law is optimal with respect to a meaningful performance index. • The sliding mode based CLF control approach improves the robustness and transient performance of the system. [ABSTRACT FROM AUTHOR]

Here the problem of designing two degrees of freedom controllers for an unknown plant based on input–output measurements is discussed. Virtual reference feedback tuning aims at minimizing a cost function of the L2-norm type by using a set of data, as no identification process is needed. When constructing this cost function, two model-matching problems are considered between closed loop transfer function and sensitivity function simultaneously. In model-matching procedures, we design virtual input and virtual disturb respectively. Further two filters used to reprocess the input–output measurements are derived to prove the equivalence between virtual reference feedback tuning and model reference control. After constructing one identification cost without any knowledge of the plant, we derive one bound on the difference between the expected identification cost and its sample identification cost under the condition that the number of data points is finite. Further the correlation property between the input and external noise is considered in deriving this bound. Then we continue to derive one probabilistic bound to quantify this difference through using some probability inequalities and knowledge of control theory. The number of data points is obtained by using generalization of independent block sequence. Finally two simulation examples have been performed to demonstrate the effectiveness of the theories proposed in this paper. • Virtual reference feedback tuning control is proposed to design two parameterized controllers. • Virtual input and virtual disturbance are constructed to obtain an optimization problem. • One probability bound is derived to quantify the model quality with finite datapoints. [ABSTRACT FROM AUTHOR]

Youla-Kucera (YK) parametrization was formulated decades ago for obtaining the set of controllers stabilizing a linear plant. This fundamental result of control theory has been used to develop theoretical tools solving many control problems ranging from stable controller switching, closed-loop identification, robust control, disturbance rejection, adaptive control to fault tolerant control. This paper collects the recent work and classifies them according to the use of YK parametrization, Dual YK parametrization or both, providing the latest advances with main applications in different control fields. A final discussion gives some insights on the future trends in the field. [ABSTRACT FROM AUTHOR]

• Demand-driven supply network model with transportation delay is proposed. • State-feedback stabilizing control strategies are designed. • Sufficient conditions that guarantee the stability of the supply network in the form of matrix inequalities are obtained. • The prescribed H∞ disturbance attenuation level under uncertain demand is studied. In this paper, we consider the stabilization strategies for a demand-driven supply network model with transportation delay. Based on Lyapunov stability theory and the robust control approach, we obtain sufficient conditions that guarantee the global asymptotic stability of the supply network in the form of matrix inequalities. Furthermore, state-feedback stabilizing control strategies are designed. We also carry out analysis on the prescribed H ∞ disturbance attenuation level under uncertain demand. Numerical simulation results are presented to verify the effectiveness of the control strategy that is designed. [ABSTRACT FROM AUTHOR]

The explicit consideration of a communication channel model in a feedback control loop is known to be constrained by a fundamental limitation for stabilizability on the channel signal-to-noise ratio (SNR) when the linear time invariant (LTI) plant model is unstable. The LTI modelling approach for real, usually nonlinear, processes compromises accuracy versus complexity of the resulting model. This in turn introduces a gap between the proposed model and the real process, which is known as the model uncertainty. In this paper we then study SNR limitations by considering the continuous-time scenario and the case of an additive coloured Gaussian noise (ACGN) channel with bandwidth limitation, for which we then quantify the infimal SNR subject to the simultaneous presence of plant, channel and noise model uncertainties. We observe, for the special case of memoryless additive white Gaussian noise (AWGN) channels, that the obtained SNR limitation subject to plant model uncertainty can be redefined as a channel capacity limitation for stabilization. • Signal transmission through communication channels is increasingly relevant in Control Theory. • Many relevant communication features can be considered: power, channel bandwidth, time delay, etc. • Control Theory require analysis tools for studying model uncertainty and communication features simultaneously. • The SNR approach can provide such analysis tool, and in turn better inform the controller design. [ABSTRACT FROM AUTHOR]

• Community detection is used to synthesize distributed architecture with strong input–output impact. • Equivalence between maximization of strength of input–output impact and modularity maximization in weighted equation graph is established. • Extension of vector portioning-based community detection algorithm for weighted and directed graph is presented. • Relationship between strength of variable interactions and rational distributed architecture is illustrated. Distributed control offers practical trade-off between globally (plant-wide) valid, computationally expensive centralized and locally effective decentralized architectures. While the development of distributed control theory (algorithms, stability, convergence properties, etc.) has made a significant progress in the last decade, decomposition of a system into an optimal distributed structure (classification of controller variables) has received considerably less attention. This paper focuses on achieving such a decomposition for integrated process systems with the objective of maximizing the strength of input–output impact and thus reducing the strength of inter-controller interactions. A graph-theoretic framework is used to abstract input-state-output dependence of a dynamical system and control-relevant interactions are quantified using weighted digraphs. It is shown that community detection in this weighted digraph is equivalent to distributed structure corresponding to strong input–output impact (quantified through the corresponding gain). Two relevant example systems are considered to illustrate the proposed framework and it is shown that the optimal distributed architectures adhere to the underlying structure of strong and weak inter-variable interactions. [ABSTRACT FROM AUTHOR]

Abstract: Wireless Sensor Networks (WSNs) have been utilized by many critical applications such as military and health care monitoring. Such applications require special Quality of Service (QoS) treatment. However, the components of sensor nodes suffer from different limitations including the scarce energy source, limited processing capabilities, and limited storage space. At the same time, nodes are supposed to live for long time. This could occur when the energy is balanced on the active nodes in the network. This paper handles the problem of QoS in Wireless Sensor Networks (WSNs). The paper considers the limitation of the nodes in handling many messages at the same time especially the sink node. Therefore, nodes can coordinate with each other to minimize the number of dropped message. Defining some nodes to send to the sink node at certain time allows other nodes to go to sleep. Certainly, this QoS control enhances the operation of the network and positively affect the nodes’ consumed energy. This work applies one of the game theory schemes which is Gur game. The paper proposes two QoS control techniques with Quick Convergence called Periodic Gur Game (PGur) and Adaptive Periodic Gur Game (APGur). These two approaches are evaluated using different sets of experiments. [Copyright &y& Elsevier]

Abstract: This paper presents a new application software for control configuration selection of interconnected industrial processes, called ProMoVis. Moreover, ProMoVis is able to visualize process models and process layout at the physical level together with the control system dynamics. The software consists of a builder part where the visual representation of the interconnected process is created and an analyzer part where the process is analyzed using different control configuration selection tools. The conceptual idea of the software is presented and the subsequent design and implementation of ProMoVis are discussed. The implemented analysis methods are briefly described including their usage and implementation aspects. The use of ProMoVis is demonstrated by an application study on the stock preparation process at SCA Obbola AB, Sweden. The results of this study are compared with the currently used control strategy. The study indicates that ProMoVis introduces a systematic and comprehensive way to perform control configuration selection. ProMoVis has been released under the Apache Open Source license. [Copyright &y& Elsevier]

Abstract: This paper deals with the binary analysis of executable programs, with the goal of understanding how they access memory. It explains how to statically build a formal model of all memory accesses. Starting with a control flow graph of each procedure, well-known techniques are used to structure this graph into a hierarchy of loops in all cases. The paper shows that much more information can be extracted by performing a complete data-flow analysis over machine registers after the program has been put in static single assignment (SSA) form. By using the SSA form, registers used in addressing memory can be symbolically expressed in terms of other previously set registers. By including the loop structures in the analysis, loop indices and trip counts can also often be expressed symbolically. The whole process produces a formal model made of loops where memory accesses are linear expressions of loop counters and registers. The paper provides a quantitative evaluation of the results when applied to several dozens of SPEC benchmark programs. Because static analysis has no access to input data, the paper ends by describing a lightweight instrumentation strategy that collects at run time enough information to rebuild an exact trace. The section on applications also describes how the techniques developed in this paper can be used to perform automatic parallelization of binary code. [Copyright &y& Elsevier]

Abstract: Framing effects have been shown to have dramatic impact on human decision making in many domains, in certain circumstances even driving self-detrimental behavior. Multi-stakeholder tradespace exploration (MSTSE), an emerging technique for advanced multiparty decision making for engineering systems, has displayed many benefits with regards to insight-generation and identification of mutually beneficial solutions. However, for complex problems with no solutions that are individually optimal for each stakeholder, stakeholders may still resist “compromising” from their individual preferred solutions. This occasionally drives a failure to reach agreement, despite a design space with a considerable number of feasible designs with value for all parties. This paper hypothesizes that this result may be caused in part by an unintentional framing of the initial stages of MSTSE as an individual problem, establishing an unrealistically high reference point. Theoretically, this locks stakeholders into a mindset that forces them to “compromise” down, rather than more appropriately building up mutual value from the “no agreement” alternative. This paper addresses the current literature of multi-stakeholder system design, the ramifications of framing on MSTSE, considerations for establishing a more appropriate reference point, and example techniques and visual representations for doing so. A preliminary set of experiments is described to confirm the hypothesized framing effect and to validate visual representations for mitigating its impact. [Copyright &y& Elsevier]

Abstract: This paper discusses the continuous effect of the fractional order parameter of the Lü system where the system response starts stable, passing by chaotic behavior then reaching periodic response as the fractional-order increases. In addition, this paper presents the concept of synchronization of different fractional order chaotic systems using active control technique. Four different synchronization cases are introduced based on the switching parameters. Also, the static and dynamic synchronizations can be obtained when the switching parameters are functions of time. The nonstandard finite difference method is used for the numerical solution of the fractional order master and slave systems. Many numeric simulations are presented to validate the concept for different fractional order parameters. [Copyright &y& Elsevier]

Abstract: This paper provides an overview of building structure modeling and control. It focuses on different types of control devices, control strategies, and sensors used in structural control systems. This paper also discusses system identification techniques and some important implementation issues, like the time-delay in the system, estimation of velocity and position from acceleration signals, and optimal placement of the sensors and control devices. Finally, the applications of structural control systems in real buildings and their performance have been reviewed. [Copyright &y& Elsevier]

Abstract: The paper presents the application of object-oriented modeling techniques to control software development for complex manufacturing systems, with particular focus on case studies taken from the packaging industry and design patterns that can be abstracted from such case studies. The proposed methodology for control software modeling and implementation is based on a practical approach refined on the basis of on-the-field experience and interactions with control engineers involved in the development projects. The final objective of the paper is to review and analyze patterns for the solution of design and implementation issues that typically arise in the considered application domain. [Copyright &y& Elsevier]

Abstract: This paper addresses the temperature control problem in a solar furnace. In particular, two control strategies for the disturbances rejection (represented by the variation of the input energy provided by the Sun, mainly because of passing clouds and the solar daily cycle) are proposed, based on a two-degrees-of-freedom scheme. The first one is based on generalized predictive control, where a nonlinear model is employed for free response prediction while a linearized model is used for the computation of the forced response. Amplitude and slew-rate constraints on both the control variable and the output of the system are taken into account. The second one is a constrained control strategy where both the process input and output constraints are taken into account explicitly. In both cases an adaptation of the most significant process parameter is performed. Simulation and experimental results show the effectiveness of the methodologies. 1 [1] This paper is the extended version of the one presented at the 18th IFAC World Congress (Milano, Italy, 2011), but including more details and real tests. [Copyright &y& Elsevier]

Abstract: Movement of piston inside a cylinder has many applications in industries and measurement of its displacement inside the cylinder is very much important to study its operation and control. In the present paper a non contact type displacement measurement technique of a piston made of magnetic material inside a cylinder has been proposed. In this technique, the difference of inductances of two identical coils wound outside a cylinder due to movement of piston inside it has been found to be linearly related with the displacement. A modified differential inductance measurement circuit has been designed to develop the proposed displacement transducer. The design of the circuit along with principle of operation has been described in the paper. The operation of the proposed circuit has been experimentally studied and the experimental results are reported in the paper. The proposed transducer has been found to have very good linearity and repeatability. [Copyright &y& Elsevier]

Abstract: The traditional integer order proportional-integral-differential (IO-PID) controller is sensitive to the parameter variation or/and external load disturbance of permanent magnet synchronous motor (PMSM). And the fractional order proportional-integral-differential (FO-PID) control scheme based on robustness tuning method is proposed to enhance the robustness. But the robustness focuses on the open-loop gain variation of controlled plant. In this paper, an enhanced robust fractional order proportional-plus-integral (ERFOPI) controller based on neural network is proposed. The control law of the ERFOPI controller is acted on a fractional order implement function (FOIF) of tracking error but not tracking error directly, which, according to theory analysis, can enhance the robust performance of system. Tuning rules and approaches, based on phase margin, crossover frequency specification and robustness rejecting gain variation, are introduced to obtain the parameters of ERFOPI controller. And the neural network algorithm is used to adjust the parameter of FOIF. Simulation and experimental results show that the method proposed in this paper not only achieve favorable tracking performance, but also is robust with regard to external load disturbance and parameter variation. [Copyright &y& Elsevier]

Abstract: Application of technology systems is seen in many sectors including agriculture and food. Traditionally, agricultural industry has been solely dependent on human labor with limited application of mechanical equipment and machines. The applications of advanced technology such as embedded computing, robotics, wireless technology, GPS/GIS (Geographical Positioning System/Geographical Information System) and DBMS (Database Management System) software are seen to be recent developments. This paper reviews the applications of technology systems in agriculture and food. Because knowledge on standardization and interfacing plays a key role in using the technology systems in any application domain, this paper aims to highlight the important attributes of such an emerging research area. In particular, the paper describes soil sampling methods and technology applications; field and yield mapping with GPS and GIS; harvesters and future research in robotic-based harvesters; food processing and packaging technology such as traceability and status of RFID networking research; application of sensor network; data management and execution systems; and the automation and control standards such as fieldbus systems and OMAC guidelines. [Copyright &y& Elsevier]

Abstract: In this paper, we provide a tutorial review of recent results in the design of distributed model predictive control systems. Our goal is to not only conceptually review the results in this area but also to provide enough algorithmic details so that the advantages and disadvantages of the various approaches can become quite clear. In this sense, our hope is that this paper would complement a series of recent review papers and catalyze future research in this rapidly evolving area. We conclude discussing our viewpoint on future research directions in this area. [Copyright &y& Elsevier]

Abstract: This paper explores the evolving industrial control paradigm of product intelligence. The approach seeks to give a customer greater control over the processing of an order – by integrating technologies which allow for greater tracking of the order and methodologies which allow the customer [via the order] to dynamically influence the way the order is produced, stored or transported. The paper examines developments from four distinct perspectives: conceptual developments, theoretical issues, practical deployment and business opportunities. In each area, existing work is reviewed and open challenges for research are identified. The paper concludes by identifying four key obstacles to be overcome in order to successfully deploy product intelligence in an industrial application. [Copyright &y& Elsevier]

Abstract: This paper presents an evaluation of various control methods to be used during drilling operations where an unexpected gas influx occurs. In the event of an unexpected gas influx the current industry procedure is to control the pressure in the well manually. The drilling industry term for this manual procedure is well control. The focus of the paper is threefold. Firstly, to design an automatic sequence which is similar to the existing manual procedure. Secondly, to evaluate three different control algorithms for pressure control during an unexpected gas influx, and thirdly, to evaluate control parameter tuning needed when implementing different control algorithms. The control methods have been evaluated on various drilling scenarios with unexpected gas influx, referred to as a kick. After a kick of reservoir gas has entered the well, automatic control of the well control choke and rig pump is applied to compensate for pressure fluctuations while circulating out the gas. A PI controller is designed to stabilize the well pressure by controlling the well control choke, an internal model controller (IMC) controls the pressure by manipulating the choke and the rig pump flowrate, and a model predictive controller (MPC) uses coordinated control of the choke and the pump flowrate to stabilize the well pressure. The model based controllers use a simple first order model of the well. Simulations are performed using a detailed flow model of the well to test the controller performance and robustness. Several cases with different amounts of gas influx are investigated. The simulations show that it is feasible to control the pressure using automatic control of the choke valve and pump during an unexpected gas influx by use of all the presented control methods. The control methods are robust against changes in process conditions and disturbances, as they are able to handle several pressure levels and gas volumes without requiring re-tuning. However, since the pressure dynamics in the well are influenced when gas is entering the well, the model based controllers could probably be further improved if the models were updated after the gas influx occurred. The results indicate that adaption of the automatic sequence to the current manual procedure is applicable. However, to avoid a reduction in downhole pressure when stopping the pump and shutting in the well, the automatic sequence may be further improved beyond what is feasible with manual operation. [Copyright &y& Elsevier]

Abstract: Coal mills play an important role in the overall dynamic response of coal fired power plants and there is significant potential to improve the load ramp rates of coal fired power plants through improvements of coal mill control strategies. This potential can be employed to compensate for the power fluctuations generated by renewable but intermittent energy sources such as wind and solar in a more efficient way. In this paper a three state coal mill model based on heat and mass balances as well as a single step coarse to fine particle grinding relationship is presented with the purpose of predicting the dynamic behavior of coal mills during both start-up and in normal operation. The parameters of the model were identified and later validated with measurements obtained from a hard coal fired power plant. During these studies several parameters were found to be time varying. In order to estimate the values of these time varying parameters and the internal states of the coal mill an extended Kalman filter was designed. The proposed solution is observed to achieve very good agreement with measurements and can be used for various applications such as model-based control, performance monitoring, fault detection, and maintenance scheduling. In order to demonstrate one of these use cases a nonlinear model predictive control (NMPC) application was developed based on the coal mill model and the performance of the NMPC was compared to a conventional coal mill control strategy for tracking load change references and for rejecting disturbances caused by variations in coal moisture. The results demonstrate that the coal mill control system performance can be significantly improved through the use of the model presented in this paper. [Copyright &y& Elsevier]