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The problem of infinite horizon H∞ control for general delayed nonlinear stochastic Markov jump systems with the infinite jumping parameters is considered in this paper, in which the noise is dependent on the state, control, and external disturbance. The coupled Hamilton–Jacobi inequalities (HJIs)-based sufficient condition is given to ensure the existence of the H∞ controller. As a corollary, infinite horizon H∞ controllers are designed for nonlinear stochastic time-delay systems without jumps by solving a series of coupled HJIs. Besides, the effectiveness of the proposed method is verified by a numerical example. [ABSTRACT FROM AUTHOR]

The rollover phenomenon is quite familiar with trucks and often has severe consequences worldwide. This article focuses on developing a new control structure for the active antiroll bar system using the robust control method. The main objective is to improve the vehicle's roll stability by using additional suspension roll angle sensors. First, a truck model equipped with an active antiroll bar system is introduced. Then, the basic robust controller structure diagram is described in detail. Based on this basic robust controller, the authors develop a new robust controller considering the suspension roll angle sensors. Finally, the response of a truck using an active antiroll bar system with two robust (H∞) controllers and a passive antiroll bar system is compared and evaluated in the time domain and in the frequency domain. The results showed that the use of two sensors of the suspension roll angle sensors increased the efficiency by about 20% compared to the basic robust controller. This has proven the effectiveness of a new approach in improving the roll stability of trucks. [ABSTRACT FROM AUTHOR]

This article introduces long short-term memory (LSTM)-enabled direct torque control (DTC) for induction motor under a wide range of operation. Low-power applications of industrial drives are more as compared to high-power applications. The main objective of this paper is to address high torque, poor dynamic response, and flux ripple problems observed in low-power induction motor drives. The voltage selector switching table is replaced by LSTM encoder and embedding layer with hysteresis comparator. This will ensure robust control against induction motor disturbances and at the same time will enhance the stator flux trajectory prediction for DTC. Most of the studies describe DTC at a higher speed. In this article, the DTC has been applied to lower speed IM, typically in the range of 100 RPM. Different LSTM models have also been presented in terms of response time. A detailed comparative analysis between LSTM and fuzzy and ANFIS-based DTC has been carried out using MATLAB/Simulink model. The performance has been evaluated under steady and transient conditions as well. [ABSTRACT FROM AUTHOR]

Fractional-order calculus has exclusive advantages in modeling the viscoelastic components with obvious fractional-order characteristics such as air springs and metal rubbers in the pantograph structure. In this paper, the air spring is tested, and fractional-order calculus is applied to the modeling of pantograph-catenary system of the high-speed train. The parameter identification method of fractional-order derivative is analytically derived. The traditional lumped mass model is improved and a coupling two-degree-of-freedom model of the fractional-order pantograph-catenary system is established. The fractional-order derivative term in the pantograph-catenary model is approximately calculated by the Oustaloup filter algorithm. Taking the time-varying nature into consideration, the catenary is treated as an extended variable to obtain an augmented model. On this basis, the system is linearized based on differential geometry theory, and an LQR controller is designed to control the pantograph-catenary system. The feedback linearized LQR control and PID control are used to control the same type of traditional pantograph, and the results are compared. Meanwhile, the control effects of feedback linearized LQR control under different pantograph parameters and at different train speeds are analyzed. The results show that the feedback linearized LQR control can present a much better control performance than PID control, and the pantograph-catenary contact force and pantograph head vibration amplitude are both reduced obviously. Even at different train speeds or under different pantograph parameters, it can also effectively reduce these control indexes and provide more robust control performance. These results help to put forward new control ideas and theoretical basis for the vibration control of the pantograph-catenary or similar dynamical system. [ABSTRACT FROM AUTHOR]

For a class of uncertain continuously networked Lurie control systems with both sensor-to-controller time-delay and controller-to-actuator time-delay, the problem of codesigning its observer and fault-tolerant controller based on an event-triggered mechanism under actuator failure is investigated. Firstly, considering that the state of the system cannot be measured directly, an observer is constructed on the controller node. Secondly, to reduce the waste of network bandwidth resources and improve the performance of the network control system, a network control system approach based on event-triggered mechanism is proposed. By introducing the event-triggered mechanism and the actuator fault indication matrix, the Lurie networked control system is modeled as a Lurie system with time-delay using the state augmentation technique to obtain a model of the closed-loop system. Finally, based on Lyapunov stability theory, sufficient condition for the stability of the closed-loop system is obtained, and the design method of the fault-tolerant controller and the observer is given. The obtained results are given in the form of linear matrix inequalities, which are easy to be solved by using the linear matrix inequality toolbox. Finally, the feasibility and effectiveness of the method are illustrated by a simulation example. [ABSTRACT FROM AUTHOR]

This study is devoted to investigating the robust adaptive finite-time attitude tracking control problem for a rigid body subject to unknown uncertainties. Considering about the nonlinear attitude dynamics for a rigid body, a homogeneous sliding variable is designed by employing the signum-function technique. For the presented homogeneous sliding variable, a real sliding manifold, on which the singularity problem is avoided, could be achieved. Subsequently, a novel signum-function-based MIMO adaptive homogeneous finite-time control (SMAHFTC) algorithm is proposed. Finite-time convergence of the tracking errors to a region around the origin is rigorously proved through the Lyapunov approach. The control gains will not be overestimated, which implies that minimal control gains will be obtained by the adaptation law. Moreover, the controls' signals are continuous for the SMAHFTC law. Then, by means of the proposed design method, an attitude tracking controller is designed for a rigid body described by the modified Rodrigues parameters' (MRPs) representation. A comparison simulation is carried out to show the effectiveness and superiority of the proposed method. [ABSTRACT FROM AUTHOR]

The paper is focused to design a robust and a simple fixed structure H ∞ control synthesis for an Electrohydraulic Servo System (EHSS) and comparing its performance with the conventional H ∞ controller and the classical proportional integral derivative (PID) controller. The precise position tracking of the piston load of EHSS system using classical PID controller is a difficult task due to some non-linear properties of EHSS and the dynamic behaviour of its parameters. The conventional H ∞ controllers also have constraints on gain ( H ∞ norm) for typical design requirement such as the speed of response, higher order, complex structure, control bandwidth, and robust stability. To overcome the above limitations, the proposed synthesis is formulated in the MATLAB. The proposed synthesis has fixed order and fixed structure and is also a linear robust controller. The control parameters of proposed synthesis are tuned using Genetic Algorithm optimization in MATLAB. Another advantage of this design is to use higher order complex shaping fillers to shape the close loop sensitivity S s and complementary sensitivity T s for the desired robust performance, without effecting the structure fixed of proposed synthesis. The order of the proposed controller is not affected by using the higher order complex weights transfer functions W s s and W T s on sensitivity and complementary sensitivity, respectively, whereas the structure of the conventional H ∞ controller becomes more complex due to higher order shaping weights. Model of the Electrohydraulic Servo System is validated experimentally, and results of proposed robust synthesis are compared with conventional H ∞ controller and the classical PID. [ABSTRACT FROM AUTHOR]

This paper investigates a joint robust scheme in a secrecy relay network where distributed relays perform cooperative beamforming and a friendly jammer transmits jamming signal to enhance the information security. Specifically, we consider the outage constraint secrecy rate maximization design with imperfect channel state information. Through semidefinite relaxation and one-dimensional search, we propose a two-layer optimization method to solve the nonconvex problem. In addition, the Bernstein-type inequality and large deviation inequality are utilized to convert the probabilistic constraint. Simulation results demonstrate the performance of the proposed design. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of designing novel switching control for a class of stochastic nonlinear switched fuzzy systems with time delay. Firstly, a stochastic nonlinear switched fuzzy system can precisely describe continuous and discrete dynamics as well as their interactions in the complex real-world systems. Next, novel control algorithm and switching law design of the state-dependent form are developed such that the stability is guaranteed. Since convex combination techniques are used to derive the delay independent criteria, some subsystems are allowed to be unstable. Finally, various comparisons of the elaborated examples are conducted to demonstrate the effectiveness of the proposed control design approach. All results illustrate good control performances as desired. [ABSTRACT FROM AUTHOR]

The stability analysis and controller design problems for the fractional-order (FO) direct-drive permanent magnet synchronous generator (FOD-PMSG) wind turbine with parameter uncertainties and external disturbance are addressed. Takagi–Sugeno (T-S) model is used to approximate nonlinearities, and the parallel distributed compensation (PDC) technique is employed to construct the fuzzy state feedback controller. In order to suppress the external disturbance more effectively, the global Mittag-Leffler stability definition satisfying the H∞ performance index is proposed for the first time. Using the FO Lyapunov direct method, applying the Cauchy matrix inequality (CMI), and combining with the Schur complement lemma, the sufficient conditions of Mittag-Leffler stability meeting the H∞ performance index are given in the form of linear matrix inequalities (LMIs). Simulation results clearly show that the proposed control scheme can make the system get rid of the chaotic state quickly and have strong robustness under parameter uncertainties and external disturbance varying randomly. [ABSTRACT FROM AUTHOR]

The backlash by the hysteresis between the input and the output is always present in the inertial stabilized platform, which will seriously affect the dynamic performance of the platform system at low speed. So, the backlash has been paid more and more attention for the use in the inertial stabilized platform. To handle such a situation, extend disturbance observer (EDOB) has a high advantage to compensate the disturbance caused by backlash. However, some research studies show that the observation effect for some fast time-varying disturbances is satisfactory, which will strict limits on the rate of change in disturbance and still hamper its application; consequently, this paper proposes a sliding-mode-based extend disturbance observer (SMEDO) to compensate backlash. By well-designed sliding-mode surface, it is unnecessary to measure the whole state and the lack of robustness against unmatched uncertainties of the resulting controller, and the robustness and accuracy of modified disturbance observer can be enhanced. Experiments were carried out on a DSP-based platform with backlash in the pitch shafting. The obtained experimental results demonstrate that the SMEDO scheme has an improved performance with the dynamic performance and shafting transmission accuracy compared with the traditional methods. [ABSTRACT FROM AUTHOR]

In this paper, a PD + controller combined with the sliding mode surface is proposed to improve system convergence rate and efficiency on control torque for satellite attitude tracking control. A sliding mode surface with the maneuver stage is constructed by the Euler axis; hence, the constant angular velocity is achieved. The PD + controller with the variable structure and auxiliary term is constructed to track the desired sliding mode surface. The Lyapunov function in PD control analysis is modified to simplify stability analysis. Model uncertainty, external disturbance, control torque constraint, and angular velocity constraint are taken into consideration, and a novel method to reduce the overshoot of angular velocity is proposed. The performance and superiority of the proposed method are demonstrated by numerical simulation results. [ABSTRACT FROM AUTHOR]

In this paper, a robust vector control sensorless based on three Active Disturbance Rejection Controllers (ADRC) for an induction motor fed by a five-level cascaded H-bridge was developed. The estimation of rotor position is achieved using a Luenberger estimator. The proposed model considers the disturbances and the inaccuracies of the system and compensates them using the extended state observer of ADRC. Moreover, a five-level cascaded H-bridge inverter is the best topology to minimize the torque ripples and to improve the current output of IMunder control. The suggested control system was simulated under different conditions using MATLAB-Simulink. The results demonstrate the effectiveness and the robustness of the proposed system against disturbances such as variations of parameters and load torque. [ABSTRACT FROM AUTHOR]

In this paper, the problem of the delay-dependent robust H ∞ control for a class of uncertain neutral systems with mixed time-varying delays is studied. Firstly, a robust delay-dependent asymptotic stability criterion is shown by linear matrix inequalities (LMIs) after introducing a new Lyapunov–Krasovskii functional (LKF). The LKF including vital terms is expected to obtain results of less conservatism by employing the technique of various efficient convex optimization algorithms and free matrices. Then, based on the obtained criterion, analyses for uncertain systems and H ∞ controller design are presented. Moreover, on the analysis of the state-feedback controller, different from the traditional method which multiplies the matrix inequality left and right by some matrix and its transpose, respectively, we can obtain the state-feedback gain directly by calculating the LMIs through the toolbox of MATLAB in this paper. Finally, the feasibility and validity of the method are illustrated by examples. [ABSTRACT FROM AUTHOR]

Excessive use of fuel or being underutilized will make the actual performance of solid oxide fuel cells (SOFCs) affected by a lot, and at the same time, in order to meet the demands of DC load voltage, a controller of the SOFC that is subjected to small varying loads is proposed on the basis of H∞ control theory. For the controller design, a state-space representation of the SOFC by using small-signal linearization is derived. To evaluate the control performance, the presented H∞ controller is tested on the SOFC stack with various load disturbances. The results show that the obtained H∞ controller can mitigate the voltage oscillations and deviations and can keep fuel utilization constant at varying loads. [ABSTRACT FROM AUTHOR]

In this paper, chaotic synchronization with uncertainties and disturbances is studied. Firstly, a new control method based on UDE control is proposed, which is composed of two controllers: one is the stabilization controller in order to realize the stabilization of nominal system without uncertainties and disturbances and the other is the UDE controller in order to deal with the given controlled system with both uncertainties and disturbances. Then, two examples are studied by the above method. Finally, the correctness and effectiveness of the method are verified by numerical simulation. [ABSTRACT FROM AUTHOR]

In this paper, H ∞ control for the uncertain switched nonlinear cascade systems with passive and nonpassive subsystems is investigated. Based on the average dwell time method, for any given passivity rate, average dwell time, and disturbance attenuation level, the feedback controllers of the subsystems by predetermined constants are designed to solve the exponential stability and L 2 -gain problems of H ∞ control for switched nonlinear cascade systems. Two examples are provided to demonstrate the effectiveness of the proposed design method. [ABSTRACT FROM AUTHOR]

The present study tackles the tracking control problem for unstructured uncertain bilinear systems with multiple time-delayed states subject to control input constraints. First, a new method is introduced to design memory state feedback controllers with compensator gain based on the use of operational properties of block-pulse functions basis. The proposed technique permits transformation of the posed control problem into a constrained and robust optimization problem. The constrained robust least squares approach is then used for determination of the control gains. Second, new sufficient conditions are proposed for the practical stability analysis of the closed-loop system, where a domain of attraction is estimated. A real-world example, the headbox control of a paper machine, demonstrates the efficiency of the proposed method. [ABSTRACT FROM AUTHOR]

This paper presents a hybrid robust control design method for a third-order lower-triangular model of nonlinear dynamic systems in the presence of disturbance. In this paper, a novel control design is presented systematically to synthesize a robust nonlinear feedback controller, called backstepping sliding mode control (BSMC), for the proposed system by a combined approach of backstepping design and sliding mode control. In this approach, a family of the "sliding surface" is introduced in state transformations. Then, a smooth switching function of the sliding surface is introduced and enforced to include in virtual feedbacks and a real control law from the control selection phrases of the backstepping design loop. The achieved control method proves a well-tracking command with asymptotic stability, provides a robustness in the presence of uncertainties, and eliminates completely a chattering phenomenon. The application of flight-path angle control corresponding to the longitudinal dynamics of a high-performance F-16 aircraft simulation model is implemented. Under some assumptions, full nonlinear longitudinal dynamics is reformed into a lower-triangular system for a direct application to formulate a control law. A closed-loop system is achieved for in-flight simulation with different flight profiles for a comparison of the existing methods. Also, an external disturbance on different loading/unloading conditions in flight is applied to verify and validate robustness of the proposed control method. [ABSTRACT FROM AUTHOR]

The discrete coupled algebraic Riccati equation (DCARE) has wide applications in robust control, optimal control, and so on. In this paper, we present two iterative algorithms for solving the DCARE. The two iterative algorithms contain both the iterative solution in the last iterative step and the iterative solution in the current iterative step. And, for different initial value, the iterative sequences are increasing and bounded in one algorithm and decreasing and bounded in another. They are all monotonous and convergent. Numerical examples demonstrate the convergence effect of the presented algorithms. [ABSTRACT FROM AUTHOR]

This paper aims to contribute to the fault-tolerant control of the current sensor. The system studied is a double star induction machine (DSIM) controlled by a robust control called Active Disturbance Rejection Control (ADRC). The proposed method makes it possible to detect, isolate, and reconfigure the fault in real time. The reconfiguration is based on the comparison between the values measured by the current sensors and the estimated values. Two voltage observers will be used to estimate the estimated currents, and these two observers are placed at the level of the converters. This method of fault-tolerant control (FTC) has the advantage of ensuring, even in the presence of a sensor fault, the continuity of the system's operation and maintaining its performance at the desired level. The effectiveness of the FTC strategy proposed in this work is illustrated with simulations carried out under the MATLAB/Simulink environment. [ABSTRACT FROM AUTHOR]

Cognitive radar can overcome the shortcomings of traditional radars that are difficult to adapt to complex environments and adaptively adjust the transmitted waveform through closed-loop feedback. The optimization design of the transmitted waveform is a very important issue in the research of cognitive radar. Most of the previous studies on waveform design assume that the prior information of the target spectrum is completely known, but actually the target in the real scene is uncertain. In order to simulate this situation, this paper uses a robust waveform design scheme based on signal-to-interference-plus-noise ratio (SINR) and mutual information (MI). After setting up the signal model, the SINR and MI between target and echo are derived based on the information theory, and robust models for MI and SINR are established. Next, the MI and SINR are maximized by using the maximum marginal allocation (MMA) algorithm and the water-filling method which is improved by bisection algorithm. Simulation results show that, under the most unfavorable conditions, the robust transmitted waveform has better performance than other waveforms in the improvement degree of SINR and MI. By comparing the robust transmitted waveform based on SINR criterion and MI criterion, the influence on the variation trend of SINR and MI is explored, and the range of critical value of Ty is found. The longer the echo observation time is, the better the performance of the SINR-based transmitted waveform over the MI-based transmitted waveform is. For the mutual information between the target and the echo, the performance of the MMA algorithm is better than the improved water-filling algorithm. [ABSTRACT FROM AUTHOR]

An intelligent proportional-derivative sliding mode controller (i-PDSMC) is presented to overcome the unmodeled complexity of the robot manipulator under an actuator. i-PDSMC is a free model intelligent control based on the ultralocal, sliding mode, and PD control structure. A stability condition is determined by the Lyapunov theory. A comparative study between a classical PD, an intelligent PD control, and i-PDSMC is done through a robot manipulator under actuators. The simulation results prove that the proposed controller is more robust to trajectory tracking under parameter variations and external disturbances. [ABSTRACT FROM AUTHOR]

The proposed work presented in this paper is mainly focused on the control of the active and reactive stator powers generated by a wind energy conversion system (WECS) based on the dual feed induction generator (DFIG). This control is achieved by acting on the rotor side converter (RSC) to extract the maximum power from the wind turbine (WT) while regulating the rotor currents. Furthermore, another control objective is achieved by acting on the grid side converter (GSC), in which the DC bus voltage is maintained constant and a unity power factor is ensured. To do that, a new robust control known as active disturbance rejection control (ADRC) has been proposed and applied to the WECS. This control is based on the extended state observer (ESO), which is the main core of this algorithm; it makes the estimation and cancellation of the total effect of various uncertainties (internal and external disturbances) possible in real time. To validate the effectiveness of the proposed approach, the system was modeled and simulated by using the Matlab/Simulink software. Two tests, namely, tracking and robustness tests, were performed to compare the proposed ADRC technique and classical PI controllers. The obtained results are promising and have shown that the proposed control strategy based on ADRC, especially when varying the mode parameters, is performant and very useful. [ABSTRACT FROM AUTHOR]

In recent years, more and more scientists have been interested in research on driving two-wheel bicycles. The problems in two-wheel bicycle control problem are self-balancing, uncertain models, and the impact of noise. In the paper, to solve the self-balancing problem, we use the flywheel method according to the inverted pendulum principle. To overcome the effects of the uncertain model, the impact of noise, we designed the vehicle balance controller according to the robust control algorithm. However, robust controllers often have a high order, which affects the quality during real control. To simplify the robust controller, we propose the use of a model order reduction algorithm. The simulation and experimental results have proved the correctness of the solutions given in the paper. [ABSTRACT FROM AUTHOR]

As a key feature of networked control systems (NCSs), the time delays induced by communication medium sharing and data exchange over the system components could largely degrade the NCS performances or may even cause system instability, and thus, it is of critical importance to reduce time delays within NCSs. This paper studies the time-delay reduction problem in distributed NCSs and presents a dual-way data scheduling mechanism for time-delay reductions in delay-bounded NCSs with time-varying delays. We assess the time delays and their influences on the NCSs first with various delay factors being considered and then describe a one-way scheduling mechanism for network-delay reductions in NCSs. Based upon such a method, a dual-way scheduling algorithm is finally proposed for distributed NCSs with different types of transmitted data packets. Experiments are conducted on a remote teaching platform to verify the effectiveness of the proposed dual-way scheduling mechanism. Results demonstrate that, with the stability time-delay bound considered within the scheduling process, the proposed mechanism is effective for NCS time-delay reductions while addressing the stability, control accuracy, and settling time issues efficiently. Such a proposed mechanism could also be implemented together with some other existing control algorithms for time-delay reductions in NCSs. Our work could provide both useful theoretical guidance and application references for stable tracking control of delay-bounded NCSs. [ABSTRACT FROM AUTHOR]

Network repair is indispensable for maintaining network security. Conventional static repair is relatively inefficient. In this study, by considering the energy transfer between nodes, a dynamic repair model was established. The fundamental reason for the secondary failure of repaired nodes during the dynamic repair process is the coupling structure of failure networks. A dynamic repair strategy was proposed that can effectively prevent the secondary failure of repair nodes influenced by energy during repair and can cause the redundant capacity of repair nodes to be used reasonably. By turning off the energy transfer function of the link to control the excessive flow of energy into the repair node to avoid the occurrence of secondary failure; on the other hand, by sharing part of the load of the failure node, realize the rational use of the redundant capacity of the repair node to reduce the impact of the failure node on the overall function of the network. The proposed strategy mitigated the effect of failure nodes on network functions and substantially improved the recovery efficiency of network functions. Furthermore, redundant edges, behaving as energy redundant links in a network structure, can considerably improve the robustness of the network by optimizing the removal of redundant edges. Dynamic repair is not only an efficient repair method but also a highly flexible choice for network repair. [ABSTRACT FROM AUTHOR]

This article investigates the robust stabilization problem for nonlinear time-delay systems with dead-zone input and complex dynamics. By flexibly using the inequality technique, the backstepping control method, and skillfully introducing a new Lyapunov–Krasovskii functional, we obtain a stable controller without using unmeasurable signals in the dynamic subsystem. The control system is guaranteed to be stable finally. Two simulation examples are given to verify the control strategy. [ABSTRACT FROM AUTHOR]

Dissolved oxygen (DO) concentration is a key variable in wastewater treatment process (WWTP). It directly influences effluent quality of a wastewater treatment. However, due to the great changes of the influent flow rate and the large uncertainties of the wastewater in composition, concentration, and temperature, most control approaches become powerless on DO regulation. To improve the robustness of a DO control, and reduce the phase delay between the control input and the system output, a U-model-based active disturbance rejection control (UADRC) is proposed. The U-model control (UC) reduces the phase delay between the control input and the system output. The active disturbance rejection control (ADRC) enhances the robustness of the closed-loop system. Also, ADRC converts the system dynamics to be integrators connected in series, which helps the realization of UC. By changing the system dynamics to be an approximate unit, a controller based on desired closed-loop system dynamics can be designed and the DO concentration is guaranteed. UADRC combines advantages of both UC and ADRC, and a commonly accepted benchmark simulation model no.1 (BSM1) is taken to verify the proposed UADRC. Numerical results show that, with similar energy consumption, the UADRC is able to achieve much better tracking performance than ADRC, SMC, and PI with suggested parameters. [ABSTRACT FROM AUTHOR]

A robust receding horizon control (RHC) with free control moves is applied to polytopic parametric uncertainty systems with multiple input delays and unstable system matrices. A difficulty in the previous robust RHC work is that the free control moves are unsuitable for the system with input time delay, which is overcome in this paper by the design based on the augmented state. As a result, the synthesis of local control based on augmented feedback is given offline to alleviate the online computation burden. The free control moves before the augmented feedback are the online decision variables, which are solved by minimizing a sequence of nonnegative scalars online. The recursive feasibility is guaranteed by adopting the augmented state space equation. By adjusting the robust positively invariant set, the stability of the closed-loop system is guaranteed. Simulation results demonstrate that the proposed algorithm improves the control performance effectively. [ABSTRACT FROM AUTHOR]

In this paper, the air-fuel ratio regulation problem of compressed natural gas (CNG) engines considering stochastic L2 disturbance attenuation is researched. A state observer is designed to overcome the unmeasurability of the total air mass and total fuel mass in the cylinder, since the residual air and residual fuel that are included in the residual gas are unmeasured and the residual gas reflects stochasticity. With the proposed state observer, a stochastic robust air-fuel ratio regulator is proposed by using a CNG engine dynamic model to attenuate the uncertain cyclic fluctuation of the fresh air, and the augmented closed-loop system is mean-square stable. A validation of the proposed stochastic robust air-fuel ratio regulator is carried out by the numerical simulation of two working conditions. The accuracy control of the air-fuel ratio is realized by the proposed stochastic robust air-fuel ratio regulator, which in turn leads to an improvement in fuel economy and emission performance of the CNG engines. [ABSTRACT FROM AUTHOR]

This paper investigates the robust H ∞ path-tracking control problem of network-based autonomous vehicles (AVs) with delay and packet dropout. Generally, both network-induced delay and packet dropout bring negative effects on the system stability and performance. A robust H ∞ control scheme is proposed to realize the desired path tracking and lateral stability. The closed-loop system is asymptotically stable with the prescribed H ∞ disturbance attention level if there exist some matrices satisfying certain linear matrix inequality (LMI) conditions. Furthermore, the proposed controller is robust to the parameter uncertainties and external disturbances. Simulation results are presented to verify the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

In this paper, a new approach to the decentralized control design for vehicle platooning for uncertain automated highway systems is proposed. The uncertainty in the system, which is nonlinear and (possibly) fast time-varying, is bounded. The bound is assumed to be within a prescribed fuzzy set. A creative transformation is made to the system, which converts a local problem to a global problem. Based on the fuzzy description of the uncertainty bound and the transformation, a class of decentralized control is proposed in which each vehicle only needs the knowledge of its preceding vehicle in the platoon. No acceleration feedback or the information of the leading vehicle is required. Both the vehicle platooning system and the control are deterministic, hence not if-then fuzzy rule-based. The performance of the resulting controlled system is twofold. First, the collision avoidance performance is guaranteed under any safe initial conditions regardless of the value of the uncertainty. Second, the minimization of a fuzzy-based performance index is guaranteed based on an optimal choice of a control design parameter. Numerical simulations are conducted to validate the efficiency of the proposed algorithm. [ABSTRACT FROM AUTHOR]

The fluctuation of industrial process operation parameters will severely influence the production process. How to find the robust optimal process operation parameters is an effective method to address this problem. In this paper, a scheme based on data-driven model and variable fluctuation analysis is proposed to obtain the robust optimal operation parameters of industrial process. The data-driven modelling method: multivariate Gaussian process regression (MGPR) based on Bayesian statistical learning theory can map the process operation parameters to objective performance with the flexibility in nonparameter inferring and the self-adaptiveness to determinate hyperparameters. According to the minimum variance criterion, the parameter fluctuation analysis can be performed through multiobjective evolutionary algorithm based on the MGPR model. To analyze the robustness influence of a single parameter, cross validation is applied to evaluate the model output with 2% fluctuation. After that, the robust optimal process operation parameters can be obtained and applied to guide the production. The effectiveness and reliability of the proposed method have been verified with the hydrogen cyanide production process and compared with other model methods and single objective optimization method. [ABSTRACT FROM AUTHOR]

This paper proposes an innovative adaptive neural prescribed performance control (PPC) scheme for large classes of nonlinear, nonstrict-feedback systems under input saturation constraint. A restrictive hypothesis under which the upper and lower bounds of control gain functions exist a priori is first relieved by constructing appropriate compact sets within which all state trajectories are held. A novel asymmetry error transformed variable is then introduced to cope with the nondifferentiable obstacle and complex deductions corresponding to traditional PPC schemes. To efficiently manage the input saturation constraint, a new auxiliary dynamic system with a bounded compensation tangent function term is established as the strictly bounded assumption of the dynamic system is canceled. It is rigorously proven that all signals in the closed-loop systems are semiglobally uniformly ultimately bounded under both Lyapunov and invariant set theories. The tracking errors converge to a small tunable residual set with prescribed performance under the effect of the input saturation constraint. The effectiveness of the proposed control scheme is thoroughly verified by two simulation examples. [ABSTRACT FROM AUTHOR]

We consider the robust asymptotical stabilization problem for uncertain singular systems. We design a new impulsive control technique to ensure that the controlled singular system is robustly asymptotically stable and hence derive the corresponding stability criteria. These sufficient conditions are expressed in the form of algebra matrix inequalities and can be implemented numerically. We finally provide a numerical example of a transportation system to illustrate the effectiveness and usefulness of the proposed criteria. [ABSTRACT FROM AUTHOR]

There is a challenge in characterizing the soft tissue mechanical functionality in cylindrical geometries by current elastography techniques applied to small organs. Torsional waves are a type of shear elastic waves that propagate through soft tissue radially and in depth in a curled geometry, ideally suited to explore structures such as the cervix. Here, a sensor based on a novel arrangement of concentric sandwiches of piezo- and electromechanical elements is prototyped and tested to quantitatively assess stiffness in human cervix. The purpose is to determine the robustness of a torsional wave elastography (TWE) sensor prototype to quantify cervical stiffness, as a first step to validate a reliable measurement protocol using TWE. An array of tests designed to validate a set of hypothesis about the contact conditions were performed on up to 3 different nonpregnant voluntary women. The mechanical properties were reconstructed from the recorded TWE signals, and the outcomes were statistically analyzed to validate the contact condition hypothesis. The results suggest that, although future tests need to be performed to fully assess the repeatability and quality of the measurements, some characteristics of the measurement protocol become clear; in particular: (1) the use of speculum is recommended since it not only stabilizes the measurements, but also corrects and stabilizes the orientation of the cervical neck, and allows to visually verify the positioning and alignment of the probe, while not significantly increasing discomfort to women during this test; (2) the use of lubricant gel has no significant effect on the measurement quality; (3) 1cm off-centering from external cervical os is not acceptable; (4) a range of applied force between 500-2000 N does not significantly vary measurement signal quality, but the reconstructed value of the shear modulus does vary, probably due to its constitutive nonlinearity; (5) breathing movements affects measurements, but short duration of TWE pulse (0.3 s) allows to take measurements in apnea. [ABSTRACT FROM AUTHOR]

A control algorithm that is robust with respect to wind disturbances for a quadrotor UAV attitude dynamics is presented. The proposed approach consists of a high-gain observer based on a discontinuous technique. Such an algorithm is embedded on board the quadrotor. The high-gain observer estimates external disturbances such as wind and parameter uncertainties, and a control algorithm is designed to compensate these undesired effects. The observer design is based on Lyapunov stability theory; simulation results and experiments validate the nonlinear observer performance and robustness of the approach under windy conditions. Also, a photogrammetry survey was carried out to develop Digital Elevation Models in order to experimentally demonstrate the effectiveness of our approach. The accuracy of such models was compared and the performance improvement is demonstrated. [ABSTRACT FROM AUTHOR]

In this paper, the problem of robust preview control for uncertain discrete singular systems is considered. First of all, by employing the forward difference for uncertain discrete singular systems, the singular augmented error system with the state vector, the input control vector, and the previewable reference signal is derived. Since there is a singular matrix in the system, the existing method cannot be directly applied to this problem. By considering the stability of the transposition system with Linear Matrix Inequality (LMI) method, a new stability criterion for the transposition system is introduced. Then, the robust controller for the augmented error system is obtained, which is regarded as the robust preview controller for the original singular system. At last, the numerical simulation shows the correctness and effectiveness of the results. [ABSTRACT FROM AUTHOR]

A phase-based adaptive differential evolution (PADE) algorithm is proposed to solve the economic load dispatch (ELD) considering valve-point effects (VPE) and transmission losses. To a great extent, PADE makes up for the drawbacks of the traditional differential evolution (DE) through three improvements. First, we establish an archive of storing successful individuals to improve the quality of offspring. Second, to balance the exploring and exploiting ability of the algorithm, a phase-based mutation operation is carried out. Third, two control parameters are adaptively adjusted, which is helpful for enhancing the robustness of the algorithm. In addition, two types of repair methods of constraint handling are employed for the ELD without or with transmission losses to help PADE find feasible solutions more efficiently. A performance comparison between PADE and other DE approaches from the literature was carried out on six ELD test cases which consider a set of operating constraints including the VPE and transmission losses. Results show a competitive PADE performance in all test cases regarding the compared DE approaches. Compared to methods from the literature, the costs obtained by PADE are lower in most cases while the corresponding constraint violations reach a lower level. [ABSTRACT FROM AUTHOR]

The regulation of a disturbed output can be improved when several manipulated inputs are available. A popular choice in these cases is the series control scheme, characterized by (1) a sequential intervention of loops and (2) faster loops being reset by slower loops, to keep their control action around convenient values. This paper tackles the problem from the frequency-domain perspective. First, the working frequencies for each loop are determined and closed-loop specifications are defined. Then, Quantitative Feedback Theory (QFT) bounds are computed for each loop, and a sequential loop-shaping of controllers takes place. The obtained controllers are placed in a new series architecture, which unlike the classical series architecture only requires one controller with integral action. The benefits of the method are greater as the number of control inputs grow. A continuous stirred tank reactor (CSTR) is presented as an application example. [ABSTRACT FROM AUTHOR]

The novel hybrid multilevel storage system will be popular with SSD being integrated into traditional storage systems. To improve the performance of data migration between solid-state hard disk and hard disk according to the characteristics of each storage device, identifying the hot data block is significant issue. The hot data block prediction model based on wavelet neural network is built and trained by using historical data. This prediction model can overcome the cumulative effect of traditional statistical methods and has strong sensitivity to I/O loads with random variations. The experimental results show that the proposed model has better accuracy and faster learning speed than BP neural network model. In addition, it has less dependence on sample data and has better generalization ability and robustness. This model can be applied to the data migration of distributed hybrid storage systems to improve performance. [ABSTRACT FROM AUTHOR]

During the past few decades, face recognition has been an active research area in pattern recognition and computer vision due to its wide range of applications. However, one of the most challenging problems encountered by face recognition is the difficulty of handling large head pose variations. Therefore, the efficient and effective head pose estimation is a critical step of face recognition. In this paper, a novel feature extraction framework, called Directional Correlation Filter Bank (DCFB), is presented for head pose estimation. Specifically, in the proposed framework, the 1-Dimensional Optimal Tradeoff Filters (1D-OTF) corresponding to different head poses are simultaneously and jointly designed in the low-dimensional linear subspace. Different from the traditional methods that heavily rely on the precise localization of the key facial feature points, our proposed framework exploits the frequency domain of the face images, which effectively captures the high-order statistics of faces. As a result, the obtained features are compact and discriminative. Experimental results on public face databases with large head pose variations show the superior performance obtained by the proposed framework on the tasks of both head pose estimation and face recognition. [ABSTRACT FROM AUTHOR]

With a purpose to evolve the surfaces of complex geometries in their normal direction at arbitrarily defined velocities, we have developed a robust level-set approach which runs on three-dimensional unstructured meshes. The approach is built on the basis of an innovative spatial discretization and corresponding gradient-estimating approach. The numerical consistency of the estimating method is mathematically proven. A correction technology is utilized to improve accuracy near sharp geometric features. Validation tests show that the proposed approach is able to accurately handle geometries containing sharp features, computation regions having irregular shapes, discontinuous speed fields, and topological changes. Results of the test problems fit well with the reference results produced by analytical or other numerical methods and converge to reference results as the meshes refine. Compared to level-set method implementations on Cartesian meshes, the proposed approach makes it easier to describe jump boundary conditions and to perform coupling simulations. [ABSTRACT FROM AUTHOR]

This paper considers the design of the robust preview controller for a class of uncertain discrete-time Lipschitz nonlinear systems. According to the preview control theory, an augmented error system including the tracking error and the known future information on the reference signal is constructed. To avoid static error, a discrete integrator is introduced. Using the linear matrix inequality (LMI) approach, a state feedback controller is developed to guarantee that the closed-loop system of the augmented error system is asymptotically stable with H∞ performance. Based on this, the robust preview tracking controller of the original system is obtained. Finally, two numerical examples are included to show the effectiveness of the proposed controller. [ABSTRACT FROM AUTHOR]

The dynamic model of the Electric Power Steering (EPS) system for electric forklifts and the two-degree-of-freedom (2DOF) forklift models has been established. Based on the control target of electric forklift EPS, a generalized EPS control model with model perturbation and interference is established. The standard H∞control model of the EPS system is transformed, and the EPS generalized state equation of electric forklift is derived. The principle of robust control with genetic optimization is expounded, aiming at the parameters optimization of the weighted function of H∞control model, the constraint function of the genetic algorithm (GA) is constructed, and the robust controller of genetic optimization is derived. Taking the electric forklift TFC20 as the research object, according to the actual data on the forklift, the system model is established in MATLAB, and the effects of PID control, robust control, and genetic robust control are compared, the results show that the power steering characteristic of the robust control is better than the power steering characteristic of the PID control, and the stability of the forklift under the control of robust control is better. Also, the power steering characteristic of the H∞ controller with GA optimization is better than that of an unoptimized one, and its robustness is better, under external pavement interference, the following ability is stronger for the ideal current and the steering is more stable. [ABSTRACT FROM AUTHOR]

Co-Kriging (CK) modeling provides an efficient way to predict responses of complicated engineering problems based on a set of sample data obtained by methods with varying degree of accuracy and computation cost. In this work, the Gaussian random process (GRP) is introduced to construct a novel combination CK model (CK-GRP) to improve the prediction accuracy of the conventional CK model, in which all the sample information provided by different correlation models is well utilized. The features of the new model are demonstrated and evaluated for a numerical case and an engineering application. It is shown that the CK-GRP model proposed in this work is effective and can be used to improve the prediction accuracy and robustness of the CK model. [ABSTRACT FROM AUTHOR]

A robust newsvendor model with discrete demand is initiatively studied, and the steps to obtain the optimal ordering decision are provided. The study shows that the optimal ordering decision with discrete demand is very different from that with continuous demand. Besides, the total number of demand points has almost no effect on the performance of both ordering decisions. Furthermore, for an ultralow-profit product, the ordering decision with discrete demand performs significantly better than that with continuous demand. [ABSTRACT FROM AUTHOR]

For a class of nonlinear harmonic gear drive systems with mismatched uncertainties, a novel robust control method is presented on the basis of quadratic integral sliding mode surface, and the closed-loop system has satisfying performance and strong robustness against mismatched uncertainties and nonlinear disturbances. Considering time-varying nonlinear torques and parameters variations which are caused by nonlinear frictions and backlash, a nonlinear harmonic gear drive system mathematic model is established and the effect of nonlinear parts is compensated during control system design. It is proven that the quadratic integral sliding mode surface can be reached in finite time and the closed-loop system is asymptotic stable robustly. The simulation studies are carried out in comparison with traditional linear sliding mode control and integral sliding mode control, verifying the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The robust generation self-scheduling problem under electricity price uncertainty is usually solved by the commercial solver, which is limited in computation time and memory requirement. This paper proposes an improved Lagrangian relaxation algorithm for the robust generation self-scheduling problem where the quadratic fuel cost and the time-dependent exponential startup cost are considered. By using the optimal duality theory, the robust generation self-scheduling problem, which has a max-min structure, is reformulated as a minimization mixed integer nonlinear programming (MINLP) problem. Upon the reformulation, the Lagrangian relaxation algorithm is developed. To obtain a solvable relaxed problem, the variable splitting technique is introduced before the relaxation. The obtained relaxed problem is decomposed into a linear programming-type subproblem and multiple single-unit subproblems. Each single-unit subproblem is solved optimally by a two-stage backward dynamic programming procedure. The special cases of the problem are discussed and a two-stage algorithm is proposed. The proposed algorithms are tested on test cases of different sizes and the numerical results show that the algorithms can find near-optimal solutions in a reasonable time. [ABSTRACT FROM AUTHOR]