Reliable Sampled-data Control Research Articles

Finite-time reliable sampled-data control for fractional-order memristive neural networks with quantisation

ABSTRACT This paper addresses the reliable finite-time stabilisation problem for a class of fractional-order memristor neural networks under sampled-data controller influenced by the quantisation signal and actuator failures. Precisely, the framework of observer has been initiated for estimating unmeasured state and remunerate the actuator faults with nonlinearities in the controller. Precisely, quantiser is incorporated in the network can reduce the process of transmitting data. Subsequently, activation function approach bringing together with traditional indirect Lyapunov theory endows some sufficient conditions in the frame of linear matrix inequalities to assure the finite-time stabilisation criterion for the addressed neural networks under the proposed reliable sampled-data control. Explicitly, the state feedback control and observer gain matrices are attained by solving the developed linear matrix inequalities. Convincingly, two numerical simulations are explored to substantiate the excellence and potentiality of the developed control law.

Dissipativity-based resilient reliable sampled-data asynchronous control for interval-valued fuzzy systems with semi-Markovian hybrid fault coefficients

Dissipativity-based resilient reliable sampled-data asynchronous control for interval-valued fuzzy systems with semi-Markovian hybrid fault coefficients

Extended dissipative analysis for T–S fuzzy system with sampled-data input and actuator fault

This paper is concerned with reliable robust sampled-data control for T–S fuzzy system with time-varying delay. By adjusting the free weight matrix in the concept of extended dissipative, , , passive and -dissipative performance are solved in a unified framework. A novel mode-dependent Lyapunov–Krasovskii functional (LKF) is constructed, which fully utilises the characteristics of the real sampling period. Based on Lyapunov stability theory, Newton–Leibniz condition and new integral inequality techniques, some less conservative sufficient conditions are obtained to guarantee the close-loop system is asymptotically stable and extended dissipative. Based on sampled-data approach, a robust reliable controller can be developed by solving the linear matrix inequalities (LMIs). The advantage and effectiveness of the proposed design method can be illustrated by several numerical examples.

Stabilization of Interval Type-2 Fuzzy-Based Reliable Sampled-Data Control Systems.

This article investigates the stabilization problem of the Takagi-Sugeno (T-S) fuzzy-based interval type-2 (IT-2) reliable sampled-data control system. Different from the existing studies, the information for the entire sampling interval with a relation of the augmented state vectors is considered for designing the reliable sampled-data control of IT-2 T-S fuzzy systems. In this regard, we construct the suitable looped Lyapunov-Krasovskii functional (LKF) with the information of the fuzzy membership function that feeds back the time derivative of the membership function to derive sufficient conditions. These sufficient conditions are established in the form of linear matrix inequalities (LMIs), which ensure the global asymptotic stability of T-S fuzzy systems under the designed control technique. Finally, the applicability and superiority of developed reliable sampled-data control techniques were validated by three practical systems.

Impulsive method to reliable sampled-data control for uncertain fractional-order memristive neural networks with stochastic sensor faults and its applications

This paper is devoted to investigate the issue of fault-tolerant sampled-data control for a class of uncertain fractional-order memristive neural networks with random switching topologies subject to stochastic sensor faults via impulsive method. Firstly, a fault detection sampled-data control strategy is proposed for sensor failure. Then, by utilizing the constructed quasi-periodic polynomial Lyapunov function, the criterion for ensuring that the transformed pulse system achieves asymptotic stability is established. Moreover, based on this criterion and with the help of the mechanism of sum of squares (SSs), the desired reliable control gain matrix is obtained. Finally, a numerical example is employed to demonstrate the validity of our method, and this method is applied to the well-known fractional-order Chua???s circuit system. Compared to large quantities of results for integer-order memristive neural networks, only a small number of results are for fractional order. In particular, the sampling-controlled fractional-order memristive neural networks have not been solved until now, let alone the novel impulive approach designed in this paper. This paper is the first attempt to make up for this vacancy in this topic.

Non-fragile asynchronous reliable sampled-data control for uncertain fuzzy systems with Bernoulli distribution

In this study, the non-fragile asynchronous reliable sampled-data control for uncertain Takagi–Sugeno fuzzy systems with Bernoulli distribution is addressed. The system involves both the randomly occurring uncertainties of parameters in the fuzzy system model and randomly occurring gain perturbations of the controller. By introducing three stochastic variables, a new model structure satisfying Bernoulli distribution is formulated to describe the system and the controller. The main purpose of this study is to design the non-fragile asynchronous reliable sampled-data controller such that the considered system is finite-time bounded and possesses finite-time mixed H∞ and passive performance. Based on an improved Lyapunov–Krasovskii functional, newly bounding inequalities and stochastic processing method, new conditions satisfying the required result are derived for the uncertain fuzzy systems in terms of linear matrix inequalities. Moreover, a modified non-fragile asynchronous reliable sampled-data controller is designed. Finally, two numerical examples are given to demonstrate the effectiveness of the presented results.

Fault-tolerant sampled-data control of singular networked cascade control systems

ABSTRACTThis paper investigates the reliable sampled-data control problem for a class of singular networked cascade control systems with randomly occurring actuator failures, time-varying delay and disturbances. In particular, the randomly occurring actuator failures describes the phenomenon of the actuator failure appearing in a random way and is modelled by a Bernoulli distributed white noise sequences with a known conditional probability. The main purpose of this work is to design a reliable sampled-data controller such that an optimised upper bound of the predefined performance index is well guaranteed for the systems under consideration even in the presence of both the randomly occurring actuator failures and disturbances. The resulting controllers are reliable in the sense that they will provide guaranteed stochastically admissible and performance index when all actuators are operational as well as when some actuators experiences failure. Finally, two numerical examples are given to exhibit the effectiveness of the proposed control scheme.

Finite-time resilient reliable sampled-data control for fuzzy systems with randomly occurring uncertainties

This paper deals with the problem of finite-time passivity-based H∞ resilient reliable state feedback sampled-data control for Takagi–Sugeno fuzzy systems with randomly occurring uncertainties and gain variations, where the randomly occurring characteristics are designed by stochastic variables satisfying the Bernoulli distribution. The main objective of this paper is to design a resilient reliable sampled-data controller such that the resulting closed-loop system is finite-time bounded and satisfies finite-time mixed H∞ and passive performance index γ. Based on the constructed Lyapunov–Krasovskii functional and Wirtinger integral inequality, some delay-dependent sufficient conditions are derived for achieving the required result of the considered systems. Moreover the derived finite-time stability conditions are established in the form of linear matrix inequalities (LMIs) which can be solved by Matlab LMI toolbox. Finally two numerical examples are presented to demonstrate the applicability of the proposed control design technique.

Synchronization of Lur׳e systems via stochastic reliable sampled-data controller

This paper deals with the problem of synchronization methods for Lur׳e system with stochastic reliable sampled-data control scheme. By constructing the framework of linear matrix inequalities (LMIs) based on Lyapunov method and utilizing Wirtinger-based integral inequality (WBI), Jensen׳s inquality (JI), and other lemmas, synchronization criteria of sampled-data control for Lur׳e systems are derived and compared with the existing works. The necessity and validity of the proposed results are illustrated by two numerical examples.

Dissipativity-Based Reliable Sampled-Data Control With Nonlinear Actuator Faults

In this paper, the problem of reliable sampled-data control design with strict dissipativity for a class of linear continuous-time-delay systems against nonlinear actuator faults is studied. The main objective of this paper is to design a reliable sampled-data controller to ensure a strictly dissipative performance for the closed-loop system. Based on the linear matrix inequality (LMI) optimization approach and Wirtinger-based integral inequality, a new set of sufficient conditions is established for reliable dissipativity analysis of the considered system by assuming the mixed actuator fault matrix to be known. Then, the proposed result is extended to unknown fault matrix case. Also, the reliable sampled-data controller with strict dissipativity is designed by solving a convex optimization problem which can be easily solved by using standard numerical algorithms. Finally, a numerical example based on liquid propellant rocket motor with a pressure feeding system model is presented to illustrate the effectiveness of the developed control design technique.

Reliable sampled-data vibration control for uncertain flexible spacecraft with frequency range limitation

This paper deals with the problem of reliable finite frequency vibration control for flexible spacecraft subject to torque constraint, actuator failure and linear fractional transformation (LFT) uncertainty. The practical sampled-data control signal is converted into a continuous-time input with time-varying delay. Since the main vibration energy of flexible spacecraft is dominated by low-frequency vibration modes lying in a specific frequency band, a novel reliable robust \(H_\infty \) output feedback controller with frequency constraint is employed here to suppress these resonance modes. Compared with classic full frequency scheme, finite frequency algorithm achieves a lower upper bound of vibration reduction performance even under the circumstance of torque constraint, actuator failure and LFT uncertainty. By convex optimization techniques, the problem of seeking admissible controller is transformed into the feasibility of linear matrix inequalities. The merits and effectiveness of proposed control algorithm are confirmed by an illustrative design example.

Reliable Sampled-Data Control of Fuzzy Markovian Systems with Partly Known Transition Probabilities

Abstract This article presents a fuzzy dynamic reliable sampled-data control design for nonlinear Markovian jump systems, where the nonlinear plant is represented by a Takagi–Sugeno fuzzy model and the transition probability matrix for Markov process is permitted to be partially known. In addition, a generalised as well as more practical consideration of the real-world actuator fault model which consists of both linear and nonlinear fault terms is proposed to the above-addressed system. Then, based on the construction of an appropriate Lyapunov–Krasovskii functional and the employment of convex combination technique together with free-weighting matrices method, some sufficient conditions that promising the robust stochastic stability of system under consideration and the existence of the proposed controller are derived in terms of linear matrix inequalities, which can be easily solved by any of the available standard numerical softwares. Finally, a numerical example is provided to illustrate the validity of the proposed methodology.

Dissipative based adaptive reliable sampled-data control of time-varying delay systems

This paper is concerned with the problem of dissipative based adaptive reliable controller for a class of time delay systems subject to actuator failures and time-varying sampling with a known upper bound on the sampling intervals. By constructing a proper Lyapunov-Krasovskii functional which fully uses the available information about the actual sampling pattern and time delays, a new set of sufficient conditions is derived to obtain the required result. Then, a dissipative based adaptive sampled-data controller is designed such that the resulting closed-loop system is reliable in the sense that it is asymptotically stable and has the prescribed dissipative performance under given constraints. The existence condition of the desired dissipative based adaptive reliable sampled-data controller is obtained in terms of linear matrix inequalities. Further, the performance of the proposed controller is implemented on a liquid propellant rocket motor with a pressure feeding system model. The simulation results show the effectiveness and better performance of the proposed adaptive reliable sampled-data controller over conventional reliable controller.

Robust reliable sampled-data control for switched systems with application to flight control

abstractThis paper addresses the robust reliable stabilisation problem for a class of uncertain switched systems with random delays and norm bounded uncertainties. The main aim of this paper is to obtain the reliable robust sampled-data control design which involves random time delay with an appropriate gain control matrix for achieving the robust exponential stabilisation for uncertain switched system against actuator failures. In particular, the involved delays are assumed to be randomly time-varying which obeys certain mutually uncorrelated Bernoulli distributed white noise sequences. By constructing an appropriate Lyapunov–Krasovskii functional (LKF) and employing an average-dwell time approach, a new set of criteria is derived for ensuring the robust exponential stability of the closed-loop switched system. More precisely, the Schur complement and Jensen's integral inequality are used in derivation of stabilisation criteria. By considering the relationship among the random time-varying delay and its lower and upper bounds, a new set of sufficient condition is established for the existence of reliable robust sampled-data control in terms of solution to linear matrix inequalities (LMIs). Finally, an illustrative example based on the F-18 aircraft model is provided to show the effectiveness of the proposed design procedures.

Reliable dissipative sampled-data control for uncertain systems with actuator failures and application to vehicle dynamics

This paper focuses on the dissipative reliable sampled-data control for a class of linear uncertain systems against actuator failures. The main purpose is to design a state feedback reliable dissipative control law such that the resulting closed-loop uncertain system is strictly $({\mathcal Q}, {\mathcal R}, {\mathcal S})-\theta $ dissipative for all admissible actuator failures with a certain prescribed performance constraint. By constructing a proper Lyapunov–Krasovskii functional based on sampled-data strategy, a set of sufficient condition for the existence of the controller is derived in terms of the linear matrix inequality (LMI) technique. It has also been shown that the solutions to the dissipative reliable sampled-data control can be obtained by solving the proposed LMIs. The main advantage of this paper is it unifies $H_\infty $ and passivity control and provides a more flexible control design as it allows for a better trade-off between phase and gain performances. Finally, a numerical example based on vehicle dynamics model is provided to demonstrate the effectiveness of the proposed design technique.

Robust reliable sampled-data control for offshore steel jacket platforms with nonlinear perturbations

In this article, we consider the robust reliable sample-data control problem for an offshore steel jacket platform with input time-varying delay and possible occurrence of actuator faults subject to nonlinear self-exited hydrodynamic forces. The main objective of this work is to design a state feedback reliable sample-data controller such that for all admissible uncertainties as well as actuator failure cases, the resulting closed-loop system is robustly exponentially stable. By constructing an appropriate Lyapunov–Krasovskii functional and using linear matrix inequality (LMI) approach, a new set of sufficient condition is derived in terms of LMIs for the existence of robust reliable sample-data control law. In particular, the uncertainty under consideration in system parameters includes linear fractional norm-bounded uncertainty. Further, Schur complement and Jenson’s integral inequality are used to substantially simplify the derivation in the main results. More precisely, the controller gain matrix for the nonlinear offshore steel jacket platform can be achieved by solving the LMIs, which can be easily facilitated by using some standard numerical packages. Finally, a numerical example with simulation result is provided to illustrate the applicability and effectiveness of the proposed reliable sampled-data control scheme.