Quantized H∞ filtering for switched linear parameter-varying systems with sojourn probabilities and unreliable communication channels

Event-Triggered Asynchronous Filter of Nonlinear Switched Positive Systems with Output Quantization

This paper deals with a static/dynamic event-triggered asynchronous filter of nonlinear switched positive systems with output quantization. The nonlinear function is located in a sector. Both static and dynamic event-triggering conditions are established based on the 1-norm form. By virtue of the event-triggering mechanism, the error system is transformed into an interval uncertain system. An event-triggered asynchronous filter is designed by employing a matrix decomposition approach. The positivity and L1-gain stability of the error system are guaranteed by means of linear copositive Lyapunov functions and a linear programming approach. Finally, two examples are given to verify the effectiveness of the design.

Dissipativity Analysis for T-S Fuzzy System Under Memory Sampled-Data Control

The dissipative stability problem for a class of Takagi-Sugeno (T-S) fuzzy systems with variable sampling control is the focus of this paper. The controller signals are assumed to transmit with a constant delay. Our aim is to design the sampled-data controller such that the T-S fuzzy system is globally asymptotically stable with a (Q,S,R) - γ -dissipative performance index. The stability is analyzed by using a novel piecewise Lyapunov-Krasovskii functional (LKF) together with a looped-functional and free-matrix-based (FMB) inequality method. First, several useful linear matrix inequality (LMI) conditions are derived to verify the dissipative stability of the T-S fuzzy system and then the controller gains matrices are expressed by resorting the LMI approach with the maximal-allowable upper bound (MAUB) of sampling periods. The proposed LMI conditions can be easily solved by using the MATLAB tool box. Finally, the numerical example of a truck-trailer system is considered and analyzed by the proposed scheme to illustrate the benefit and superiority.

Optimal power allocation for multiple DoS attackers in wireless networked control systems

In this paper, an optimal power allocation strategy for multiple denial-of-service attackers is investigated in a wireless networked control system with stochastic disturbances. In the presence of denial-of-service attackers, effective signals sent by a transmitter are interfered with causing degradation of signal-to-interference-plus-noise ratio and even packet loss. The effect of multiple attacks on the wireless networked control system is maximized by cooperative game. An H_∞ minimax controller is also designed to guarantee an optimal performance for the wireless networked control system in the worst case. A numerical example is conducted to verify the validity of the proposed methodology.

Reprint of: Observer-based output feedback H∞ control for cyber-physical systems under randomly occurring packet dropout and periodic DoS attacks

This paper investigates the observer-based output feedback control problem for cyber-physical systems against randomly occurring packet dropout and periodic Denial-of-Service (DoS) attacks. Two independent Bernoulli distribution are employed to model the randomly occurring packet dropout and periodic DoS attacks such that the considered system can be viewed as a stochastic system. Then, by stochastic analysis method, it proves that the closed-loop systems are still stochastically stable and satisfy a specified H_∞ performance. The relationship between the disturbance rejection capacity and the success rate of a DoS attacker is also analyzed. Moreover, some novel inequalities and auxiliary matrices are adopted to remove the restrictive conditions on input matrix B and the diagonal structure of Lyapunov function. Finally, three examples are utilized to show the applicability of the proposed method.

Event-triggered filter design for nonlinear cyber-physical systems subject to deception attacks

This paper is concerned with an event-triggered filter design for fuzzy-model-based cyber-physical systems with cyber-attacks. Spurious events may be triggered under the conventional event-triggered mechanism (ETM) when the sampling data has a rapid change arising from unpredicted external disturbance. To avoid spurious decisions on data releasing a new ETM is proposed. Furthermore, the communication network is vulnerable to attacks by malicious attackers. Under this scenario, a new resilient filter is designed to ensure the security. Sufficient conditions are established to make the filtering error system asymptotically stable. A numerical example is provided to show the effectiveness of the proposed results.

Dissipativity-Based Asynchronous Fuzzy Sliding Mode Control for T-S Fuzzy Hidden Markov Jump Systems

This paper investigates the problem of dissipativity-based asynchronous fuzzy integral sliding mode control (AFISMC) for nonlinear Markov jump systems represented by Takagi-Sugeno (T-S) models, which are subject to external noise and matched uncertainties. Since modes of original systems cannot be directly obtained, the hidden Markov model is employed to detect mode information. With the detected mode and the parallel distributed compensation approach, a suitable fuzzy integral sliding surface is devised. Then using Lyapunov function, a sufficient condition for the existence of sliding mode controller gains is developed, which can also ensure the stochastic stability of the sliding mode dynamics with a satisfactory dissipative performance. An AFISMC law is proposed to drive system trajectories into the predetermined sliding mode boundary layer in finite time. For the case with unknown bound of uncertainties, an adaptive AFISMC law is developed as well. The studied T-S fuzzy Markov jump systems involve both continuous-time and discrete-time domains. Finally, some simulation results are presented to demonstrate the applicability and effectiveness of the proposed approaches.

State estimation for cyber-physical systems with limited communication resources, sensor saturation and denial-of-service attacks

This paper addresses the issue of the state estimation for cyber-physical systems (CPSs) with limited communication resources, sensor saturation and denial-of-service (DoS) attacks. In order to conveniently handle nonlinear term in CPSs, a Takagi-Sugeno (T-S) fuzzy model is borrowed to approximate it. The event-triggered scheme and quantization mechanism are introduced to relieve the effects brought by limited communication resources. By taking the influence of sensor saturation and DoS attacks into account, a novel mathematical model of state estimation for CPSs is constructed with limited communication resources. By using the Lyapunov stability theory, the sufficient conditions, which can ensure the system exponentially stable, are derived. Moreover, the explicit expressions of the event-based estimator gains are obtained in the form of linear matrix inequalities (LMIs). At last, a simulated example is provided for illustrating the effectiveness of the proposed method.

Finite-horizon tracking control for a class of stochastic systems subject to input constraints and hybrid cyber attacks

This paper is concerned with the probabilistic-constrained finite-horizon tracking control problem for a class of stochastic systems subject to randomly occurring hybrid cyber attacks and input constraints. Both the randomly occurring denial-of-service (DOS) attacks and randomly occurring deception attacks are considered in an unified framework. The purpose of the current study is to design an observer-based tracking controller such that: over a finite horizon, (1) the variance of the estimation error is less than certain bound at each time step, (2) the probability of the tracking error falling in certain region should larger than a specified value and the region is minimized at each time step. To achieve those purposes, an improved multi-dimensional Chebyshev inequality method is first utilized to convert the probabilistic constraint to a deterministic one. Then an observer-based tracking control method is designed to estimate the state and design the tracking controller, which are realized through solving a set of recursive linear matrix inequalities. By using the proposed algorithm, the observer and tracking controller gains can be solved out in terms of the solution to a convex optimization problem. A simulation example is finally given to demonstrate the effectiveness and applicability of the proposed method.

Fuzzy Output Tracking Control and Filtering for Nonlinear Discrete-Time Descriptor Systems Under Unreliable Communication Links

In this paper, the problems of output tracking control and filtering are investigated for Takagi-Sugeno fuzzy-approximation-based nonlinear descriptor systems in the discrete-time domain. Especially, the unreliability of the communication links between the sensor and actuator/filter is taken into account, and the phenomenon of packet dropouts is characterized by a binary Markov chain with uncertain transition probabilities, which may reflect the reality more accurately than the existing description processes. A novel bounded real lemma (BRL), which ensures the stochastic admissibility with H_∞ performance for fuzzy discrete-time descriptor systems despite the uncertain Markov packet dropouts, is presented based on a fuzzy basis-dependent Lyapunov function. By resorting to the dual conditions of the obtained BRL, a solution for the designed fuzzy output tracking controller is given. A design method for the full-order fuzzy filter is also provided. Finally, two examples are finally adopted to show the applicability of the achieved design strategies.

Decentralized Finite-time L2-L∞ tracking control for a class of interconnected Markovian jump system with actuator saturation

An observer-based decentralized tracking control technique is developed for a saturated interconnected Markovian jump system in the sense of finite-time stability (FTS). To improve tracking performances, a L₂-L_∞ performance criterion which is relevant to both estimated error and estimated tracking error is proposed. A sufficient condition for finite-time bounded (FTB) is established. In view of the obtained condition, a method with the one-step procedure to seek the gains of observer and controller is investigated. By virtue of this procedure, the problem of the decentralized tracking stabilization is transformed into a convex optimization problem subject to constraints in the form of linear matrix inequalities (LMIs). Furthermore, the tracking control problem of interconnected Markovian jump system without saturation is also investigated, and the results are obtained directly to avoid taking congruent transformation. Simulation is presented to show the effectiveness and applicability of the obtained results.

Observer-based output feedback H∞ control for cyber-physical systems under randomly occurring packet dropout and periodic DoS attacks

This paper investigates the observer-based output feedback control problem for cyber-physical systems against randomly occurring packet dropout and periodic Denial-of-Service (DoS) attacks. Two independent Bernoulli distribution are employed to model the randomly occurring packet dropout and periodic DoS attacks such that the considered system can be viewed as a stochastic system. Then, by stochastic analysis method, it proves that the closed-loop systems are still stochastically stable and satisfy a specified H_∞ performance. The relationship between the disturbance rejection capacity and the success rate of a DoS attacker is also analyzed. Moreover, some novel inequalities and auxiliary matrices are adopted to remove the restrictive conditions on input matrix B and the diagonal structure of Lyapunov function. Finally, three examples are utilized to show the applicability of the proposed method.

New Results on Stability Analysis for Delayed Markovian Generalized Neural Networks With Partly Unknown Transition Rates

The stability of delayed Markovian generalized neural networks is studied where the transition rates of the modes are partly unknown. The partly unknown transition rates generalize the traditional works that are with all known transition rates. Then, a Lyapunov-Krasovskii functional (LKF) with a delay-product-type (DPT) term is constructed. The DPT term is not only simple but also fully utilizes the information of time delay. Based on the new DPT LKF, stability criteria are presented, which are with lower computational complexity and less conservative. In the end, the validity and superiorities of the analytical results are verified by several examples.

Nonfragile H∞ control for periodic stochastic systems with probabilistic measurement

This paper addresses the problem of nonfragile H_∞ control for periodic stochastic systems with probabilistic measurement. A novel Lyapunov-Krasovskii functional is formulated, which makes full use of both delay and its change rate. In view of the measurement signal, the mode-dependent stochastic variables are employed and new sufficient conditions are achieved. Finally, two numerical examples are worked out to demonstrate the effectiveness of the proposed control design.