Zhenhuan Wang

Bio: Zhenhuan Wang is an academic researcher from Harbin Institute of Technology. The author has contributed to research in topics: Lyapunov function & Exponential stability. The author has an hindex of 6, co-authored 7 publications receiving 297 citations.

Reliable Filter Design for Sensor Networks Using Type-2 Fuzzy Framework

Abstract: This paper studies the problem of reliable filter problem for a category of sensor networks in the framework of interval type-2 fuzzy model. In the filter design, the random link failures, which are caused possibly by missing measurements as well as by probabilistic communication failures, are considered to illustrate more realistic dynamical behaviors of sensor networks. In order to tackle the uncertainties existing in systems, interval type-2 (IT2) fuzzy approach is utilized to establish the model, wherein upper and lower membership functions together with weighting coefficients are employed to express the uncertainties. An distributed IT2 fuzzy filter model is constructed to estimate system states. Using the Lyapunov theory, sufficient conditions have been given to ensure that the filtering error system is mean-square asymptotically stable and satisfies the predefined average $ \mathcal {H}_{\infty }$ performance level. Moreover, the criteria to design the filter parameters are developed through using cone complementary linearization approach. Finally, a practical example is given to validate the proposed method.

Quasi-Time-Dependent Output Control for Discrete-Time Switched System With Mode-Dependent Average Dwell Time

Abstract: This paper is concerned with dynamic output feedback control for a class of switched systems with mode-dependent average dwell-time switching. By constructing a quasi-time-dependent Lyapunov function, the issues of global uniform asymptotic stability and $\ell _{2}$ -gain analysis for the switched system are addressed first. Then, a set of reduced-order output feedback controllers is designed, which is both mode-dependent and quasi-time-dependent. Compared with time-independent criteria, the new results greatly reduce the conservatism. The effectiveness and merits of the proposed method are illustrated with a numerical example.

Interval Type-2 FNN-Based Quantized Tracking Control for Hypersonic Flight Vehicles With Prescribed Performance

Abstract: This paper presents a tracking control scheme with quantization mechanism for hypersonic flight vehicles (HFVs) with prescribed performance using an interval type-2 fuzzy neural network (IT2FNN). A parameterized tracking error model of the HFV is derived with some considered uncertainties, which are approximated by an IT2FNN. The tracking control of the velocity and altitude of the HFV is designed by using a prescribed performance control technique. It allows that transient characteristics of the tracking errors can be improved and adjusted by some prescribed performance functions. According to an adaptive backstepping control design procedure, novel continuous control laws of the fuel equivalency ratio, canard deflection, and elevator deflection are designed with logarithmic quantization mechanism, for the sake of avoiding inadvertently increasing the effective gains of continuous controllers as well as reducing loads of the communication from controller unit to actuator unit. Besides, the limited tracking errors of the flight path angle and angle-of-attack can be achieved by applying the designed controllers. Finally, the presented tracking controllers with quantization mechanism are validated by comparative simulations.

Brief Paper - State-feedback control of discrete-time switched positive linear systems

Abstract: This brief concerns the stabilisation problem for a class of slowly switched positive linear systems in discrete-time context The average dwell-time switching associated with the corresponding state-feedback controllers is designed to stabilise the closed-loop systems and keep the states non-negative The developed conditions are formulated as linear matrix inequalities, which can be directly used for controller synthesis and switching designing Finally, a numerical example is presented to show the feasibility of the obtained theoretical results

The sector bound approach to quantized feedback control | NOVA. The University of Newcastle's Digital Repository

Abstract: This paper studies a number of quantized feedback design problems for linear systems. We consider the case where quantizers are static (memoryless). The common aim of these design problems is to stabilize the given system or to achieve certain performance with the coarsest quantization density. Our main discovery is that the classical sector bound approach is nonconservative for studying these design problems. Consequently, we are able to convert many quantized feedback design problems to well-known robust control problems with sector bound uncertainties. In particular, we derive the coarsest quantization densities for stabilization for multiple-input-multiple-output systems in both state feedback and output feedback cases; and we also derive conditions for quantized feedback control for quadratic cost and H/sub /spl infin// performances.

Secure State Estimation and Control of Cyber-Physical Systems: A Survey

Abstract: Cyber-physical systems (CPSs) empower the integration of physical processes and cyber infrastructure with the aid of ubiquitous computation resources and communication capabilities. CPSs have permeated modern society and found extensive applications in a wide variety of areas, including energy, transportation, advanced manufacturing, and medical health. The security of CPSs against cyberattacks has been regarded as a long-standing concern. However, CPSs suffer from extendable vulnerabilities that are beyond classical networked systems due to the tight integration of cyber and physical components. Sophisticated and malicious cyberattacks continue to emerge to adversely impact CPS operation, resulting in performance degradation, service interruption, and system failure. Secure state estimation and control technologies play a vital role in warranting reliable monitoring and operation of safety-critical CPSs. This article provides a review of the state-of-the-art results for secure state estimation and control of CPSs. Specifically, the latest development of secure state estimation is summarized in light of different performance indicators and defense strategies. Then, the recent results on secure control are discussed and classified into three categories: 1) centralized secure control; 2) distributed secure control; and 3) resource-aware secure control. Furthermore, two specific application examples of water supply distribution systems and wide-area power systems are presented to demonstrate the applicability of secure state estimation and control approaches. Finally, several challenging issues are discussed to direct future research.

$\mathcal {H}_{\infty }$ Synchronization for Fuzzy Markov Jump Chaotic Systems With Piecewise-Constant Transition Probabilities Subject to PDT Switching Rule

Abstract: This article investigates the nonfragile $\mathcal {H}_{\infty }$ synchronization issue for a class of discrete-time Takagi–Sugeno (T–S) fuzzy Markov jump systems. With regard to the T–S fuzzy model, a novel processing method based on the matrix transformation is introduced to deal with the double summation inequality containing fuzzy weighting functions, which may be beneficial to obtain conditions with less conservatism. In view of the fact that the uncertainties may occur randomly in the execution of the actuator, a nonfragile controller design scheme is presented by virtue of the Bernoulli distributed white sequence. The main novelty of this article lies in that the transition probabilities of the Markov chain are considered to be piecewise time-varying, and whose variation characteristics are described by the persistent dwell-time switching regularity. Then, based on the Lyapunov stability theory, it is concluded that the resulting synchronization error system is mean-square exponentially stable with a prescribed $\mathcal {H}_{\infty }$ performance in the presence of actuator gain variations. Finally, an illustrative example about Lorenz chaotic systems is provided to show the effectiveness of the established results.

Observer-Based Adaptive SMC for Nonlinear Uncertain Singular Semi-Markov Jump Systems With Applications to DC Motor

Abstract: This paper deals with the observer-based adaptive sliding mode control (OBASMC) design for nonlinear uncertain singular semi-Markov jump systems. The system satisfies the singular property and follows a stochastic semi-Markov process related to Weibull distribution. Due to the influence of sensor factors in practical systems, the state vectors are not always known. Additionally, the unavoidable measurement errors in the actual system always lead to the model uncertainties and the unknown nonlinearity. Our attention is to design the OBASMC law for such a class of complex systems. First, by the use of the Lyapunov–Krasovskii functional, sufficient conditions are given, such that the sliding mode dynamics are stochastically admissible. Then, the OBASMC law is proposed to guarantee the reachability in a finite-time region. Finally, the practical system about dc motor model is given to verify the validity.

Distributed non-fragile set-membership filtering for nonlinear systems under fading channels and bias injection attacks

Abstract: In this paper, the secure distributed set-membership filtering problem is investigated for general nonlinear system over wireless sensor networks. For the purpose of getting close to practical wire...