Dongyan Chen

Bio: Dongyan Chen is an academic researcher from Harbin University of Science and Technology. The author has contributed to research in topics: Estimator & Nonlinear system. The author has an hindex of 12, co-authored 75 publications receiving 594 citations. Previous affiliations of Dongyan Chen include Harbin University.

State estimation for a class of discrete nonlinear systems with randomly occurring uncertainties and distributed sensor delays

Abstract: In this paper, the state estimation problem is investigated for a class of discrete nonlinear systems with randomly occurring uncertainties and distributed sensor delays. The norm-bounded uncertainties enter into the system in a randomly way, and such randomly occurring uncertainties (ROUs) obey certain Bernoulli distributed white noise sequence with known conditional probability. By constructing a new Lyapunov–Krasovskii functional, sufficient conditions are proposed to guarantee the convergence of the estimation error for all discrete time-varying delays, ROUs and distributed sensor delays. Subsequently, the explicit form of the estimator parameter is derived by solving two linear matrix inequalities (LMIs) which can be easily tested by using standard numerical software. Finally, a simulation example is given to illustrate the feasibility and effectiveness of the proposed estimation scheme.

Design of Sliding-Mode-Based Control for Nonlinear Systems With Mixed-Delays and Packet Losses Under Uncertain Missing Probability

Abstract: This paper is coped with the robust sliding-mode-based control problem for a class of discrete nonlinear systems in the presence of mixed-delays and packet losses with uncertain missing probability. Both the time-varying state delays and the infinite distributed state delays are considered. Also, the data packet losses are modeled by a Bernoulli distributed stochastic variable with uncertain missing probability and an update rule is employed to characterize the signal transmitted to controller side. A sliding function is first constructed and the desired stochastic mean-square stability of sliding motion is ensured by providing a sufficient condition based on the matrix inequality technique. Besides, a new discrete SMC strategy is designed to guarantee that the state trajectories are driven onto the bounded band of predesigned sliding surface and maintain them therein during subsequent time. Finally, the effectiveness of the developed sliding-mode control technique is verified by some simulations with comparative results.

A recursive approach to non-fragile filtering for networked systems with stochastic uncertainties and incomplete measurements

Abstract: In this paper, the non-fragile recursive filtering problem is investigated for a class of networked time-varying nonlinear systems with stochastic uncertainties and incomplete measurements. By employing a stochastic Kronecker delta function, the phenomena of the incomplete measurements are characterized in a unified framework which contain the randomly occurring signal quantization and the missing measurements. Based on the available probability information of the incomplete measurements, a new filtering compensation scheme is proposed to ensure that, for all stochastic uncertainties, incomplete measurements and stochastic perturbations of the filter gain, an upper bound of the filtering error covariance is guaranteed and such an upper bound is minimized by properly designing the filter gain at each sampling instant. It is shown that the desired filter gain can be obtained by solving two Riccati-like difference equations, and the proposed filtering algorithm is of a recursive form which is suitable for online applications. Finally, an illustrative example is provided to demonstrate the feasibility of the developed filtering approach.

Non-fragile consensus control for nonlinear multi-agent systems with uniform quantizations and deception attacks via output feedback approach

Abstract: In this paper, we handle the non-fragile consensus control problem for a class of discrete time-varying nonlinear multi-agent systems with uniform quantization and randomly occurring deception attacks. The quantization error is described by a noise distributed uniformly in certain interval, and the phenomenon of the randomly occurring deception attacks is depicted by the Bernoulli distributed random variables with known probabilities. Here, the measurement output utilized in the controller side is not only from a single agent itself, but also from its adjacent agents, where the corresponding transmissions are carried out under a given topology. In particular, the controller gain perturbations are characterized by the multiplicative noises. We focus on the design of non-fragile time-varying output feedback controller such that, when the randomly occurring deception attacks, uniform quantization effects as well as controller gain perturbations exist simultaneously, and the desired consensus performance is guaranteed by designing the controller parameters. Accordingly, a sufficient condition is derived to ensure the existence of the desired control scheme, where the feasibility of conducted problem can be tested by solving a set of matrix inequalities. Moreover, the optimal consensus performance is addressed by employing an optimization problem. Finally, we utilize the simulations to illustrate the feasibility of the proposed output feedback control strategy.

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.

Observer-Based Event-Triggering Consensus Control for Multiagent Systems With Lossy Sensors and Cyber-Attacks

Abstract: In this paper, the observer-based event-triggering consensus control problem is investigated for a class of discrete-time multiagent systems with lossy sensors and cyber-attacks. A novel distributed observer is proposed to estimate the relative full states and the estimated states are then used in the feedback protocol in order to achieve the overall consensus. An event-triggered mechanism with state-independent threshold is adopted to update the control input signals so as to reduce unnecessary data communications. The success ratio of the launched attacks is taken into account to reflect the probabilistic failures of the attacks passing through the protection devices subject to limited resources and network fluctuations. The purpose of the address problem is to design an observer-based distributed controller such that the closed-loop multiagent system achieves the prescribed consensus in spite of the lossy sensors and cyber-attacks. By making use of eigenvalues and eigenvectors of the Laplacian matrix, the closed-loop system is transformed into an easy-to-analyze setting and then a sufficient condition is derived to guarantee the desired consensus. Furthermore, the controller gain is obtained in terms of the solution to certain matrix inequality which is independent of the number of agents. An algorithm is provided to optimize the consensus bound. Finally, a simulation example is utilized to illustrate the usefulness of the proposed controller design scheme.