Huaicheng Yan

Bio: Huaicheng Yan is an academic researcher from East China University of Science and Technology. The author has contributed to research in topics: Control theory & Filter (signal processing). The author has an hindex of 11, co-authored 21 publications receiving 842 citations. Previous affiliations of Huaicheng Yan include East China Jiaotong University.

Finite-Time Event-Triggered $\mathcal{H}_{\infty }$ Control for T–S Fuzzy Markov Jump Systems

Abstract: This paper investigates the finite-time event-triggered $\mathcal{H}_{\infty }$ control problem for Takagi–Sugeno Markov jump fuzzy systems. Because of the sampling behaviors and the effect of network environment, the premise variables considered in this paper are subject to asynchronous constraints. The aim of this paper is to synthesize a controller via an event-triggered communication scheme such that not only the resulting closed-loop system is finite-time bounded and satisfies a prescribed $\mathcal{H}_{\infty }$ performance level, but also the communication burden is reduced. First, a sufficient condition is established for the finite-time bounded $\mathcal{H} _{\infty }$ performance analysis of the closed-loop fuzzy system with fully considering the asynchronous premises. Then, based on the derived condition, the method of the desired controller design is presented. Two illustrative examples are finally presented to demonstrate the practicability and efficacy of the proposed method.

Adaptive Event-Triggered Fuzzy Control for Uncertain Active Suspension Systems

Abstract: This paper studies the adaptive event-triggered fuzzy control issue for active vehicle suspension systems with uncertainties Takagi–Sugeno fuzzy model is applied for considered systems In the process of designing controller, a crucial problem, actuator failure, is taken into account An adaptive event-triggered mechanism is adopted to economize limited communication resource Compared with the traditional event-triggered scheme with a constant threshold, the adaptive event-triggered mechanism can save more resource effectively Based on Lyapunov stability theory, an adaptive event-triggered fuzzy control approach is proposed to guarantee the desired performance Meanwhile, suspension constrained requirements are also ensured Finally, simulation examples are presented to testify the feasibility of the approach proposed in this paper

Quantized Control Design for Impulsive Fuzzy Networked Systems

Abstract: In this paper, a continuous-time Takagi-Sugeno (T-S) fuzzy system with impulsive effects that are controlled through network is investigated. Network signal-transmission delays and signal-quantization effects are simultaneously considered. The network is with two time-varying additive delays and limited capacity. First, a quantized output-feedback networked control system (NCS) model is established to describe the impulsive NCSs through a channel with limited capacity. Then, based on the Lyapunov-Krasovskii functional approach and a parallel-distributed compensation scheme, a delay-dependent stabilization approach is developed for the impulsive NCSs, which guarantees that the closed-loop system is asymptotically stable. Finally, a simulation example is given to illustrate the effectiveness of the proposed method.

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.

An Overview and Deep Investigation on Sampled-Data-Based Event-Triggered Control and Filtering for Networked Systems

Abstract: This paper provides an overview and makes a deep investigation on sampled-data-based event-triggered control and filtering for networked systems. Compared with some existing event-triggered and self-triggered schemes, a sampled-data-based event-triggered scheme can ensure a positive minimum inter-event time and make it possible to jointly design suitable feedback controllers and event-triggered threshold parameters. Thus, more attention has been paid to the sampled-data-based event-triggered scheme. A deep investigation is first made on the sampled-data-based event-triggered scheme. Then, recent results on sampled-data-based event-triggered state feedback control, dynamic output feedback control, $H_\infty$ filtering for networked systems are surveyed and analyzed. An overview on sampled-data-based event-triggered consensus for distributed multiagent systems is given. Finally, some challenging issues are addressed to direct the future research.

Distributed Formation Control of Networked Multi-Agent Systems Using a Dynamic Event-Triggered Communication Mechanism

Abstract: This paper addresses the distributed formation control problem of a networked multi-agent system (MAS) subject to limited communication resources. First, a dynamic event-triggered communication mechanism (DECM) is developed to schedule inter-agent communication such that some unnecessary data exchanges among agents can be reduced so as to achieve better resource efficiency. Different from most of the existing event-triggered communication mechanisms, wherein threshold parameters are fixed all the time, the threshold parameter in the developed event triggering condition is dynamically adjustable in accordance with a dynamic rule. It is numerically shown that the proposed DECM can achieve a better tradeoff between reducing inter-agent communication frequency and preserving an expected formation than some existing ones. Second, an event-triggered formation protocol is delicately proposed by using only locally triggered sampled data in a distributed manner. Based on the formation protocol, it is shown that the state formation control problem is cast into an asymptotic stability problem of a reduced-order closed-loop system. Then, criteria for designing desired formation protocol and communication mechanism are derived. Finally, the effectiveness and advantages of the proposed approach are demonstrated through a comparative study in multirobot formation control.

Analysis and synthesis of networked control systems: A survey of recent advances and challenges.

Abstract: A networked control system (NCS) is a control system which involves a communication network. In NCSs, the continuous-time measurement is usually sampled and quantized before transmission. Then, the measurement is transmitted to the remote controller via the communication channel, during which the signal may be delayed, lost or even sometimes not allowed for transmission due to the communication or energy constraints. In recent years, the modeling, analysis and synthesis of networked control systems (NCSs) have received great attention, which leads to a large number of publications. This paper attempts to present an overview of recent advances and unify them in a framework of network-induced issues such as signal sampling, data quantization, communication delay, packet dropouts, medium access constraints, channel fading and power constraint, and present respective solution approaches to each of these issues. We draw some conclusions and highlight future research directions in end.

Recent Advances on Fuzzy-Model-Based Nonlinear Networked Control Systems: A Survey

Abstract: In recent years, the analysis and synthesis of fuzzy-model-based nonlinear networked control systems (NCSs) have received increasing attention from both scientific and industrial communities, and a number of significant results have been proposed. This paper gives a review on recent advances on the analysis and design of fuzzy-model-based nonlinear NCSs with various network-induced limitations such as packet dropouts, time delays, and signal quantization. With these network-induced constraints, the developments on various control and filtering design issues are surveyed in details, and some essential technical difficulties are mentioned. Then, some latest results on event-triggered control and filtering design of fuzzy-model-based nonlinear NCSs are also summarized. Finally, some conclusions are drawn and several potential future research topics are highlighted.