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Zuxin Li,Yunliang Jiang,Wanliang Wang 제어·로봇·시스템학회 2009 International Journal of Control, Automation, and Vol.7 No.2
There is an unavoidable tradeoff between the control performance and the quality of service in networked control systems with resource constraints. To address the impact of network resources availability on requirement of bandwidth (RoB) and quality of control (QoC), an intelligent control ap-proach to dynamic bandwidth management, namely fuzzy bandwidth management, is proposed based on fuzzy logic control technique. In order to guarantee the system’s stability, the lower and upper bound of the assignable bandwidth are evaluated in terms of linear matrix inequalities and the resource constraints, respectively. In addition, the normalizable criterions of QoC and RoB are also defined, which can estimate the performance of the whole networked control systems. Preliminary simulations are carried out to highlight the merits of the proposed approach. It is argued that the proposed approach can save significant bandwidth and simultaneously improve overall control performance in comparison with the fixed bandwidth allocation and optimal bandwidth allocation.
Resilient Filtering for Delayed Markov Jump Neural Networks via Event-triggered Strategy
Weifeng Xia,Yongmin Li,Zuxin Li,Shuxin Du,Bo Li,Wenbin Chen 제어·로봇·시스템학회 2021 International Journal of Control, Automation, and Vol.19 No.10
This paper deals with the event triggered filtering problem for a class of delayed discrete-time Markov jump neural networks, where a resilient filter with parameter uncertainties is adopted. The aim of this paper is to design a suitable filter which ensures that the filtering error system is stochastically stable and satisfies a prescribed mixed passivity and H∞ performance. Sufficient conditions for solvability of such a problem are developed. Basedon the obtained conditions, an explicit expression of the desired resilient filter is proposed. Finally, an example is presented to show the usefulness of the proposed scheme.
Huiying Chen,Weifeng Xia,Zheng-Guang Wu,Zuxin Li 제어·로봇·시스템학회 2024 International Journal of Control, Automation, and Vol.22 No.3
This article is primarily concerned with the collaborative optimization design issue of the asynchronousfilter and the event-based trigger for discrete-time nonlinear Markov jump systems modeled by the Takagi-Sugenofuzzy model. In the network environment, an event-based trigger is introduced to reduce communication consumption while the hidden Markov model approach is utilized to express the asynchronous phenomenon between thefilter and the plant. Based on this framework, using the parameter-dependent Lyapunov function and matrix inequality techniques, the H∞ and L2 −L∞ asynchronous filter design schemes are developed such that the resultingfiltering error dynamic system can be randomly mean square stable and satisfy a preset noise attenuation performance. Furthermore, an iterative optimization algorithm is presented to collaboratively solve the optimal parametersof the filter and the trigger. At last, a tunnel-diode circuit is employed to verify the validity of our design schemes.