详细信息
Adaptive output feedback quantised tracking control for stochastic nonstrict-feedback nonlinear systems with input saturation ( SCI-EXPANDED收录 EI收录)
文献类型:期刊文献
英文题名:Adaptive output feedback quantised tracking control for stochastic nonstrict-feedback nonlinear systems with input saturation
作者:Yang, Yekai[1];Yu, Zhaoxu[1];Li, Shugang[2]
机构:[1]East China Univ Sci & Technol, Minist Educ, Key Lab Adv Control & Optimizat Chem Proc, Shanghai, Peoples R China;[2]Shanghai Univ, Dept Informat Management, Shanghai, Peoples R China
年份:2018
卷号:49
期号:15
起止页码:3130
外文期刊名:INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE
收录:;EI(收录号:20184305971467);WOS:【SCI-EXPANDED(收录号:WOS:000451416400010)】;
基金:This work is partially supported by the Chinese National Natural Science Foundation [grant number 71871135], and Shanghai Pujiang Program [grant number 15PJC049], and Fundamental Research Funds for the Central Universities [grant numbers 222201714055 and 222201717006].
语种:英文
外文关键词:Stochastic nonlinear systems; adaptive control; output feedback; quantisation; input saturation
摘要:This paper is concerned with the problem of adaptive output feedback quantised tracking control for a class of stochastic nonstrict-feedback nonlinear systems with asymmetric input saturation. Especially, both input and output signals are quantised by two sector-bounded quantisers. In order to solve the technical difficulties originating from asymmetric saturation nonlinearities and sector-bounded quantisation errors, some special technique, approximation-based methods and Gaussian error function-based continuous differentiable model are exploited. Meanwhile, an observer including the quantised input and output signals is designed to estimate the states. Then, a novel output feedback adaptive quantised control scheme is proposed to ensure that all signals in the closed-loop system are 4-moment (2-moment) semi-globally uniformly ultimately bounded while the output signal follows a desired reference signal. Finally, the effectiveness and applicability of the design methodology is illustrated with two simulation examples.
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