Command filter based adaptive DSC of uncertain stochastic nonlinear systems with input delay and state constraints. Issue 17 (November 2022)

• Record Type: Journal Article
• Authors: Xia, Xiaonan; Pan, Jianwen; Zhang, Tianping; Fang, Yu
• Is Part Of: Journal of the Franklin Institute. Volume 359:Issue 17(2022)
• Page Start: 9492
• Page End: 9521
• Publication Date: 2022-11
• Subjects: Science -- Periodicals; Technology -- Periodicals; Patents -- United States -- Periodicals; 505
• DOI: 10.1016/j.jfranklin.2022.10.004
• Languages: English
• ISSNs: 0016-0032

Abstract

Abstract: In this paper, a command filter based dynamic surface control (DSC) is developed for stochastic nonlinear systems with input delay, stochastic unmodeled dynamics and full state constraints. An error compensation system is designed to constrain the filtering error caused by the first-order filter in the traditional dynamic surface design. On this basis, the stability proof of DSC for stochastic nonlinear systems based on command filter is proposed. The definition of state constraints in probability is presented, and the problem of stochastic full state constraints is solved by constructing a group of coordinate transformations with nonlinear mappings. The Pade approximation is adopted to deal with input delay. The stochastic unmodeled dynamics is considered, which is processed by utilizing the property of stochastic input-to-state stability (SISS) and changing supply function. All the signals of the system are proved to be semi-globally uniformly ultimately bounded (SGUUB) in probability, and the full state constraints are not violated. The two simulation examples also verify the effectiveness of the proposed adaptive DSC scheme.