Open AccessData‐driven sliding mode tracking control for unknown Markovian jump non‐linear systems
Author(s) -
Niu Xiaoru,
Gao Xianwen,
Weng Yongpeng
Publication year - 2017
Publication title -
iet control theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.059
H-Index - 108
eISSN - 1751-8652
pISSN - 1751-8644
DOI - 10.1049/iet-cta.2017.0321
Subject(s) - control theory (sociology) , reachability , mode (computer interface) , tracking (education) , sliding mode control , linear matrix inequality , stability theory , linear system , jump , computer science , mathematics , markov process , control (management) , nonlinear system , mathematical optimization , algorithm , physics , mathematical analysis , artificial intelligence , psychology , pedagogy , statistics , quantum mechanics , operating system
This study aims to investigate the sliding mode control (SMC) problem for non‐linear Markovian jump systems (MJSs) in which the transition probability could only be partly obtained and the system models and orders are unknown. Firstly, a mode‐dependent data‐driven sliding surface is established and by using the high‐order SMC strategy, a data‐based SMC law is proposed to guarantee the reachability of the SMC system. With the linear matrix inequalities technique, the tracking error of the closed‐loop non‐linear MJS is demonstrated to be asymptotically stochastically stable. Furthermore, a simulation experiment is carried out to prove the effectiveness of this method.