文献类型：期刊文献

英文题名：Partial model-free sliding mode control design for a class of disturbed systems via computational learning algorithm

作者：Zhou, Jia-Le[1];Huang, Long-Yang[2];Song, Jun[1];Wang, Hui-Feng[1]

机构：[1]East China Univ Sci & Technol, Minist Educ, Key Lab Smart Mfg Energy Chem Proc, Shanghai 200237, Peoples R China;[2]China Univ Min & Technol, Sch Informat & Control Engn, Xuzhou 221116, Jiangsu, Peoples R China

年份：2023

卷号：44

期号：3

起止页码：1278

外文期刊名：OPTIMAL CONTROL APPLICATIONS & METHODS

收录：;EI(收录号：20213410804809);WOS:【SCI-EXPANDED(收录号:WOS:000687120400001)】；

基金：National Natural Science Foundation of China, Grant/Award Numbers: 61906068, 61903143; National Key R&D Program of China, Grant/Award Number: 2018YFC1803306

语种：英文

外文关键词：sliding mode control; model-free control; policy iteration algorithm; disturbed systems

摘要：In this article, a partial model-free sliding mode control (SMC) strategy is proposed for a class of disturbed systems. A partial model-free SMC law is designed to attenuate the matched external disturbances by just employing partial dynamics information. A complete model-free policy iteration algorithm is integrated to the designed SMC scheme such that the optimal control performance of the disturbed system is achieved. The implementation of the proposed partial model-free SMC strategy is based on a computational learning algorithm, which involves date collection, policy iteration, and optimal control phases. The feasibility of the proposed SMC strategy in data collection phase and optimal control phase are analyzed, respectively. Finally, a numerical example is employed to verify the effectiveness of the proposed SMC strategy.