Yiwen Qi , Caibin Yao , Choon Ki Ahn , Dong Shen , Ziyu Qu
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引用次数: 0
Abstract
Iterative learning control (ILC) refers to the optimal control of repetitive systems. It is a thorny problem that ILC is maliciously terminated during any single run, resulting in different running lengths. In addition, reinforcement learning is an intelligent approach to finding the optimal controller gains for system performance improvement. In this paper, dual variable ILC (DV-ILC) for switched systems with arbitrary switching rules is examined. First, for variable iteration run lengths induced by security issues, an iteration experience succession strategy (IESS) is proposed, and the minimum number of iterations is presented. Second, a reinforcement learning optimizer is adopted to continuously regulate variable controller gains. The controller is designed in the form of an open-loop P-type and a closed-loop PD-type working together, meaning that both current and historical information can be fully utilized. In addition, the tracking error convergence in the iteration domain is proved. Finally, the simulations prove the effectiveness of the proposed method.
期刊介绍:
Automatica is a leading archival publication in the field of systems and control. The field encompasses today a broad set of areas and topics, and is thriving not only within itself but also in terms of its impact on other fields, such as communications, computers, biology, energy and economics. Since its inception in 1963, Automatica has kept abreast with the evolution of the field over the years, and has emerged as a leading publication driving the trends in the field.
After being founded in 1963, Automatica became a journal of the International Federation of Automatic Control (IFAC) in 1969. It features a characteristic blend of theoretical and applied papers of archival, lasting value, reporting cutting edge research results by authors across the globe. It features articles in distinct categories, including regular, brief and survey papers, technical communiqués, correspondence items, as well as reviews on published books of interest to the readership. It occasionally publishes special issues on emerging new topics or established mature topics of interest to a broad audience.
Automatica solicits original high-quality contributions in all the categories listed above, and in all areas of systems and control interpreted in a broad sense and evolving constantly. They may be submitted directly to a subject editor or to the Editor-in-Chief if not sure about the subject area. Editorial procedures in place assure careful, fair, and prompt handling of all submitted articles. Accepted papers appear in the journal in the shortest time feasible given production time constraints.