Active Fault Diagnosis for LPV Systems Based on Constrained Zonotopes

• 成果类型: Article
• 署名作者: Zhang, Zhao; He, Xiao; Zhou, Donghua
• 署名单位: Peking University; Tsinghua University; Shandong University of Science & Technology
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2024.3401271
• 发表日期: 2024
• 页码: 7893-7900
• 关键词: Fault diagnosis; programming; uncertainty; Generators; complex systems; automation; Real-time systems; Active fault diagnosis (AFD); auxiliary input; constrained zonotope (CZ); online updating; set-valued observer

摘要

This article investigates the active fault diagnosis problem for linear parameter-varying systems with bounded disturbances. Constrained zonotopes (CZs) are utilized to model the range of the system disturbances, in which case, the system state and output can also be described by CZs. Different models are employed to describe different fault modes. The basic idea of the proposed method is to design proper auxiliary input and inject it into the system to ensure that the system's output is only within the theoretical output set of a certain system mode. The auxiliary input, which can guarantee fault diagnosis and has minimum energy, is calculated by solving a bilevel programming problem. By replacing the inner programming problem with its necessary and sufficient conditions, the original bilevel programming problem can be transformed into a single-level programming problem. Through variable substitution, linear relaxation, and complementary condition transformation, the obtained single-level programming problem can be transformed into a mixed-integer quadratic programming problem. Furthermore, in order to reduce conservatism, an online updating scheme is proposed. The auxiliary input is redesigned at every moment and injected into the system by a selection mechanism. A numerical example is presented to demonstrate the effectiveness of the proposed approach.