Notes on Data-Driven Output-Feedback Control of Linear MIMO Systems

• 成果类型: Article
• 署名作者: Alsalti, Mohammad; Lopez, Victor G.; Muller, Matthias A.
• 署名单位: Leibniz University Hannover
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2025.3553073
• 发表日期: 2025
• 页码: 6143-6150
• 关键词: Linear systems; vectors; trajectory; observability; MIMO; Complexity theory; training; Sufficient conditions; reviews; indexes; Data-driven control; multivariable linear systems; non-minimal state representations

摘要

Recent works have approached the data-driven design of dynamic output-feedback controllers for discrete-time linear time-invariant (LTI) systems by constructing nonminimal state vectors composed of past inputs and outputs. Depending on the system's complexity (order n, lag & ell; and number of outputs p), it was observed in several works that such an approach presents significant limitations. In particular, many works require to restrict the class of LTI systems to those satisfying the relation p & ell; =n. In this note, we show how to address the general multi-input multi-output (MIMO) case (for which p & ell; >= n in general) by constructing an alternative nonminimal state vector from data. Different from the existing literature, our method guarantees the satisfaction of certain rank conditions when the system is persistently excited, thereby facilitating the direct data-driven dynamic output-feedback control of MIMO systems by applying methods that were originally developed for the input-state data setting.