Controller Reduction for Nonlinear Systems by Generalized Differential Balancing

• 成果类型: Article
• 署名作者: Kawano, Yu
• 署名单位: Hiroshima University
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2021.3124980
• 发表日期: 2022
• 页码: 5856-5871
• 关键词: Balancing; contraction; controller reduction; Model reduction; Nonlinear systems

摘要

In this article, we aim at developing computationally tractable methods for nonlinear model/controller reduction. Recently, model reduction by generalized differential (GD) balancing has been proposed for nonlinear systems with constant input-vector fields and linear output functions. First, we study incremental properties in the GD balancing framework. Next, based on these analyses, we provide GD linear quadratic Gaussian (LQG) balancing and GD H-infinity-balancing as controller reduction methods for nonlinear systems by focusing on linear feedback and observer gains. Especially for GD H-infinity-balancing, we clarify when the closed-loop system consisting of the full-order system and a reduced-order controller is exponentially stable. All provided methods for controller reduction can be relaxed to linear matrix inequalities (LMIs).