Bounded Integral Controller With Limited Control Power for Nonlinear Multiple-Input Multiple-Output Systems

• Published in: IEEE transactions on control systems technology Vol. 29; no. 3; pp. 1348 - 1355
• Main Authors: Wang, Yeqin, Ren, Beibei, Zhong, Qing-Chang, Dai, Jiguo
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.05.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Bounded integral controller (BIC); Constraints; Control systems; Controllers; D C motors; DC motors; Feedback control; Integral equations; Integrals; limited control power; MIMO (control systems); MIMO communication; multiple-input multiple-output (MIMO); Nonlinear control; Permanent magnets; sum-of-squares constraint; Synchronous motors; time-invariant input weights; time-varying input weights; Time-varying systems; Tracking control; Tracking errors; Voltage control
• ISSN: 1063-6536; 1558-0865
• DOI: 10.1109/TCST.2020.2989691

In this brief, a bounded integral controller (BIC) with limited control power is proposed for a class of nonlinear multiple-input multiple-output (MIMO) systems. The sum-of-squares constraint on the control inputs with time-varying weights is studied and handled through the BIC design, which guarantees that both the control inputs and an auxiliary time-varying variable are dynamically constrained on a designed control circle. The BIC inherits the properties of the traditional integral controller to eliminate tracking errors and achieve disturbance rejections. Even under time-varying input weights, the BIC guarantees limited control power independently of both plant information and system states. The input-to-state (practical) stability of the closed-loop system is established. To demonstrate the effectiveness of the proposed method, experimental validations are conducted for two systems: a system with multiple dc motors subject to a power limit with time-varying input weights and a permanent magnet synchronous motor system subject to a voltage limit with time-invariant input weights.