4.7 Article

Robust tracking composite nonlinear feedback controller design for time-delay uncertain systems in the presence of input saturation

期刊

ISA TRANSACTIONS
卷 129, 期 -, 页码 88-99

出版社

ELSEVIER SCIENCE INC
DOI: 10.1016/j.isatra.2022.02.029

关键词

Robust control; Composite nonlinear feedback; Input saturation; Linear matrix inequality; Time -delay system

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This study investigates a robust control technique for the reference tracking of uncertain time-delayed systems in the presence of actuator saturation. The tracking goal is achieved through suitable design of the composite nonlinear feedback (CNF) controller, considering the control complexities, input limitations, time-varying delay, uncertainty, and external disturbance. A Lyapunov-based procedure is used to determine the control law, and the parameters of the CNF input are derived using a solution of a linear matrix inequality (LMI) problem. The numerical implementation of the proposed tracking idea in two uncertain control systems demonstrates the efficiency of the suggested control procedure compared to existing CNF approaches.
In this study, a robust control technique is investigated for the reference tracking of uncertain time -delayed systems in the existence of the actuator saturation. Due to emerging of some control complexities, as well as the input limitations, time-varying delay, uncertainty, and external disturbance, such a tracking goal would be realized through suitable design of the composite nonlinear feedback (CNF) controller. Thus, considering the mentioned limitations, a Lyapunov-based procedure is used to determine the control law. Then, the parameters of the CNF input are derived by using the solution of a linear matrix inequality (LMI) problem. The planned tracking idea is numerically implemented in two uncertain control systems. Some performance characteristics (i.e., the tracking error, boundedness, and transient responses) are compared with similar ones. Accordingly, the simulations illustrate the efficiency of the suggested control procedure over the existing CNF approaches.(c) 2022 ISA. Published by Elsevier Ltd. All rights reserved.

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