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Output-feedback Robust Tracking Control of Uncertain Systems via Adaptive Learning
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Journal Article
Output-feedback Robust Tracking Control of Uncertain Systems via Adaptive Learning
2023
Overview
This paper presents an adaptive learning method to achieve the output-feedback robust tracking control of systems with uncertain dynamics, which uses the techniques developed for optimal control. An augmented system is first constructed using the system state and desired output trajectory. Then, the robust tracking control problem is equivalent to the optimal tracking control problem with an appropriate cost function. To design the output-feedback optimal tracking control, an output tracking algebraic Riccati equation (OTARE) is then constructed, which can be used in the online learning process. To obtain the solution of the derived OTARE, an online adaptive learning method is proposed, where the input gain matrix is removed. In this learning algorithm, only the system output information is required and the observers widely used in the output-feedback optimal control design are removed. Simulations based on the power system are given to test the proposed method.
Publisher
Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers,Springer Nature B.V,제어·로봇·시스템학회
Subject
