Observer-based event-triggered tracking control for large-scale high order nonlinear uncertain systems
| Autor: | Xingwen Chen, Xiangmo Zhao, Jiacheng Song, Panpan Yang |
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| Rok vydání: | 2021 |
| Předmět: |
Observer (quantum physics)
Computer science Applied Mathematics Mechanical Engineering Stability (learning theory) Aerospace Engineering Ocean Engineering Tracking (particle physics) Nonlinear system Control and Systems Engineering Control theory Backstepping Trajectory Electrical and Electronic Engineering Actuator |
| Zdroj: | Nonlinear Dynamics. 105:3299-3321 |
| ISSN: | 1573-269X 0924-090X |
| Popis: | The event-triggered tracking control for large-scale high order nonlinear uncertain systems, whose state information is immeasurable, is investigated via an observer-based approach. Firstly, a neural observer is designed to estimate the unmeasurable state information of high order nonlinear systems. Then, a relative threshold event-triggered strategy is proposed to reduce the communication burden between the actuator and the controller. On this basis, a novel observer-based adaptive event-triggered controller is designed to achieve the output tracking of the reference trajectory via the backstepping technique. Theoretical proof shows that the proposed controller guarantees the stability of the closed-loop systems and the Zeno-behavior can be excluded. Finally, some simulation examples are performed to illustrate the effectiveness of the proposed method. |
| Databáze: | OpenAIRE |
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