Journal
NONLINEAR DYNAMICS
Volume 105, Issue 4, Pages 3299-3321Publisher
SPRINGER
DOI: 10.1007/s11071-021-06805-5
Keywords
High order nonlinear systems; Tracking control; Event-trigger; Observer; Neural network; Backstepping
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Funding
- National Natural Science Foundation of China [61803040]
- key research and development plan of Shaanxi Province [2019GY-218]
- China Postdoctoral Science Foundation [2018M643556]
- Fundamental Research Funds for the Central University of China [300102320203, 300102320720, 300102328403]
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The study investigates an event-triggered tracking control method for large-scale high order nonlinear uncertain systems, utilizing a neural observer to estimate unmeasurable states and reducing communication burden through event-trigger strategy, eventually designing an observer-based adaptive event-triggered controller to achieve output tracking.
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.
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