Event-Triggered Robust Constrained Control of Uncertain Nonlinear Systems With Input Saturation Based on Self-Learning Disturbance Observer

In this article, an adaptive event-triggered constrained control strategy is proposed for uncertain nonlinear systems with input constraints by using reinforcement learning (RL) technology and disturbance observer (DO). By constructing an actor-critic neural network (NN) framework, the unknown uncer...

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Bibliographic Details
Published in:IEEE transactions on instrumentation and measurement 2024, Vol.73, p.1-15
Main Authors: Shao, Shuyi, Yan, Xiaohui, Chen, Mou, An, Zhengcai
Format: Article
Language:English
Subjects:
Adaptive control
Artificial neural networks
Closed loops
Compensation
Constraints
Control systems
Distance learning
Disturbance observer (DO)
Disturbance observers
Event triggered control
event-triggered control (ETC)
Feedback control
input constraints
Machine learning
Neural networks
Nonlinear control
Nonlinear systems
Nonlinearity
Process control
Reinforcement learning
reinforcement learning (RL)
Robust control
Systems stability
uncertain nonlinear system
Uncertain systems
Uncertainty
Unmanned aerial vehicles
Unmanned helicopters
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Summary:In this article, an adaptive event-triggered constrained control strategy is proposed for uncertain nonlinear systems with input constraints by using reinforcement learning (RL) technology and disturbance observer (DO). By constructing an actor-critic neural network (NN) framework, the unknown uncertainties can be tackled by online learning and more accurate compensation. The actor-NN is adopted for generating actions (regarded as compensation signals), and the critic-NN is employed to evaluate the performed actions (regarded as to monitor and assess the actor-NN performance, including the control performance). Moreover, a self-learning DO with learning ability is designed to estimate the external disturbance. On the basis of the backstepping control technology, the event-triggered control (ETC) method and the smooth approximation of input saturation nonlinearity, an improved event-triggered constrained control strategy is presented using RL technique, and the rigorous theoretical proofs of the closed-loop system stability and the avoidance of Zeno behavior are presented. The application for the quadrotor unmanned aerial vehicle (UAV) validates the effectiveness of the developed ETC approach.
ISSN:0018-9456
1557-9662
DOI:10.1109/TIM.2024.3391335