控制理论(社会学)
计算机科学
非线性系统
执行机构
观察员(物理)
动态规划
人工神经网络
最优控制
控制工程
控制器(灌溉)
工程类
控制(管理)
数学优化
数学
算法
人工智能
物理
机器学习
生物
量子力学
农学
作者
Peng Zhang,Yuan Yuan,Lei Guo
出处
期刊:IEEE transactions on cybernetics
[Institute of Electrical and Electronics Engineers]
日期:2019-07-12
卷期号:51 (6): 2956-2968
被引量:59
标识
DOI:10.1109/tcyb.2019.2923011
摘要
This paper investigates the dynamic event-triggered fault-tolerant optimal control strategy for a class of output feedback nonlinear discrete-time systems subject to actuator faults and input saturations. To save the communication resources between the sensor and the controller, the so-called dynamic event-triggered mechanism is adopted to schedule the measurement signal. A neural network-based observer is first designed to provide both the system states and fault information. Then, with consideration of the actuator saturation phenomenon, the adaptive dynamic programming (ADP) algorithm is designed based on the estimates provided by the observer. To reduce the computational burden, the optimal control strategy is implemented via the single network adaptive critic architecture. The sufficient conditions are provided to guarantee the boundedness of the overall closed-loop systems. Finally, the numerical simulations on a two-link flexible manipulator system are provided to verify the validity of the proposed control strategy.
科研通智能强力驱动
Strongly Powered by AbleSci AI