Integral Reinforcement Learning for Tracking in a Class of Partially Unknown Linear Systems With Output Constraints and External Disturbances
Author:
Affiliation:
1. School of Artificial Intelligence, Henan University, Zhengzhou, Henan, China
2. School of Computer and Information Engineering, Henan University, Zhengzhou, Henan, China
Funder
Youth Backbone Teachers in Colleges and Universities of Henan Province
Science and Technology Research Project of the Henan Province
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science
Link
http://xplorestaging.ieee.org/ielx7/6287639/9668973/09775967.pdf?arnumber=9775967
Reference37 articles.
1. Adaptive tracking control for nonlinear time-varying delay systems with full state constraints and unknown control coefficients
2. Barrier Lyapunov functions-based adaptive control for nonlinear pure-feedback systems with time-varying full state constraints
3. Adaptive control-based Barrier Lyapunov Functions for a class of stochastic nonlinear systems with full state constraints
4. Adaptive neural control for output feedback nonlinear systems using a barrier Lyapunov function;ren;IEEE Trans Neural Netw,2010
5. Tracking control optimization scheme for a class of partially unknown fuzzy systems by using integral reinforcement learning architecture
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