Regulation With Guaranteed Convergence Rate for Continuous-Time Systems With Completely Unknown Dynamics in the Presence of Disturbance
Author:
Affiliation:
1. Electrical Engineering Department, Iran University of Science and Technology, Tehran, Iran
2. School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran
3. School of Engineering, Lancaster University, Lancaster, U.K.
Funder
Engineering and Physical Sciences Research Council
National Centre for Nuclear Robotics
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/6287639/9668973/09895408.pdf?arnumber=9895408
Reference45 articles.
1. $ {H}_{ {\infty }}$ Tracking Control of Completely Unknown Continuous-Time Systems via Off-Policy Reinforcement Learning
2. Integral reinforcement learning-based optimal output feedback control for linear continuous-time systems with input delay
3. Robust Reinforcement Learning: A Case Study in Linear Quadratic Regulation
4. Neural network‐based optimal tracking control for partially unknown discrete‐time non‐linear systems using reinforcement learning
5. Data-Driven Robust Control of Discrete-Time Uncertain Linear Systems via Off-Policy Reinforcement Learning
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