4.7 Article

Discrete-Time H2 Neural Control Using Reinforcement Learning

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Automation & Control Systems

Self-Learning Optimal Regulation for Discrete-Time Nonlinear Systems Under Event-Driven Formulation

Ding Wang et al.

IEEE TRANSACTIONS ON AUTOMATIC CONTROL (2020)

Article Automation & Control Systems

Robust control under worst-case uncertainty for unknown nonlinear systems using modified reinforcement learning

Adolfo Perrusquia et al.

INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL (2020)

Article Computer Science, Cybernetics

Robot Position/Force Control in Unknown Environment Using Hybrid Reinforcement Learning

Adolfo Perrusquia et al.

CYBERNETICS AND SYSTEMS (2020)

Article Engineering, Industrial

Position/force control of robot manipulators using reinforcement learning

Adolfo Perrusquia et al.

INDUSTRIAL ROBOT-THE INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH AND APPLICATION (2019)

Article Chemistry, Multidisciplinary

Data-Driven Model-Free Tracking Reinforcement Learning Control with VRFT-based Adaptive Actor-Critic

Mircea-Bogdan Radac et al.

APPLIED SCIENCES-BASEL (2019)

Article Computer Science, Artificial Intelligence

Observer-based adaptive neural optimal control for discrete-time systems in nonstrict-feedback form

Shiyi Zhao et al.

NEUROCOMPUTING (2019)

Article Computer Science, Artificial Intelligence

Optimal and Autonomous Control Using Reinforcement Learning: A Survey

Bahare Kiumarsi et al.

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2018)

Article Computer Science, Artificial Intelligence

Adaptive Event-Triggered Control Based on Heuristic Dynamic Programming for Nonlinear Discrete-Time Systems

Lu Dong et al.

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2017)

Article Automation & Control Systems

Model-based reinforcement learning for approximate optimal regulation

Rushikesh Kamalapurkar et al.

AUTOMATICA (2016)

Article Computer Science, Artificial Intelligence

Near Optimal Event-Triggered Control of Nonlinear Discrete-Time Systems Using Neurodynamic Programming

Avimanyu Sahoo et al.

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2016)

Article Computer Science, Artificial Intelligence

Optimal Critic Learning for Robot Control in Time-Varying Environments

Chen Wang et al.

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2015)

Article Computer Science, Artificial Intelligence

Actor-Critic-Based Optimal Tracking for Partially Unknown Nonlinear Discrete-Time Systems

Bahare Kiumarsi et al.

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2015)

Article Computer Science, Artificial Intelligence

H∞ Tracking Control of Completely Unknown Continuous-Time Systems via Off-Policy Reinforcement Learning

Hamidreza Modares et al.

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2015)

Article Automation & Control Systems

Linear Quadratic Tracking Control of Partially-Unknown Continuous-Time Systems Using Reinforcement Learning

Hamidreza Modares et al.

IEEE TRANSACTIONS ON AUTOMATIC CONTROL (2014)

Article Computer Science, Artificial Intelligence

A supervised Actor-Critic approach for adaptive cruise control

Dongbin Zhao et al.

SOFT COMPUTING (2013)

Article Automation & Control Systems

Reinforcement Learning and Feedback Control USING NATURAL DECISION METHODS TO DESIGN OPTIMAL ADAPTIVE CONTROLLERS

Frank L. Lewis et al.

IEEE CONTROL SYSTEMS MAGAZINE (2012)

Article Automation & Control Systems

Efficient Model Learning Methods for Actor-Critic Control

Ivo Grondman et al.

IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS (2012)

Article Automation & Control Systems

Online actor-critic algorithm to solve the continuous-time infinite horizon optimal control problem

Kyriakos G. Vamvoudakis et al.

AUTOMATICA (2010)

Article Computer Science, Artificial Intelligence

Neural network approach to continuous-time direct adaptive optimal control for partially unknown nonlinear systems

Draguna Vrabie et al.

NEURAL NETWORKS (2009)

Article Automation & Control Systems

Discrete-time nonlinear HJB solution using approximate dynamic programming: Convergence proof

Asma Al-Tamimi et al.

IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS (2008)

Article Computer Science, Artificial Intelligence

Multiple recurrent neural networks for stable adaptive control

Wen Yu

NEUROCOMPUTING (2006)

Article Computer Science, Artificial Intelligence

Stable auto-tuning of adaptive fuzzy/neural controllers for nonlinear discrete-time systems

HN Nounou et al.

IEEE TRANSACTIONS ON FUZZY SYSTEMS (2004)

Article Automation & Control Systems

Input-to-state stability for discrete-time nonlinear systems

ZP Jiang et al.

AUTOMATICA (2001)