Complete stability analysis of a heuristic approximate dynamic programming control design
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TLDR
This paper provides new stability results for Action-Dependent Heuristic Dynamic Programming (ADHDP), using a control algorithm that iteratively improves an internal model of the external world in the autonomous system based on its continuous interaction with the environment.About:
This article is published in Automatica.The article was published on 2015-09-01 and is currently open access. It has received 102 citations till now. The article focuses on the topics: Adaptive control & Stability (learning theory).read more
Citations
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Data-Driven Optimal Consensus Control for Discrete-Time Multi-Agent Systems With Unknown Dynamics Using Reinforcement Learning Method
TL;DR: A data-based adaptive dynamic programming method is presented using the current and past system data rather than the accurate system models also instead of the traditional identification scheme which would cause the approximation residual errors.
Journal ArticleDOI
Adaptive Critic Nonlinear Robust Control: A Survey
Ding Wang,Haibo He,Derong Liu +2 more
TL;DR: This survey reviews the recent main results of adaptive-critic-based robust control design of continuous-time nonlinear systems and promotes the development of adaptive critic control methods with robustness guarantee and the construction of higher level intelligent systems.
Journal ArticleDOI
Air-Breathing Hypersonic Vehicle Tracking Control Based on Adaptive Dynamic Programming
TL;DR: The adaptive supplementary control approach versus the traditional SMC in the cruising flight is verified, and three simulation studies are provided to illustrate the improved performance with the proposed approach.
Journal ArticleDOI
Learning-Based Adaptive Attitude Control of Spacecraft Formation With Guaranteed Prescribed Performance
TL;DR: A novel leader-following attitude control approach for spacecraft formation under the preassigned two-layer performance with consideration of unknown inertial parameters, external disturbance torque, and unmodeled uncertainty is investigated.
Journal ArticleDOI
Event-Driven Adaptive Robust Control of Nonlinear Systems With Uncertainties Through NDP Strategy
TL;DR: An event-driven adaptive robust control approach for continuous-time uncertain nonlinear systems through a neural dynamic programming (NDP) strategy, which provides a new avenue of combining adaptive dynamic programming-based self-learning control, event-triggered adaptive control, and robust control, to investigate the nonlinear adaptive robust feedback design under uncertain environment.
References
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Neuro-Dynamic Programming.
TL;DR: In this article, the authors present the first textbook that fully explains the neuro-dynamic programming/reinforcement learning methodology, which is a recent breakthrough in the practical application of neural networks and dynamic programming to complex problems of planning, optimal decision making, and intelligent control.
Book
Neuro-dynamic programming
TL;DR: This is the first textbook that fully explains the neuro-dynamic programming/reinforcement learning methodology, which is a recent breakthrough in the practical application of neural networks and dynamic programming to complex problems of planning, optimal decision making, and intelligent control.
Journal ArticleDOI
Neuronlike adaptive elements that can solve difficult learning control problems
TL;DR: In this article, a system consisting of two neuron-like adaptive elements can solve a difficult learning control problem, where the task is to balance a pole that is hinged to a movable cart by applying forces to the cart base.
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