Real-time tracking on adaptive critic design with uniformly ultimately bounded condition
Document Type
Conference Proceeding
Date of Original Version
12-1-2013
Abstract
In this paper, we proposed a new nonlinear tracking controller based on heuristic dynamic programming (HDP) with the tracking filter. Specifically, we integrate a goal network into the regular HDP design and provide the critic network with detailed internal reward signal to help the value function approximation. The architecture is explicitly explained with the tracking filter, goal network, critic network and action network, respectively. We provide the stability analysis of our proposed controller with Lyapunov approach. It is shown that the filtered tracking errors and the weights estimation errors in neural networks are all uniformly ultimately bounded (UUB) under certain conditions. Finally, we compare our proposed approach with regular HDP approach in virtual reality (VR)/Simulink environment to justify the improved control performance. © 2013 IEEE.
Publication Title, e.g., Journal
IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning, ADPRL
Citation/Publisher Attribution
Ni, Zhen, Xiao Fang, Haibo He, Dongbin Zhao, and Xin Xu. "Real-time tracking on adaptive critic design with uniformly ultimately bounded condition." IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning, ADPRL (2013): 39-46. doi: 10.1109/ADPRL.2013.6614987.