On-line adaptive control for inverted pendulum balancing based on feedback-error-learning

Authors:
Xiaogang Ruan;Mingxiao Ding;Daoxiong Gong;Junfei Qiao
Affiliations:
Institution of Artificial Intelligence and Robots, Beijing University of Technology, Beijing 100022, China;Institution of Artificial Intelligence and Robots, Beijing University of Technology, Beijing 100022, China;Institution of Artificial Intelligence and Robots, Beijing University of Technology, Beijing 100022, China;Institution of Artificial Intelligence and Robots, Beijing University of Technology, Beijing 100022, China
Venue:
Neurocomputing
Year:
2007

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Abstract

A new on-line adaptive control scheme based on feedback-error-learning is proposed and applied to inverted pendulum balancing. The proposed adaptive controller for balancing consists of a conventional feedback controller (CFC) and a neural network feedforward controller (NNFC). In the NNFC, the feedback error signal is employed as input stimulator, instead of the usual reference signal. An on-line back-propagation (BP) algorithm with the self-adaptive learning rate is developed and employed in the NNFC to realize the combination of learning and controlling. Computer simulations on inverted pendulum balancing task demonstrate that the proposed adaptive controller could effectively reduce precision requirements of the CFC parameters, and guarantees good balance performance and acceptable robust performance.