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Author:

Ruan, Xiaogang (Ruan, Xiaogang.) | Ding, Mingxiao (Ding, Mingxiao.) | Gong, Daoxiong (Gong, Daoxiong.) | Qiao, Junfei (Qiao, Junfei.) (Scholars:乔俊飞)

Indexed by:

EI Scopus

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. © 2006 Elsevier B.V. All rights reserved.

Keyword:

Feedforward neural networks Pendulums Computer simulation Backpropagation Feedback control Adaptive control systems Algorithms Learning systems

Author Community:

  • [ 1 ] [Ruan, Xiaogang]Institution of Artificial Intelligence and Robots, Beijing University of Technology, Beijing, 100022, China
  • [ 2 ] [Ding, Mingxiao]Institution of Artificial Intelligence and Robots, Beijing University of Technology, Beijing, 100022, China
  • [ 3 ] [Gong, Daoxiong]Institution of Artificial Intelligence and Robots, Beijing University of Technology, Beijing, 100022, China
  • [ 4 ] [Qiao, Junfei]Institution of Artificial Intelligence and Robots, Beijing University of Technology, Beijing, 100022, China

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Source :

Neurocomputing

ISSN: 0925-2312

Year: 2007

Issue: 4-6

Volume: 70

Page: 770-776

6 . 0 0 0

JCR@2022

ESI Discipline: COMPUTER SCIENCE;

JCR Journal Grade:3

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 46

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 2

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