The adaptive control using BP networks for a nonlinear servo-motor
Xinliang ZHANG
Yonghong TAN
摘要：The servo-motor possesses a strongly nonlinear property due to the effect of the stimulating input voltageload-torque and environmental operating conditions.So it is rather diffcult to derive a traditional mathematical model which is capable of expressing both its dynamics and steady-state characteristics.A neural network-based adaptive control strategy is proposed in this paper.In this method,two neural networks have been adopted for system identification(NNI)and control(NNC),respectively.Then,the commonly-used specialized learning has been modified,by taking the NNI output as the approximation output of the servo-motor during the weights training to get sensitivity information.Moreover,the rule for choosing the learning rate is given on the basis of the analysis of Lyapunov stability.Finally,an example of applying the proposed control strategy on a servo-motor is presented to show its effectiveness.
机标关键词：BP networkscontrol strategysystem identificationoperating conditionsnonlinear propertymathematical modelLyapunov stabilityneural networks
资助基金：This research was partly supported by National Science Foundation of China(60572055)Advanced Research Grant of Shanghai Normal University(DYL200809)Guangxi Science Foundation(0339068)
论文发表日期：2008-01-01
在线出版日期：2025-08-15（本平台首次上网日期，不代表文献的发表时间）
页数：4( 273-276 )
英文信息