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NEURAL NETWORK BASED ASYNCHRONOUS LEARNING CONTROL SYSTEMS

DENG ZHIDONG; SUN ZENGQI (Dept. of Computer Sci. & Tech., Tsinghua University Beijing 100084 China)LIU JIANWEI (Dept. of Control Engineering, Harbin Institute of Technology Harbin 150006 China)  
In this paper the neural network based asynchronous learning control system,on the basis of the asynchronous learning control method given by ref. [1], is proposed. The gradient-type learning control algorithm is derived, the strict proof on stability convergency is provided by Lyapunov stability theory, and the simulation study of two links of PUMA 560 robot systems is given. The results show that the RMS track accuracy of this proposed method is improved greatly compared to classical PID control.
【Fund】: 国防科技预研基金
【CateGory Index】: TP273.22
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