中文摘要：

神经元PID控制器虽然具有自学习和自调整能力，但其增益K不具备这种能力。而增益K对多电机同步控制系统又有着十分显著的影响。为解决这一问题，将自适应PSD控制算法应用于神经元PID控制器中，形成增益K的自适应算法，解决了传统神经元PID控制器增益K无法实时在线调整的缺点，提高了传统神经元PID控制器的自学习和自调整能力。应用MATLAB7．0分别搭建常规PID、神经元PID和基于PSD算法的神经元PID的3种多电机同步控制系统模型，进行仿真比较。仿真结果表明：基于PSD算法的神经元PID多电机同步控制系统具有更好的自适应性和鲁棒性，实现了提高多电机同步控制系统控制精度的目的。

英文摘要：

Neuron propotional intergal and differential （PID） controller had self-learning and self-adjusting ability, but whose gain K did not, moreover gain K had an very significant effect on multi-motor synchronous control. In order to solve the problem, by applying self-adjusting PSI） control algorithm to neuron PID controller and forming self-adjusting algorithm of gain K, the shortcoming was overcomed that gain K for tranditonal neuron PID controller could not be adjusted in real time on line, and its self-learning and self- adjusting ability were improved. By using MATLABT. 0, three motors synchronous control system model of general PII）, neuron PII） and neuron PID based on PSD algorithm were respectively set up, and simulated to compare. The simulation result shows that neuron PID multi-motor synchronous control system based on PSD algorithm has better self-adjusting and robustness, which realizes the pur- pose to improve multi-motor synchronous control accuracy.