基于神经网络滑模变结构的BLDC伺服控制系统

BLDC Position Servo System Based on Neural Network Sliding Mode Variable Structure

针对离散时间系统,分析了趋近律中参数对系统到达稳定状态时间的影响,提出了用递归神经网络方法自适应调整参数的控制策略;并将研究结果用于无刷直流电机(BLDC)位置伺服系统变结构控制器的设计。仿真试验结果表明,该控制器可以使伺服系统具有良好的跟踪能力和很强的鲁棒性。

For discrete time systems,the effect of the parameter choice is analyzed in order to shorten the time of reaching the sliding hypersurface.Then the new method which used the networks regulated adaptively parameters is applied to achieve accurate servo tracking to BLDC（brushless DC motor） control system.The simulation results demonstrate that the controller designed can provide the servo system with perfect tracking and strong robustness.