无刷直流电机小脑模型网络与PID复合控制

Compound control for brushless DC motors using cerebellar model controller and PID controller

为提高无刷直流电机调速驱动系统的性能,提出了无刷直流电机的小脑模型神经网络与PID复合控制策略。介绍了小脑模型神经网络的原理,给出了复合控制器的结构框图及适于数字控制的算法离散化过程,并对控制系统在转速指令和负载转矩变化时的性能进行了仿真和实验验证。结果表明,所提出的智能控制策略在减小转速超调的同时保证了响应速度,能快速平稳的跟踪给定指令,有效的抑制了负载扰动的影响,动、静态性能均优于PID控制。

To improve the performance of brushless DC motor drives, a novel approach of compound control for brushless DC motor using cerebella model articulation controller and PID strategy was proposed. The principle of cerebella model articulation controller was introduced. The structural flow chart of control system was presented, The compound control algorithm was discretized to be implemented on digital control systems, The operating condition with speed reference and torque reference changed was simulated and experimented. The proposed intelligent control strategy shows perfect response on speed reference with very short setting time and extremely reduced overshot. The effect of load disturbance is dramatically restrained. Motor speed traces reference steadily and accurately. Finally, conclusion can be drawn that the intelligent control strategy is better than PID control both in dynamic and steady state.