基于参数优化的PMSM双闭环滑模控制策略研究

Research on Double Closed Loop Sliding Mode Control Strategy of PMSM Based on Parameter Optimization

永磁同步电机(PMSM)具有成本低、精度高、稳定性好、体积小等众多优点,是交流伺服领域的重要研究方向。其传统比例积分微分(PID)控制已经不能满足目前非线性、强耦合系统的应用需求,有学者提出采用滑模变结构控制作为转速环控制器以解决调速系统动态品质不佳的问题。针对滑模控制器参数极难调试到系统效果优良的问题,提出了一种基于遗传算法(GA)替代试凑法优化滑模控制器参数的方法。通过GA迭代使得初始参数种群中经过适应度函数计算判断后系统动态品质较佳的参数得以保留并遗传、交叉变异出使系统动态品质更优的参数,经过数次迭代后算法输出最优的参数个体。仿真结果表明,提出的方法可以将需求的超调稳定在1%以内、稳态误差在1%以内、动态性能及快速性更佳,能更好地适应更多工况的需求。

Permanent magnet synchronous motor(PMSM) has many advantages,such as low cost,high precision,good stability and small size.It is an important research direction in the field of alternating current servo.Its traditional proportional integral differential(PID) control can no longer meet the current application requirements of nonlinear and strong coupling systems.Some scholars have proposed using sliding mode variable structure control as the speed loop controller to solve the problem of poor dynamic quality of the speed control system.Aiming at the problem that it is extremely difficult to adjust the parameters of the sliding mode controller to achieve a good system effect,a method is proposed to optimize the parameters of the sliding mode controller based on the genetic algorithm(GA) instead of the trial and error method.Through GA iteration,the parameters with better dynamic quality of the system after the fitness function calculation and judgment in the initial parameter population can be retained,and the parameters that make the system dynamic quality better are inherited and cross-mutated.After several iterations,the algorithm outputs the best parameter individual.The simulation results show that the proposed method can stabilize the demand over-shoot within1 %,steady-state error within 1 %,and has better dynamic performance and rapidity,better adapt to the needs of more operating conditions.