基于遗传算法整定参数的火力发电用电机伺服控制分析

Analysis of servo control of thermal power generation motor based on Genetic algorithm setting parameters

同步发电机的控制精度对提高火力发电效率的影响较大,为进一步提高火力发电用电机伺服控制控制精度,选用遗传算法整定驱动轴参数。从正弦信号和直线信号两个方面开展进给测试,促进跟随性能的显著提升。研究结果表明:遗传算法优化可知,在当前人工经验条件进行整定得到的系统带宽接近64 Hz,响应性能较为理想。正弦信号下,采用遗传算法进行参数整定时,跟随误差更低,表现出更优的跟随性能。绝对误差极值降低27.3%,绝对误差积分降低42.4%。直线进给状态下,跟随误差更低,表现出更优的跟随性能。绝对误差极值降低28.6%,绝对误差积分降低39.1%。相对于人工经验整定方式,达到更优的误差波动控制状态,实现了较优的伺服稳定性。

The control precision of synchronous generator has great influence on the efficiency of thermal power generation.In order to improve the servo control precision of thermal power generation motor,genetic algorithm was selected to set the parameters of drive shaft.The feed test is carried out from sinusoidal signal and linear signal,and the following performance is improved significantly.The research results show that the genetic algorithm optimization shows that the system bandwidth is close to 64 Hz under the current manual experience condition,and the ideal response performance is obtained.Under sinusoidal signal,the genetic algorithm can achieve lower following error and better following performance.The absolute error extremums are reduced by 27.3%and the absolute error integrals are reduced by 42.4%.The following error is lower and the following performance is better in the straight-line feed state.The absolute error extremity is reduced by 28.6%,and the absolute error integral is reduced by 39.1%.Compared with the manual experience setting method,better error fluctuation control state is achieved and better servo stability is achieved.