光电吊舱稳定控制方法研究与仿真

Research and Simulation of Stabilization Control Method for Optic-Electronic Pods

为提高光电吊舱的稳定性,采用PID算法和自抗扰控制算法(ADRC),分别对光电吊舱控制系统的速度回路进行控制。PID和ADRC都存在参数整定困难的问题,通过一种适应度函数,采用粒子群算法(PSO)和人群搜索算法(SOA)分别对PID控制器和ADRC控制器的参数进行优化,其中ADRC采用了FAL和FHAN两种形式的误差反馈控制率。优化过程表明,PSO比SOA收敛速度快,在PID参数寻优上,PSO精度高于SOA,而在ADRC参数寻优上,PSO精度要低于SOA。仿真结果表明,经过PSO和SOA参数优化,PID和ADRC的控制性能都要优于经验法取参,而且ADRC在响应速度,跟随误差,抵抗力矩干扰和速度干扰上,性能都要优于PID。综合来看,采用SOA优化的ADRC-FHAN具有最好的控制性能。

In order to improve the stability of the photoelectric pod,PID algorithm and active disturbance Rejection control(ADRC)algorithm are used respectively to control the speed loop of the photoelectric pod control system.PID and ADRC both have difficulty in parameter tuning.Therefore,the parameters of PID contrller and AD-RC controller were optimized by particle swarm optimization(PSO)and seeker optimization algorithm(SOA)through a fitness function,and the ADRC controller adopted two forms of error feedback control rate(FAL and FHAN).Opti-mization process shows that PSO has a faster convergence speed than SOA.In the terms of PID parameter optimiza-tion,PSO has a higher accuracy than SOA.However,in terms of ADRC parameter optimization,PSO has a lower ac-curacy than SOA.The simulation shows that the parameters optimized by PSO and SOA in PID and ADRC controller have better control performance than that by empirical method.Besides,ADRC is better than PID in response speed,following error,resistance to torque interference and speed interference.Overall,ADRC-FHAN optimized with SOA has the best control performance.