搜寻者优化算法与卡尔曼滤波相结合的PID控制

PID Control Combining Seeker Optimization Algorithm and Kalman Filter

针对传统PID控制器的参数整定依靠经验调整,且在控制过程中,系统易受多种噪声影响的问题,提出搜寻者优化算法与卡尔曼滤波相结合的PID控制方法。利用搜寻者优化算法对PID参数进行智能优化,利用卡尔曼滤波器实现对控制噪声和测量噪声的有效抑制。对二阶延迟系统进行仿真试验,结果表明,与传统PID控制方法相比,该方法可以智能地获得较优的PID参数,有效剔除了控制过程中的噪声干扰,实现了调节速度快、稳态误差低、抗干扰能力强的智能PID控制。

Parameter tuning of traditional PID controller depends on experience, and in control process, the system is easily affected by a varietyof noises, in order to settle these problems, the PID control method based on combination of seeker optimization algorithm and Kalman filter isproposed. The seeker optimization algorithm is used to optimize PID parameters intelligently, and Kalman filter is used to effectively suppress thecontrol noise and measurement noise. A second order system with delay is simulated,and the results show that compared with the traditional PIDcontrol method,this method can achieve intelligent PID control to get better PID parameters and effectively eliminate noise interference in theprocess of control,to implement intelligent PID control which is featured with good performance in quick regulation speed,low steady - stateerror and strong anti - interference capability.