改进遗传算法PID参数优化在流浆箱总压控制中的应用

摘要

稀释水水力式流浆箱的总压控制直接关系到纸张质量的好坏,传统的PID方法对于非线性、参数时变性和模型不确定性的对象控制精度较低.虽然传统遗传算法可以优化PID参数,提高精度,但是收敛速度慢,整定时间长,限制其在高速纸机控制中的应用.针对这些问题,本课题以纸机流浆箱总压控制为研究对象,采用改进的遗传算法来整定PID参数,通过优化交叉和变异算子、增加当前最优追踪策略以及改进收敛准则等方法来提高遗传算法的全局寻优能力和收敛速度.仿真结果表明,用改进的遗传算法整定后的流浆箱总压控制PID具有更快的响应速度和更好的鲁棒性.%The total pressure control of the diluted water hydraulic headbox is directly related to the quality of the paper.The traditional PID method has low control precision for the object which is nonlinear,parameter time-varying and model uncertainty.Although the traditional genetic algorithm can optimize the PID parameters and improve the precision,it has a slow convergence speed and a long dynamic response time,which limit its application in the control of high speed paper machine.Aiming at these problems,an improved genetic algorithm,which optimize the operators of crossover and mutation,take the optimal tracking strategy and inprove convergence criterion to enhance theorenall optimization ability of genetic algorithm and speed up the convergence rate,was employed in this paper to tune the PID parameters in total pressure control of headbox of the paper-making machine.The simulation results showed that the proposed method had faster response speed and better robustness than the Z-N tuning and traditional genetic algorithm.