球磨机对象控制中模糊径向基函数神经网络的PID控制分析

摘要

结合球磨机制粉系统的特点，提出球磨机对象控制中模糊径向基函数神经网络PID控制算法，结合混合优化算法，在混沌粒子群优化的同时实现粗线调，并应用BP算法做好在线细调，进而得到PID控制的最佳参数。通过Matla对算法进行仿真，结果表明，系统不仅有效解决了球磨机复杂对象的控制问题，同时也实现了算法的快速收敛，并有较快的跟踪速度以及较小的超调，解耦较好，适应性较强。%On the basis of the characteristics of ball mill pulverizing system,the PID control algorithm of fuzzy radial basis function neural network is proposed in this paper,in which the hybrid optimization algorithm is combined to realize the chaos particle swarm optimization and coarse tunning,and the optimal parameters of PID controller are obtained by using BP algo⁃rithm. The Matlab simulation results show that the system has the advantages of fast tracking speed,small overshoot and strong adaptability,it not only can effectively solve the problem of the ball mill complex object,but also achieve the fast convergence of the algorithm.