GAAS优化PID算法在全电动注塑机注射系统中的应用

Application of GAAS Optimization PID Algorithm in Injection System of All-Electric Injection Molding Machine

全电动注塑机有2个伺服电机同时进行驱动,与一般的伺服液压注塑机相比,控制精度更高、控制速度更快,针对其控制系统提出一种遗传算法修正的蚁群算法(GAAS)对闭环PID控制的控制参数进行优化,该算法能够有效提高系统的快速性和准确性.Rosenbrock函数验证了嵌入遗传算法后蚁群算法的优越性,嵌入遗传算法后收敛速度更快,算法具有更优良的收敛速度GAAS算法能够提供更加准确可靠的PID参数,且不会降低系统的调节性能.仿真实验证明,GAAS算法能够有效减小系统超调量、缩短调节时间;在实际运行中,注射螺杆的控制精度在0.5%以内.因此,控制器可以大幅度改善全电动注塑机的闭环控制效果,参考价值较大.

All electric injection molding machine had 2 servo motors for simultaneous driving. Compared with general servo hydraulic injection molding machine, the control precision was higher and the control speed was faster. A genetic algorithm modified ant colony algorithm (GAAS) was proposed for the control system. The control parameters of the closedloop PID control were optimized. So the rapidity and accuracy of the system could be effectively improved by the algorithm. The Rosenbrock function verified the superiority of the ant colony algorithm after the embedded genetic algorithm. Faster convergence rate and better convergence speed had been processed by the embedded genetic algorithm. More accurate and reliable PID parameters without reducing the tuning performance of the system were provided by the GAAS algorithm. Simulation experiments showed that the GAAS algorithm could effectively reduce the system overshoot and shorten the adjustment time;the control accuracy of the injection screw within 0. 5%. The result proved that the effect of closed-loop control of all-electric injection molding machine could be greatly improved by the controller proposed, which was valuable.