胎面重量控制系统的CPSO优化Smith预估线性自抗扰策略

针对轮胎行业橡胶复合挤出线重量控制系统过程机理复杂、扰动过多且难以测量等问题，设计了一种史密斯预估与线性自抗扰控制(Smith prediction-linear active disturbance rejection control, Smith-LADRC)相结合的控制方式以实现对胎面重量的稳定控制。建立仿真模型与比例-积分-微分(proportional-integral-differential, PID)、LADRC、Smith-PID进行控制效果对比以验证其优势，同时针对此控制器调参困难引入混沌粒子群算法(chaotic particle swarm optimization, CPSO)进行参数整定。经实验结果表明：Smith-LADRC相较于上述3种控制方法能够使系统具有较好的抗干扰性和鲁棒性；采用CPSO算法寻优后，相比于粒子群算法(particle swarm optimization, PSO),可以很好地达到控制目的，系统输出响应快速性均得到提高，相比手动调节能更好地对系统输出进行控制，同时节省参数调节时间，提高控制效率。

Smith Prediction Linear Active Disturbance Rejection Strategy Based on CPSO Optimization of Tread Weight Control System

Aiming at the problems of complex process mechanism, excessive disturbance and difficult measurement of the weight control system of the rubber compound extrusion line in the tire industry, a control method combining Smith prediction and linear active disturbance rejection control (Smith-LADRC) is designed to realize the Stable control of tread weight. The simulation model established to compare the control effect with PID, LADRC and Smith-PID to verify its advantages. At the same time, the chaotic particle swarm algorithm (CPSO) introduced to adjust the parameters for the difficulty of parameter adjustment of this controller. The experimental results show that compared with the above three control methods, Smith-LADRC can make the system have better anti-interference and robustness. The control purpose is well achieved, and the rapidity of the system output response is improved. Compared with manual adjustment, the system output can be better controlled, while the parameter adjustment time is saved and the control efficiency is improved.