基于改进粒子群优化的胶粘剂生产过程温度控制

针对大惯性、纯迟延、非线性、时变的胶粘剂生产过程,提出一种改进粒子群优化的PID控制算法。该算法针对常规PID设计方法存在的缺点,提出了一种可兼顾多项性能指标的PID控制器参数整定的改进粒子群优化方法。该方法将遗传算法中的变异思想引入到标准的粒子群优化算法中,避免了算法陷入局部极值点,以寻优PID控制器参数。将该方法应用于胶粘剂生产过程,较好地实现了反应釜温度的跟踪控制。仿真结果和实际情况表明所提出算法的有效性和优越性。

Temperature control for the adhesive preparation processing based on improved particle swarm optimization

In view of the characteristics of the adhesive preparation processing which is lengthy, nonlinear, time -varying, big inertia and pure delay, A proportional-integral-derivative (PID) algorithm is proposed based on the improved particle swarm opti- mization. Because there are drawbacks in the design of PID controller, an improved particle swarm optimization which takes into account a number of performances is proposed to modify parameters of PID controllers. The variation of genetic algorithm is intro- duced to the standard particle swarm optimization algorithm, which can avoid local maximum points, thus the preferable PID con- troller parameters can be easily obtained. Applying the algorithm to the preparation of an adhesive process, the temperature of polymerizing-kettle can be tracked and controlled. Simulation and factual running shows that the algorithm is effective and has ex- cellent performance.