基于混沌理论的预测PID控制器参数优化研究

A Study of the Prediction of Parameter Optimization of a PID Controller Based on Chaotic Theory

现实工业过程时常受到外部干扰并且往往具有慢时变特性,导致传统PID控制难以及时跟踪系统变化克服噪音干扰。对混沌优化理论在控制过程中的应用进行了研究:将预测控制和PID控制器结合运用于再热汽温系统的控制当中,并采用神经网络作为系统预测模型,通过混沌优化算法对PID参数实行在线优化。计算机仿真试验验证了该算法的有效性,同传统PID控制相比较,基于混沌理论的PID预测控制能够及时跟踪系统变化克服外界扰动,取得了良好的控制效果,展现出了很强的鲁棒性能。

Realistic industrial processes frequently suffer from an external interference,and tend to assume slow and time-variation features,making it difficult for a traditional PID (proportional-integral-differential) controller to timely track the changes of a system and overcome noise interference.The authors have studied the application of chaos-based optimization theory in various control processes.By the combined use of a prediction control and PID controller in the control of a reheat steam temperature system and with a neural network serving as a system prediction model,an on-line optimization has been performed of PID parameters through a chaos-based optimization algorithm.A computer-based simulation test has verified the effectiveness of the algorithm.Compared with the traditional PID control,the PID prediction control based on chaotic theory is capable of timely tracking system changes and overcoming any outside perturbations.As a result,achieved is a good control effectiveness and the exhibition of a very strong robustness performance.