摘要
基于模型的预测控制算法在工业控制中获得了广泛的应用,特别是针对非线性大时滞系统.本文提出了一种基于内模结构的模糊控制算法,它的最大特点是引入模糊内模预估器作为被控过程的内部模型,对过程输出进行预测,从而克服时滞对系统带来的不利影响,同时,根据预测误差,滤波器在线修正、补偿被控过程的模型失配.仿真及炉温实时控制实验结果表明,此种控制策略优于常规控制方法,实用前景明显.
Predictive control algorithms based on model have gained widespread applications, especially at some non-linear and dead-time systems. In this paper, a fuzzy control system based on internal model structure is proposed. Its main feature is to introduce an intelligent fuzzy internal model predictor into control system so as to forecast output of the process and to reduce the influence of dead time. At the same time a filter would modify and compensate the change of model according to the predictive error. It is shown in simulations that the proposed control method has better control results than other common control methods. Furthermore, an experiment of the electrical-resistance furnace indicates that it has a perfect practical outlook.
出处
《模式识别与人工智能》
EI
CSCD
北大核心
2002年第4期448-452,共5页
Pattern Recognition and Artificial Intelligence
