Abstract
In industrial control process, saving energy and produce high quality products is demanded. A cerebellar model articulation controller (CMAC) based performance-driven (PD) PID controller is proposed to tune its gains for both transient and steady state, so that the above requirement achieves. For a conventional CMAC, a high learning accuracy is obtained by sacrificing its generalization ability. Therefore, a hierarchical clustering CMAC (HC-CMAC) is proposed. Compare with conventional CMAC, the proposed HC-CMAC enables each weight table different number of labels. In this case, the feature of CMAC such as partial learning ability and generalization ability are remained, simultaneously, the weight tables with less labels increase generalization ability and the weight tables with more labels increase learning accuracy. In some industrial control processes, if a machine participates not only one production process, a few reference signals may be set to the machine due to different conditions. If a controller tunes its gains for different situations, it costs a large calculation time, hence, generalization ability for similar reference signals of a controller is important. Based on above considerations, a HC-CAMC PD PID controller is proposed and some simulation results to show the effectiveness of proposed method are demonstrated in the paper.