Design and Experimental Evaluation of an Intelligent PID Controller using CMACs

Skilled workers decrease in these years. Then it is a problem that skilled techniques and know-how of specific work are not taken over to next generations. Therefore, a controller which is based on a human-skill is needed to design. On the other hand, in recent year, various neural networks (NNs) have been proposed. These technologies of the NNs enable us to deal with the nonlinear systems, and they play an important role in the field of control engineering. Furthermore, a cerebellar model articulation controller (CMAC) has been proposed as one or artificial NNs. The CMAC is highly structured mathematically, considering the cerebellar as a controller for the body motion system. The CMAC has the advantage for the short learning Lime compared with the conventional NNs. In this paper, a skill based intelligent PIED controller using CMACs is proposed. According to the proposed method, PID gains are tuned by trained CMACs. Those CMACs are learned using a human skill data in an off-line manner. And also they are trained on-line by a reference model. Furthermore, the experiment in order to illustrate the proposed scheme is performed by using one of pilot-scaled helicopter control models.