A naive method of applying fuzzy logic to CMAC in electric load simulator

Abstract

The inherent non-linear factors and the interference of external surplus torque of the electric load simulator make it difficult for the conventional control methods to achieve satisfactory control effect. The cerebellar model articulation controller (CMAC) is widely used because of its simple structure and quick learning. However, conventional CMAC utilizes binary 0 and 1 logic, which will lead to the divergence during the torque tracking. Inspired by the cognitive characteristics of the human brain, the fuzzy logic is implemented to CMAC. In this paper, we design a naive method of applying fuzzy logic to CMAC (NFCMAC), which can take both advantages of the local neural network and the global neural network, and present a new interpretation of the entire network. With parallel control of a PD controller, the NFCMAC–PD control strategy has been successfully applied to the electric load simulator. Dynamic simulation and experimental results have indicated that the NFCMAC–PD control strategy can ensure the control precision, restrain interference and be free of divergence, while satisfy the control requirement of the passive loading system.