Abstract—
The conventional Proportional-Integral (PI) speed control has been widely used in industrial motor controls due to its capabilities in controlling linear plants. However, motor behaves as non-linear plant where the PI speed control may not be able to provide precise speed responses. With the fast growing of artificial intelligent in motor controls, the fuzzy logic and Adaptive Network Fuzzy Inference system (ANFIS) is available in more precise motor controls. Nevertheless, there are still many disputes on the superiority of PI and fuzzy logic controls. The fuzzy logic controller with rules-based is limited to a particular load torque due to its output membership functions, on the other hand, PI controller has better adaptability over load torque variation and has a smaller steady-state error even though it incurs the overshoot and has longer settling time. In this paper, a comparative analysis of PI, fuzzy logic, and ANFIS has done in the MATLAB SIMULINK environment
The conventional Proportional-Integral (PI) speed control has been widely used in industrial motor controls due to its capabilities in controlling linear plants. However, motor behaves as non-linear plant where the PI speed control may not be able to provide precise speed responses. With the fast growing of artificial intelligent in motor controls, the fuzzy logic and Adaptive Network Fuzzy Inference system (ANFIS) is available in more precise motor controls. Nevertheless, there are still many disputes on the superiority of PI and fuzzy logic controls. The fuzzy logic controller with rules-based is limited to a particular load torque due to its output membership functions, on the other hand, PI controller has better adaptability over load torque variation and has a smaller steady-state error even though it incurs the overshoot and has longer settling time. In this paper, a comparative analysis of PI, fuzzy logic, and ANFIS has done in the MATLAB SIMULINK environment
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