Smart torque control for overloaded motor using artificial intelligence approach - Mohamed, Hazizul (2013)
This project report presents a methodology for implementation of a rule-based fuzzy logic controller applied to an induction motor torque control. The designed Fuzzy Logic Controller’s performance is weighed against with that of a PI controller. The pros of the Fuzzy Logic Controllers (FLCs) over the conventional controllers are they are economically advantageous to develop, a wider range of operating conditions can be covered using FLCs, and they are easier to adapt in terms of natural language. Another advantage is that, an initial approximate set of fuzzy rules can be impulsively refined by a self-organizing fuzzy controller. For torque control of the induction motor, a reference torque has been used and the control architecture includes some rules. These rules portray a nonchalant relationship between two inputs and an output, all of which are nothing but normalized voltages. These are the input torque error denoted by Error (e), the input derivative of torque error denoted by Change of error (Δe), and the output frequency denoted by Change of Control (ωsl). The errors are evaluated according to the rules in accordance to the defined member functions. The member functions and the rules have been defined using the FIS editor given in MATLAB. Based on the rules the surface view of the control has been recorded. The system has been simulated in MATLAB/SIMULINK® and the results have been attached. The results obtained by using a conventional PI controller and the designed Fuzzy Logic Controller has been studied and compared.