Fuzzy PI control through optimization: A new method for PI control of switched reluctance motor

The proportional and integral (PI) control plays an important role in industry. The PI controller is still widely used, due to its simplicity and effectiveness. For a system with predictable and low order dynamic behavior, PI control works well. However, it is far from perfect, its performance is not satisfactory in the case of nonlinear systems. Then, we have to find a new PI design or tuning method. This paper proposes a new design of adaptive fuzzy PI controllers to achieve optimal control performance. By applying numerical optimization, the fuzzy PI design problem is transferred to a numerical optimization problem. First, a fuzzy parameter tuner is built to generate initial PI parameters, including positions and shapes of fuzzy membership functions and scaling factors. Then the gradient-based sequential quadratic programming (SQP) algorithm is employed to minimize the cost function by adjusting the parameters. The proposed scheme is applied to control the speed of the switched reluctance motor. The effectiveness of this control technique is verified by numerical simulation.