Research of Fuzzy-PID Controller Based on Nonlinear Optimization Method
The time delay often exists in the industrial process. Its control effect by conventional PID controller needs to be improved. In this paper, a method of parameter setting based on nonlinear optimization is proposed. Combined with Fuzzy-PID, the robustness of the control system is improved. Compared with traditional PID, the proposed controller shows better control effect with the variation of controlled object. Introduction In industrial control, the traditional PID control is still in a dominant position. It gains popularity among the engineers because of the advantages of simple structure, easy implementation and clear physical significance. In PID control strategy, generally speaking, the control parameters are set manually. It requires the designers to be rich experienced in engineering, and requires some understanding of the controlled object. Systems with time delay are commonly seen in industrial process. The time delay element also affects the stability of the system and makes it harder to control. Wenbo [1] has proposed a method sectionalizing the error signal of the step response into three different functional zones. This works well in the height control system, but lack of general applicability. There are some other methods used for parameter setting, such as critical proportion method and ideal relay feature method, are based on the offline feature of the object, and the control effect may not meet the required performance indicators. Muhammad Faisal [2] has proposed an adaptive fuzzy based smith controller. The smith predictor can balance the time delay element and the fuzzy control improves the robustness of the system. However, the initial value of the control parameters has a significant impact on the system. It’s still a question to set them. Also when the parameters of the predictor do not meet the controlled object, this method cannot ensure the stability of the system. Therefore, the above control methods rely heavily on the identification or understanding of the controlled object model and experience of the engineering staff. In order to solve this problem, this paper proposes a Fuzzy-PID controller based on nonlinear optimization, which is using constrained nonlinear optimization method to set initial value of PID control parameters. This method greatly reduces the influence of the inappropriate initial value of the control parameter. There is even no need to use Smith predictor to keep the performance. The controller can set initial value of PID parameters online and use fuzzy control strategy to improve the control effect. On the premise of meeting the required performance indicators, the controller can achieve the optimal effect by the proposed strategy. Preliminarys Constrained Nonlinear Optimization A typical nonlinear optimization problem has the following formula [3]: A constrained nonlinear problem:s