FUZZY SUPERVISOR FOR PID CONTROLLER
Mikhail Vladimirovich Burakov, A. S. Konovalov · Информационно-управляющие системы · 2018
Introduction: PID regulators are an important industrial automation tool. However, the traditional ways of their customization involve experiments with the plant, reducing the control system efficiency when the operating conditions change. To solve this problem, you have to use an adaptation loop which automatically changes the regulator parameters when the quality indicators deteriorate. Purpose: Developing a structure and an algorithm for a fuzzy supervisor of a PID controller in order to improve the operation quality in the context of uncontrolled changes in the plant parameters. Results: We propose two options for organizing a fuzzy supervisor. The first option involves continuous changing of the controller parameters based on the information about the current control error. The supervisor is trained offline with the help of a genetic algorithm. This approach makes the application universal, but the resulting structure is a «black box». The second option is using transient process quality estimates; it can be used when the input signal periodically changes. The controller parameters are changed using fuzzy rules with clear semantics. It is shown that systems with a fuzzy supervisor can reduce the overshoot or static error which both can occur when the control object parameters change. The system operation was simulated using MatLab Simulink. Practical relevance: The use of PID controllers with fuzzy supervisors can be useful in the design of control systems for a wide range of dynamic plants.