Optimization Algorithm Based On Fuzzy And Genetic Optimization Of PID Parameters

PID (Proportion, Integral, Differential) that is proportional, integral, differential control of industrial process control law is the most widely used control strategy, it has a simple algorithm, robustness, and high reliability. However, with industrial development, the deepening complexity of the object, particularly for large time delay, time-varying, nonlinear and complex system, in addition, people increasingly demand quality control, conventional control deficiencies gradually exposed. For the time-varying objects and nonlinear systems, the traditional PID control has been unable to meet the control requirements of industrial production.Intelligent control and conventional control of the combined use of more and more being used in industrial control. Genetic and fuzzy as a new type of intelligent current control algorithm, genetic algorithm and PID control and fuzzy control intelligent control and genetic algorithm to form a fuzzy adaptive tuning PID algorithm and genetic algorithm based tuning method of PID parameters. MATLAB software simulation results show that these two intelligent PID tuning algorithm is effective and can achieve the desired control effect. However, the parameters of fuzzy controller is difficult to determine the membership functions and fuzzy rules are much dependent on staff experience and knowledge of experts, Space genetic algorithm optimization capability, the parameters of membership functions comprehensive code optimization, get new fuzzy controller.On this basis, the existing laboratory course PCI-Ⅲ-type experimental platform in the two-tank water level control system was modeled, using conventional PID control and genetic algorithm optimization of fuzzy PID control of the experimental system were simulation and comparison; and build a real-time systems based on Configuration hybrid simulation platform, for a variety of parameter tuning method of PID control performance of the experiment. Simulation and experimental results show that intelligent PID tuning method has good control performance, significantly better than conventional PID tuning methods, in particular by the genetic algorithm optimized fuzzy controller tuning of PID control performance better.At last, the work of this paper, and pointed out that the use of intelligent control algorithm optimization of PID parameters to be further improved to solve the problem.