Research On Self-adaptive Fuzzy Control System Based On Granular Function

As a new field of automatic control,intelligent control provides a new solution to such complex uncertainty problems with advanced and novel thinking.Intelligent control and PID control combine to form intelligent PID control.In this paper,the principle and method of fuzzy adaptive intelligence are selected and combined with the PID control algorithm to implement the all-round research on the liquid level control system,so that the control can be adaptive and self-tuning.Since the traditional mathematical methods are oriented to accurate mathematical models,and the actual control problems in nature cannot sometimes be described by traditional accurate modeling methods,fuzzy control theory provides a new method for this complex unmodelable control problem.The fuzzy control system relies on expert control experience and a large number of experiments to determine fuzzy rules and perform inference control.Compared with traditional control,fuzzy control uses fuzzy inference mechanism for controlled objects that are difficult to give accurate mathematical modeling.Although the fuzzy control system has a mature control theory foundation,when the input variables of the fuzzy control system increase,a large number of fuzzy rules are generated in the fuzzy controller,which makes the calculation of the system increase and becomes extremely complicated,so it needs to be blurred.With defuzzification.In this paper,the granulation theory is applied to the fuzzy conditional sentences,and the granulation function is used to replace the fuzzy reasoning process of the traditional fuzzy control system.The input and output obtained by each fuzzification and de-fuzzification can be regarded as a set of mapping relations between input and output.Each fuzzy control rule can be regarded as a fuzzy rule granule.The mapping relationship can be expressed by the precise response function obtained by fitting the appropriate selected points in the fuzzy rule granule.Therefore,the fuzzy reasoning of the fuzzy control system can be equivalent to a fitting response function with different fitting orders.The response function can also reduce the computational complexity of the system.A new design idea of the fuzzy control system is given.The granular function method is used to replace the traditional fuzzy control algorithm.The experimental verification of the granular function fuzzy control system is carried out in single tank and double tank.By introducing adaptive fuzzy PID control,an adaptive fuzzy PID control controller for water tank level is designed.Through self-tuning of parameters,the function of automatically adjusting PID parameters is achieved.The control of double-tank level is realized.The comparison between the two algorithms verifies the accuracy,rapidity,stability and robustness of the adaptive fuzzy PID algorithm in the control effect.It is superior to the traditional PID algorithm.An adaptive fuzzy PID control system based on granular function is designed to control the liquid level of double-tank system.Since the adaptive fuzzy PID control system is composed of two inputs and three outputs,the adaptive fuzzy PID controller is replaced by three fitted two inputs and one output functions in parallel.Through simulation analysis,parallel function can control liquid level better.At the same time,different fitting order response functions can also reduce the complexity of system operation,which proves the feasibility and superiority of granular function in intelligent control of non-linear system.The innovations of this paper are as follows: 1.Adaptive fuzzy PID control uses parallel function based on fitting to realize control,eliminating the process of fuzzification and de-fuzzification.2.Particle function is used to effectively reduce the complexity of multi-input and multi-output formation rules over-control.3.An adaptive fuzzy PID control method is designed based on particle function.