Setting And Implementation Of Intelligent PID Controller Parameter

Because PID controller has easy structure and strong robustness, so PID controller still is the popular option though all kinds of new controller are developed with the development of control fields. In recent years, intelligent PID controller rise sharply along with rapid development of control theory. Intelligent PID controller is not only has the advantage of traditional PID controller, but also can lower the accuracy of building model, corresponding algorithm is became brief.FPGA means Field Programmable Gate Array, the boundaries between software and hardware is redistricted with FPGA rise, however, the requirements to large capacity, low voltage and low power consumption of FPGA products is becoming high with the improvement of people's living standards. These means the difficulty of design of FPGA is increasing. At present, engineers are keen to combine intelligence with FPGA and all kinds of intelligent products came into being.In this article, there are two methods to tune parameters of PID controller by using FPGA. The first method is fuzzy control, which firstly divides the module of fuzzy PID controller, the module mainly consist by errors generated module, fuzzy quantization module, lookup address module, fuzzy inference module, defuzzification module, manageing parameters module and PID computation module. There use graphic design approach to realize every function module, and conduct RTL-level circuit simulation by using Quartus Ⅱ9.0.The second method is ant colony optimization algorithm (ACO), which is an intelligence algorithm of group based on biological communities'evolution. This article describes every module by using verilog language, due to all kinds of function are more in the ant colony algorithm, here through the macro module to build function module, then to realize the optimization of the parameters by using program, in the process of design, here involved of large decimal, so to deal with data by using floating-point type data. Through SOPC customize CPU to control the realization of ant colony algorithm.Results show that intelligent PID controller based on fuzzy control and ant colony algorithm not only has good dynamic and static properties but also improve the accuracy of tuning parameters and adaptability of control system.