Design of fuzzy control system by a new DNA-based immune genetic algorithm

A new DNA-based immune genetic algorithm (DNA-IGA) is proposed to design a class of Takagi-Sugeno fuzzy control systems. The DNA-IGA is developed from the structures of biological immune system and DNA. The genetic operators of the method are based on the DNA genetic operations and evaluation of immune system. It uses DNA encoding method stemmed from the biological DNA to encode the design parameters of the fuzzy controllers. The DNA encoding method can significantly shorten the code length of antibodies and is suitable for complex knowledge representation. The proposed method has the local search ability and prevents the premature convergence. As a demonstration, we show how to implement the new method to optimize the design parameters of the TS fuzzy controller in control of a nonlinear system. Computer simulation indicates that the designed fuzzy controller is satisfactory