Intelligent Fuzzy Control for Nonlinear Processes

Abstract

The paper deals with the development of a new adaptive fuzzy control method and algorithm for nonlinear dynamic systems based on the hybrid approach using fuzzy logic and genetic techniques. The new hybrid control methodology based on adaptive switching uses the principle of control parameters adaptation for all operating points of a highly nonlinear process. The control algorithm is realized by a fuzzy controller with parameter optimization for different operating points using a genetic algorithm. Proposed theoretical results are verified on a case study dealing with control design for a nonlinear model of continuously stirred tank reactor. Obtained practical results confirm the high performance and possibility of implementation of this methodology for a broad real plants in industry.