Improving of Multivariable PI Controller with a High Gain Structure for an Irregular System by Genetic Algorithm

This paper describes an optimal design for multivariable PI controller with a high gain structure for an irregular system by genetic algorithm. PI controllers with a high gain structure leads to the asymptotic decomposition of the fast and slow modes in the closed loop system that have unique characteristics. The slow modes are asymptotically uncontrollable and unobservable; therefore، they have not role in input and output behavior. The closed-loop response is affected only from rapid poles; therefore، the system response will have quick behavior. An essential requirement of this design is that the first Markov parameter of multivariable system (the matrix product CB) must have full rank. If the CB matrix is not full rank، the measurement matrix (M) is used with internal feedback. In this structure، the measurement matrix is chosen using genetic algorithm in order to reach the stable closed-loop system and minimize interference between outputs. The research is implemented on the two kind of different systems. The results show that the response time of PI controller with a high gain structure by genetic algorithms has good behavior in comparison with other methods.