Dc-dc Converter, Intelligent Control Study

PWM series type of DC-DC converter is a strong non-linear, uncertain system , and due to the characteristic of itself, control and research of DC-DC converter become more difficult. At present, most majority of control projects are still based on state-space averaging model or linear small signal model, as a result, it solved the analytical problem of steady state and dynamic state low frequency signals. Because of the strong non-linear of the system, the application scope of this simple model is limited greatly. To gain new breakthrough on the control of the DC-DC converter, we must establish a new , more precise and applied large signal discrete model, and we must develop unconventional sampling control theories. The project of intelligence control which illustrated by fuzzy control doesn't need to establish model. We can design a simpler controller based on our experience, and the experience data can be gained directly through many simulation models. Therefore , we can apply the Fuzzy control to the control of DC-DC converter, and acquire better effects. Though the advantages of the Fuzzy control are prominent, there are some disadvantages, so we must make some improvement. This paper presents the study of two Fuzzy controllers to control DC-DC converter. Accordingly ,the control effects of Fuzzy controller has distinct improvement.Genetic Algorithm is a parameter optimization algorithm which simulates the biology in nature based on the theory of evolutionism. The demand to optimization objects is lower, and it is applied extensively in engineering applications and science researches. Due to the prominent ability of optimization, we can consider naturally to take the advantage of Genetic Algorithm to optimize the parameters of Fuzzy controller. This paper brings forward a kind of Fuzzy controller optimized by Genetic Algorithm to control DC-DC converter, and makes some improvement to the traditional Genetic Algorithm to improve the ability of optimization. The Fuzzy controller optimized by Genetic Algorithm which is improved has the better effects of control.