A Novel Approach To Improve The Performance Of FuzzyLogic Based Controllers For Systems With Wide Range disturbances And Uncertain Parameters

Abstract

Applications offuzzy logic controllers have proved that a tuning algorithm must be added to improve its perfomance against the system disturbances. The tuning methodr represent an additional costs and complexiry for implementation. This paper, presents a novel method which implies a self-tuned c o n t r o h capable of damping the system oscillations whatever the disturbance changes. Moreover, this controller is robust to a degree that permits more than 2500% parameters uncertainties to be considered. The idea of this approach is to combine two control signals, one from a conventional stabilizer, e.g. lead lag compensator, and the other from a fuzzy logic controller. The stabilizer is designed based on modal techniques for the worst case of oscillations and is independent on the system disturbance. On the other side, the ranges of membership firnetions requiredfor the design of fuzzy logic controller are selected based on the worst experience of the input/output behavior. Thefinal controller is testedfor diflerent disturbances and system parameters and the results show a satisfactoory perfomance and robustness. Referring to Fig.(l), one can understand Fuzzy Logic (FL) as a logical system, which is an extension of multivalued logic. It is almost synonymous with the theory of fuzzy sets, a theory which relates to classes of objects with entrap boundaries in which membership is a matter of degree [I]. The basic concept underlying FL is that of a linguistic variable, that'is, a variable whose values are words rather than numbers. In effect, much of FL may be viewed as a methodology for computing with words rather than numbers. Although words may be less precise than numbers, their use is closer to human intuition. Furthermore, computing with words exploits the tolerance for imprecision and thereby lowers the cost of solution. Another basic concept in FL, which plays a central role in most of its applications, is that of a fuzzy if-then rule or, simply, fuzzy rule.

A Novel SSR-Countermeasure Through Appropriate Design of the Shaftdynamic Parameters

“…In four IEEE-SSR-Biographies, published at 1976, 1979, and 1991 rupectively, holding more than 300 papers for SSR studies, it is found that in many of them the SSR-Countermeasures are only concerned with application of excitation system enhancement controllers for damping the SSR oscillations. Advanced control strategies such as fuzzy logic controllers and neural networks are also introduced to the power system stabilizers [5,14]. All the above controllers can be categorized as electrical SSR countermeasures.…”