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Variable Universe Fuzzy Control Algorithm

Author: LiLiangFeng
Tutor: LiuXiaoYun
School: University of Electronic Science and Technology
Course: Control Theory and Control Engineering
Keywords: Fuzzy Control Variable universe Dilation factor Fuzzy Neural Network Inverted pendulum
CLC: TP273.4
Type: Master's thesis
Year: 2008
Downloads: 475
Quote: 11
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Abstract

With the rapid development of science and technology, modern industrial and engineering projects in the controlled object is more and more complex, the majority of these systems with multi-variable, strong coupling, nonlinear time-varying characteristics, it is difficult to establish a precise mathematical model. Obviously, the use of traditional control theory based on accurate mathematical model of system modeling and control is difficult to achieve; fuzzy control structure is simple and robust, and do not need to be charged with a mathematical model of the object, etc. have been widely used. Fuzzy control, however, there are also the control accuracy is not high, \Traditional variable universe fuzzy control algorithm domain of stretching factor function model expressed in these variable universe fuzzy control algorithm design, not only the problem of how to select the function model and the model parameters of the elastic factor, while ontological The expansion and contraction of the domain description is accurate; addition, the expansion and contraction factor of the input domain of these algorithms are single variable rate of change of error or an error function, because the error and error rate of change between the mutual influence of the change is a simple function The cause of the domain repeatedly adjusted. Response to these problems, this paper variable universe fuzzy control algorithm was further explore, try to use fuzzy reasoning and fuzzy neural network method to describe the universe of stretching changes in order to achieve the purpose of the universe with the system status changes constantly adjust . The main contents are as follows: 1. This paper first discusses the The traditional variable universe fuzzy control algorithm dilation factor choice, and enter the domain of elastic factor together determine the feasibility of the error and error rate of change has been studied. Response function model based on the variable universe fuzzy control algorithm to choose the difficult problem of stretching factor function model and its parameters, is designed based on the variable universe fuzzy reasoning fuzzy control algorithm. The algorithm thought of fuzzy reasoning introduced into the domain of the choice of the dilation factor, enter the domain of elastic factor determined by two variables, by a retractable factor fuzzy controller to complete the on-line adjustment of the input and output of the domain, thus avoiding the Select dilation factor function model and the model parameters. 3 For the average variable universe fuzzy control system using fuzzy reasoning description of the domain stretching change is quick and easy. But for more complex or control accuracy requirements are relatively high system, expansion factor fuzzy the controller universe fuzzy divided with the designer's subjectivity will affect the control of the accused effect. Solve this problem, this paper proposes fuzzy neural network function of the elastic factor, the algorithm also has the ability to learn language skills and neural network fuzzy inference system of domain retractable change is more appropriate. Inverted pendulum typical multi-variable, nonlinear, strong coupling naturally unstable system is ideal experimental means to test the new control theory. This paper were selected one, three and four inverted pendulum design algorithm validation and Professor Li Hongxing function model based on variable universe fuzzy control algorithm to compare. The experiments confirmed the feasibility and effectiveness of the above algorithm.

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