| The satellites more and more play a major role in national economy and military affairs. A lot of business can not get away man-made satellites, for instance, correspondence, navigation, weather, and so on. With the development of the aerospace technology, the man-made satellites construction is increasingly complexity, so the flexibility problem of satellites impacting on attitude of satellite increasingly stands out, and the requirements for the flexible satellite attitude control are getting more and more complex. The flexibility structure of the satellite result in a few accidents of the control performance descend or astaticism, which indicates both classical control and modern control havn't completely solved these issues, but intelligent control basically independent of model of controlled object. The study on this line not only has certain help for design of vehicle control systems of current type satellites, but also momentous sense on control system design of large-scale space structures such as manned vehicles and space stations.In order to study new methods used in satellite attitude control, this thesis presents Mamdani type fuzzy controller and Mamdani fuzzy controller based on genetic algorithm. Then this thesis makes simulation study on the attitude stabilization control of flexible satellite and analyses control outcome.Firstly, the models of the three-axis stabilized attitude control systems of a rigid satellite and a flexible satellite with a pair of solar arrays are set up. The model is composed of kinematics equation and dynamics equation. The model of the attitude control of the three-axis satellite is decoupled under assumer and predigestion, that is to say, the model is used in simulation.Secondly, the simple genetic arithmetic (SGA) is improved. Genetic algorithms are search algorithms based on the mechanics of natural selection and natural genetics. In general, a solution of an objective function is represented as a chromosome in a string structure, and each element represents a parameter in the solution. Through a search process such as selectness, crossover and mutation operators, the choice individuals in the string structure increase with series, and finally the chromosomes will approach the global optimum. The solutions are commonly encoded as binary strings, algorism strings and Gray Code, but in dimensions and high precision continuum problem, the second is better than the first, so in this thesis, genetic algorithms uses algorism coding. Genetic operations of simple genetic algorithms (SGA) easily decrease diversity of genetic population, reduce competition of individuals and result in premature, so genetic algorithms can't find global optimum. Aimed at these problems, the bettered genetic algorithms (BGA) is put forward. It changes the roulette wheel selection into the selection based on the compositor of the fitness of individuals in population in order to improve competition of individuals. The bettered crossover accelerate search. Crossover probability and mutation probability is adaptively adjusted with population maturity degree that is on the basis of fuzzy system theory, which can increase diversity of the population and avoid premature. In the end, BGA is tested by De Jong function. The result shows the feasibility and effectiveness of BGA in overcoming premature andimproving convergence speed and accuracy.Thirdly, the thesis develops a Mamdani type fuzzy controller of the attitude stabilization of flexibility satellite's roll axis. The design of fuzzy logic controller depends on experience and expert information but the mathematics model of controlled object and fuzzy controller possesses excellent robustness. Fuzzy control system is composed of four parts—fuzzifier, information base, inference engine and defuzzifier. Utilizing language information and experiences, It shows the process of the fuzzy controller design by changing the membership function and fuzzy rules. The author carves up the interzone of membership function of attitude angle and angle variety based on experience and knowledge and establish 35 control rules based on language information. Finally, by simulation, it shows that the designed controller has strong robustness quality, performs well under small disturbance and big variance of the moment of inertia, and can well restrain the oscillation of solar arrays. But its performance is enslaved to the accumulation of experiences, strongly depending on subjective factor. Its conclusion of the rule base absolutely lies on the manual experiences of designer, so it can not assure that its purpose is optimum.Therefore, this paper presents the researches on the design process of fuzzy controller optimized by genetic algorithm. Membership function adopts floating-point coding and control rules use integer coding. Both essentially are real coding, so can be optimized together. The form of the original population does not use idiomatic randomization, instead of creating every individual according to fuzzy, which can keep diversity of the original population. The fitness adopts ITAE index that can synthetically evaluate the dynamic and static capability of control system. Using the bettered genetic algorithms in this paper, firstly author optimize the fuzzycontroller witch stabilizes the attitude of the roll axis of the flexible satellite. Comparing with the anterior fuzzy controller, the optimized controller has stronger robustness quality, it performs better. Then, without any experiences, author proceed fuzzy controller optimum design on differ angle of stability of other axes, 3.5o for pitching axis and -3.0o for yawing axis, respectively. The simulation results prove its feasibility.At the end of paper, author summarizes achievement in work, points out deficiency and brings forward the new propose.
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