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Satellite Attitude Control Based On Fuzzy Sliding Mode And Neural Network

Posted on:2019-11-29Degree:MasterType:Thesis
Country:ChinaCandidate:Y J CaoFull Text:PDF
GTID:2382330548495938Subject:Engineering
Abstract/Summary:PDF Full Text Request
The attitude control system is the key to ensure that the satellite can have a high level of control performance during orbit.With the development of science and social progress,the requirements of mankind for satellites have become more and more diversified,which will lead to a more complicated satellite structure.The complexity of the structure will to some extent make the satellite attitude control system more uncertain factors in the work.Therefore,in the design of the satellite attitude control system,it is necessary to seek some superior methods to deal with these problems in order to obtain a high-level design scheme in a complex space environment.Considering the initial chaotic state of the satellite,the sliding mode variable structure control is used to solve the satellite chaos and improve the stability and accuracy of the attitude control.Considering the chattering and its negative effects of the sliding mode variable structure,the fuzzy sliding mode control method based on the exponential reaching law is used to greatly reduce the chattering until it is eliminated.However,in the control method of the anti-shake,the approximation of the complex interference in the satellite mathematical model is not fully considered.The radial basis neural network method based on the improved particle swarm is used to approximate the composite interference.The simulation results show that the hybrid fuzzy sliding mode and neural network design method not only ensures the stability of the satellite attitude control,but also eliminates the chattering of the control torque,and achieves an effective approximation to the disturbance and exhibits superior control performance.The main research content of the paper includes:Firstly,the basic knowledge of satellite attitude control is briefly introduced,including the research status at home and abroad,the definition of the relevant coordinate system,the description method of the attitude,and the establishment of the satellite attitude model.The related concepts of the chaotic system are briefly introduced,and the chaos state of the satellite when it is not added to the control is represented by simulation.The sliding mode variable structure control selected in this paper is added to the satellite chaotic system.The simulation verifies the solution to the chaotic state of satellite after adding the sliding mode variable structure control method.Secondly,the chattering weakening of the sliding mode variable structure control method is implemented by adding a reaching law.Based on the isokinetic reaching law and the sliding law variable structure control method based on the exponential reaching law,thesimulation results show that the exponential reaching law greatly weakens the buffeting.However,the simulation results show that although the buffeting of the control torque is greatly reduced but not completely eliminated,the fuzzy method is embedded into the sliding mode control based on the exponential reaching law,and the simulation verifies that the fuzzy sliding mode eliminates the control torque chatter.Then,full consideration is given to possible unknown interferences in the rigid-body satellite motion model,and neural network methods are used to approximate the interference.In order to obtain a good approximation effect,the particle swarm optimization was improved and the radial basis neural network was optimized.The simulation verified the superiority of the optimized method.Finally,in order to achieve a stable and comprehensive control of the satellite attitude,the radial basis neural network based on the improved particle swarm algorithm designed in Chapter 4 and the switching gain of the system in the sliding mode control law in Chapter 3using the fuzzy method are combined to obtain a hybrid sliding-mode and neural network control law based on an improved particle swarm optimization algorithm.The simulation results show that the fuzzy sliding mode and neural network hybrid control method is designed to improve the chaos state in the original chaotic satellite system and solve the chattering problem at the same time.The stability of the control effect is ensured when the compound interference is fully considered.
Keywords/Search Tags:attitude control, sliding mode variable structure, fuzzy method, neural network, particle swarm optimization
PDF Full Text Request
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