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Research on Intelligent Control for the Stability of a Two-wheeled Carrier in Wide-range

Author: LiWeiKe
Tutor: QuShengLi
School: Xi'an University of Electronic Science and Technology
Course: Control Theory and Control Engineering
Keywords: Two self - balanced car A wide range of stability Fuzzy linearization Adaptive Fuzzy Inference Systems
CLC: TP242
Type: Master's thesis
Year: 2008
Downloads: 335
Quote: 7
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Features two self-balanced car is a the special wheeled mobile robot multivariate analysis of dynamical systems , non-linear, strong coupling parameter uncertainty , its sports complex environment subject to nonholonomic constraints of kinematic equations , complex control tasks , the ideal platform complete path planning in the completion of the balance control , path tracking task, therefore , since the balance of the car is the study and research of various control methods . This study is concentrated in two research and control system design of intelligent control from the dynamics of the balance of the car . As the car the linear controller inclination of stable range is quite narrow , and can not constitute a practical controller This article focuses on the use of intelligent control of a wide range of self - balanced car , the two stable control problems . In conclusion, and learn from at home and abroad after two self - equilibrium trolley design , presented in cooperation with the students two self- balanced car build on the basis of the analysis of the dynamics and kinematics analysis of the introduction of the non-linearity of the car model. This work is concentrated in the Self-Balancing Robot nonlinear object large range of stable intelligent control research , mainly in two ways : first , fuzzy linear system modeling and design of linear controllers . The specific approach is to build multiple local linear model , fuzzy linear fuzzy weighted to obtain a new linear model , this new model to describe the the entire nonlinear systems in a wide range of characteristics , dynamically approximation model of the system in each point , and then accordingly design a linear controller to control the original nonlinear object . Second , the application of adaptive neuro - fuzzy control method ANFIS to obtain fuzzy control rules . The specific approach is to build multiple local linear models were designed linear controller , each linear model , the use of the the ANFIS tool for learning these the linear controller input and output data are fuzzy rules , which constitute the fuzzy control of the car devices . Finally , these two control methods do many simulation study , mainly concentrated in the the car controllable initial inclination range , system external disturbance and internal parameter perturbation , simulation results show a significant increase in the car can control the inclination range .

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CLC: > Industrial Technology > Automation technology,computer technology > Automation technology and equipment > Robotics > Robot
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