Design Of Self-balancing Two-wheeled Vehicle And Research On Its Stability In Wide-range

The two-wheeled vehicle is a special kind of wheeled mobile robot. Through analysis we find that the system is characteristic with multi-variables, nonlinear, strong coupling, uncertain parameters. Because it has the widespread application background and the research value , the theory and application research of nonholonomic mobile robot has gained more and more attention in the control community. This paper studies the unstable nature of self-balanced two-wheeled robot is a complex experimental device, has become an ideal control theory and the experimental control methods platform. This article studies mainly concentrates with emphasis in the following two aspects; first, the question to the self-balanced two-wheeled robot hardware circuit's design and realization; Second, this thesis focus on how to achieve stability in a wider range by means of the intelligent control and the optimum control methods.Through analyzes and profits the composition of the self-balancing two-wheeled vehicle from the domestic and foreign, Design of the two-wheeled self-balanced vehicle in the hardware circuit. With deep analysis in dynamics and kinematic, the non-linear model of the car is obtained. On the other hand,in the foundation of Analysis and research for the two-wheeled self-balanced vehicle, Considering the quite limited range of leaning angle that linear controller can be stablelized,which is unable to realize the wider range controllability in the work. Based on this kind of consideration, is seeking for wider range stable control research aspect for the two-wheeled self-balanced vehicle, we proposed two kind of control mentalities: First, apply the fuzzy-linearization method to get the model of the system and design the linear controller. Specific jobs establishes three condition partial linearization models, And designs the linear controller separately to each linearized model, studies these linear controller's input datas and output datas ,and using the ANFIS tool to obtain the fuzzy rule, thus constitutes car's fuzzy controller, Here we mainly divide two methods to realize, First, gives the ANFIS study three condition gathering datas and produce a new controller.second, gives three condition gathering datas the ANFIS study to produce separately three controllers, simultaneously affects to the nonlinear model. These two methods produce the controller obtained the wider range angle to be controllable for the nonlinear model, moreover improved system's dynamic characteristic. Finally ,based on the car nonlinear model's simplification we obtained the angle and u the two-dimensional fuzzy table in the actual utilization. Second, based on the optimum control method ,we obtain the optimum control state feedback matrix, by pole configuration. Through introduces one new optimization pole configuration method, using the linear controller control the nonlinear model, we obtained the wider range angle to be controllable, then utilized the optimization pole configuration to design the multi-spot linearization fuzzy controller, this controller not only expanded initial angle control area of the system for the nonlinear model, moreover improvement system's dynamic characteristic. Finally according to the multi-spot linearization , based on the car nonlinear model's simplification we obtained the angle and u the two-dimensional fuzzy table in the actual utilization.