Analysis On Modeling And Study On Attitude Balance Control Strategy Of Two-wheel Self-balancing Vehicle

Because the two-wheel self-balancing vehicle based on inverted pendulum model has advantages including small occupied area and flexible movement etc, can be applied in many special environment, such as moving in narrow space or crowded office, at the same time the controlled object itself is a multivariable, underactuation and nonlinear non-stationary system, also can be treat as the research platform of testing advanced control method, therefore it became a hot spot of related engineering and theoretical research, research its mathematical model and attitude balance control method also has certain theoretical value and practical significance.According to the control performance of the two-wheel self-balancing vehicle, the hardware architecture of DSP as the control core was builded, and get the physical parameters of the real vehicle, using Lagrange equation build system dynamical model of multiple input and output. The results under the MATLAB indicate that the model is builded correctly.Aiming at the problem of noise interference and measurement error from single sensor used in attitude estimation, a attitude estimation method of data fusion was offered to gyroscope and accelerometer based on Kalman filter, this method used the Angle value from the accelerometer X, Z axis data which after arctan operation as observed quantity, by estimate the drift error from the time accumulate of gyroscope, with the constant feedback and correction, finally an optimal estimation for attitude was achieved. The results demonstrate that this method has good capability of noise suppression, and in a variety of environments the detection accuracy of vehicle attitude is improved effectively, providing a guarantee for the research of controller.Based on the study of the traditional attitude balance control method, aiming at the problem of difficult to determine weighting matrix for the conventional LQR optimal controller and the slow response caused by this, a parameter optimization method of LQR controller based on genetic algorithm is presented. Choose the linear quadratic performance index as the objective function, the optimal solution of weighting matrix Q is obtained by using global optimization search ability of genetic algorithm, thus the state feedback control rate K can be designed, and use system model for the simulation experiment. The simulation results indicate that the GA-LQR controller has better control effect than the traditional pole placement and LQR controller, the system has more quick response speed and smaller overshoot.According to the characteristics of DSP programming, the program was designed for main module of two-wheel self-balancing vehicle control system must used, and analysis the results of real-time attitude balance control by actual debug, The results demonstrate that the system model, control algorithm and programming are correct.