Research On The Control System Of A Self-adaptive Two-wheel Self-balancing Robot With Variable Tilt Angle

As a new research field of mobile robots,two-wheeled self-balancing robots are favored by people for their flexible movements,zero-radius rotation,and simple structure.However,the self-balanced robot is highly difficult to control due to its high instability,multivariable,non-linear,and strong coupling characteristics.The current two-wheeled self-balancing robots still have shortcomings such as inaccurate attitude feedback,small inclination changes,and poor dynamic performance during actual motion.In order to improve the dynamic stability of a two-wheeled self-balancing robot,a fuzzy adaptive PID control strategy based on sensor data fusion is proposed.Based on the working principle of the two-wheeled self-balancing robot,it is mathematically modeled,based on the correct establishment of the coordinate system,the dynamic modeling is performed and the state space equation of the robot is obtained.The performance analysis of the system is performed based on the robot state equation,and the correctness of the model is verified by building a simulation model.Accelerometers and gyroscopes are selected as sensors for attitude acquisition according to the robot's working characteristics.The mathematical model of the sensors is used to analyze the sources of errors,and the improved complementary filtering and Kalman filtering fusion algorithms are compared in real-time for the inclination measurement of self-balancing robots Accuracy to meet the requirements of two-wheeled self-balancing robot to obtain attitude.Considering the working characteristics of the robot's continuous and irregular change of attitude angle during actual movement,a variable inclination fuzzy PID control method with different universe scopes and variable membership functions was designed,and the designed variables were verified by MATLAB/Simulink platform simulation.Superiority of inclination fuzzy PID control.In order to verify the effectiveness of the improved filter fusion algorithm designed in this subject and the feasibility of the variable inclination fuzzy PID controller,a two-wheeled self-balancing robot experimental platform was built and the system software was designed.Based on this,the improved filter fusion algorithm and The variable inclination fuzzy PID controller is used for experimental analysis.The experimental results show that the improved Kalman filter fusion algorithm solves the shortcomings of complementary filtering,large jitter,small drift and other defects,and is more superior in self-balancing robot control.At the same time,compared with traditional PID control,the variable inclination fuzzy PID control has a stronger adaptive ability and robustness in the process of balance and forward control.The adjustment time is shortened by 0.8s and 3s,and the overshoot is reduced by 10% and 16%.Simulation and experiments verify the effectiveness of the designed self-balancing robot control system.