Control Of Unmanned Bicycle Based On Variable Universe Fuzzy Sliding Mode

The unmanned bicycle is a typical nonlinear underactuated system with unique properties of static instability and dynamic stability.The research on the unmanned bicycle system is helpful to promote the development of the control theory of the underactuated system.At the same time,unmanned bicycles can be used as intelligent vehicles with practical application scenarios.Therefore,this paper focuses on the research of controller design,path planning,and trajectory tracking around the unmanned bicycle system.The main research contents include:Firstly,a variable universe fuzzy sliding mode controller based on extended state observer is designed for the dynamic model of the unmanned bicycle.The controller pre-adjusts the error of the system through the variable universe fuzzy controller,and then the observation value of the system variable and the estimated value of the disturbance are given by the extended state observer,and then the control variable of the system is obtained through the sliding mode controller,So as to realize the control of unmanned bicycles.Afterward,this paper combines the particle swarm algorithm to tune the core parameters of the controller,and then obtains a set of optimized parameters by minimizing the tracking error of the system and the control amount of the system.Simulation experiments show that the controller designed in this paper has a short adjustment time and strong anti-interference ability,which can better meet the control requirements of unmanned bicycles.Then,this paper studies the path planning and trajectory tracking implementation scheme of unmanned bicycles.First,the artificial potential field method is combined into the Informed RRT* global path planning algorithm to guide new nodes to expand towards the end of the path,which improves the efficiency of the algorithm’s search path,and designs a path planning objective function that incorporates angle constraints.Subsequently,this paper uses the Minimum snap algorithm to optimize the planned path to obtain a smooth trajectory and then combines the kinematics model of the bicycle to realize the trajectory tracking function of the unmanned bicycle,so that the unmanned bicycle can track the planned path while ensuring the balance of the bicycle body.Numerical simulation shows that the proposed method in this paper can effectively realize the path planning and trajectory tracking functions of unmanned bicycles in different map areas.