On Operation Trajectory Tracking Control Methods Of Autonomous Farming Vehicles Based On Disturbance Attenuation

With the development of intelligent agriculture,intelligent autonomous farming vehicles have been widely used in various farming operations in the field.One of the key technologies to achieving comprehensive and efficient farming operations of farming vehicles is to complete the accurate and fast-tracking of its specific operation trajectories.Due to the particularity of the operating environment and the specificity of the operation trajectory,the trajectory tracking control of the farming vehicles has two featured challenges that are different from other road vehicles: how to deal with the influence of system uncertainties caused by soft and uneven fields on the accurate and fast-tracking of the predefined trajectory,and how to solve the accurate and fast-tracking control problem of alternately repeated trajectories containing straight lines and specific curves.Therefore,this dissertation conducts in-depth theoretical research on farming vehicles’ operation trajectory tracking control considering the influence of uncertainties.The main research contents of this dissertation are as follows:Considering the slip disturbance caused by the special operating environment,the disturbance-estimation-based trajectory tracking control strategies are studied.Firstly,an adaptive finite time trajectory tracking control strategy with an adaptive extended state observer is designed to improve farming vehicles’ tracking speed and accuracy.Secondly,to further improve the robustness of trajectory tracking control and the accuracy and convergence rate of unknown time-varying disturbance estimation,a trajectory tracking control strategy integrating finite time disturbance observer and nonsingular fast terminal sliding mode(NFTSM)is designed.In NFTSM construction and control strategy design,the sliding mode approach speed,chattering,and singularity are concerned.Given the repetitive characteristics of the farming vehicle’ specific trajectory,a finite-time repetitive trajectory tracking control strategy combined with the equivalent input disturbance(EID)approach is studied to improve the speed and accuracy of farming vehicle repetitive trajectory tracking.Firstly,the convergence rate of repetitive trajectory tracking of farming vehicles is improved by introducing finite-time convergence technology.Secondly,the EID approach is used to deal with the disturbance effect and improve the precision of farming vehicle repetitive trajectory tracking control.Finally,the PSO algorithm is used to optimize the gains of the controller and the disturbance observer to overcome the shortcomings of the trial-and-error method in adjusting the control parameters and further improve the dynamic and steady-state performances of the control system.Because of the repetitive iteration characteristics formed by the specific operation trajectory of the farming vehicle,an adaptive iterative learning control strategy based on the internal model principle(IMP)is studied to improve further the dynamic performance of the farming vehicle tracking the repetitive,iterative operation trajectory.Firstly,an adaptive iterative learning control strategy based on IMP,exponential decay function,and auxiliary variable design system is designed to improve the trajectory tracking accuracy and iterative convergence speed and reduce the adverse impact of input constraints on the trajectory tracking performance of the control system.Secondly,an adaptive iterative learning trajectory tracking control strategy based on an adaptive high-order internal model(AHOIM)is designed further to improve the robustness of repetitive,iterative trajectory tracking to the iterative disturbance for the farming vehicle.In AHOIM design,the adaptive iterative learning updating law is used to estimate the unknown parameters of the high-order internal model.The MATLAB/Simulink and Car Sim co-simulation platforms are used to verify the effectiveness of all the disturbance-attenuation-based autonomous farming vehicles’ trajectory tracking control strategies designed in this dissertation.The advantages of the proposed control strategies in the aspects of accuracy,fast convergence,robustness,and adaptability are verified by comparing them with the simulation results of the existing relevant trajectory-tracking control strategies.