To address the nonlinearities and external disturbances in unstructured and complex agricultural environments,this paper investigates an autonomous trajectory tracking control method for agricultural ground vehicles.F...To address the nonlinearities and external disturbances in unstructured and complex agricultural environments,this paper investigates an autonomous trajectory tracking control method for agricultural ground vehicles.Firstly,this paper presents the design and implementation of a lightweight,modular two-wheeled differential drive vehicle equipped with two drive wheels and two caster wheels.The vehicle comprises drive wheel modules,passive wheel modules,battery modules,a vehicle frame,a sensor system,and a control system.Secondly,a novel robust trajectory tracking method was proposed,utilizing an improved pure pursuit algorithm.Additionally,an Online Particle Swarm Optimization Continuously Tuned PID(OPSO-CTPID)controller was introduced to dynamically search for optimal control gains for the PID controller.Simulation results demonstrate the superiority of the improved pure pursuit algorithm and the OPSO-CTPID control strategy.To validate the performance,the vehicle was integrated with a seeding and fertilizing machine to realize autonomous wheat seeding in an agricultural environment.Experimental outcomes reveal that the vehicle of this study completed a seeding operation exceeding 1 km in distance.The proposed method can robustly and smoothly track the desired trajectory with an accuracy of less than 10 cm for the root mean square error(RMSE)of the curve and straight lines,given a suitable set of parameters,meeting the requirements of agricultural applications.The findings of this study hold significant reference value for subsequent research on trajectory tracking algorithms for ground-based agricultural robots.展开更多
A new parameter identification method is proposed to solve the slippage problem when tracked mobile robots execute turning motions.Such motion is divided into two states in this paper:pivot turning and coupled turning...A new parameter identification method is proposed to solve the slippage problem when tracked mobile robots execute turning motions.Such motion is divided into two states in this paper:pivot turning and coupled turning between angular velocity and linear velocity.In the processing of pivot turning,the slippage parameters could be obtained by measuring the end point in a square path.In the process of coupled turning,the slippage parameters could be calculated by measuring the perimeter of a circular path and the linear distance between the start and end points.The identification results showed that slippage parameters were affected by velocity.Therefore,a fuzzy rule base was established with the basis on the identification data,and a fuzzy controller was applied to motion control and dead reckoning.This method effectively compensated for errors resulting in unequal tension between the left and right tracks,structural dimensions and slippage.The results demonstrated that the accuracy of robot positioning and control could be substantially improved on a rigid floor.展开更多
The article proposes a nonlinear optimal(H-infinity)control approach for the model of a tracked robotic vehicle.The kinematic model of such a tracked vehicle takes into account slippage effects due to the contact of t...The article proposes a nonlinear optimal(H-infinity)control approach for the model of a tracked robotic vehicle.The kinematic model of such a tracked vehicle takes into account slippage effects due to the contact of the tracks with the ground.To solve the related control problem,the dynamic model of the vehicle undergoes first approximate linearization around a temporary operating point which is updated at each iteration of the control algorithm.The linearization process relies on first-order Taylor series expansion and on the computation of the Jacobian matrices of the state-space model of the vehicle.For the approximately linearized description of the tracked vehicle a stabilizing H-infinity feedback controller is designed.To compute the controller’s feedback gains an algebraic Riccati equation is solved at each time-step of the control method.The stability properties of the control scheme are proven through Lyapunov analysis.It is also demonstrated that the control method retains the advantages of linear optimal control,that is fast and accurate tracking of reference setpoints under moderate variations of the control inputs.展开更多
In this paper, an adaptive generalized predictive control(GPC) based on hierarchical control strategy is designed for a quadrotor with a robotic arm. For this nonlinear and coupled system, a two-layer control structur...In this paper, an adaptive generalized predictive control(GPC) based on hierarchical control strategy is designed for a quadrotor with a robotic arm. For this nonlinear and coupled system, a two-layer control structure is adopted to achieve more precise trajectory tracking and keep the tracking performance after aerial grasping.The inner-layer controller is a proportional-derivative(PD) controller. The outer-layer subsystem is linearized by input-output linearization first and an adaptive generalized predictive controller is applied. The effectiveness of this approach is verified through the simulation using MATLAB/Simulink. A PD controller with feedforward control input is applied on such a system for a comparative study. Simulation results show that a better tracking performance can be achieved by the proposed strategy.展开更多
基金Jiangsu Provincial Key Research and Development Program(Grant No.BE2017301)Jiangsu Provincial Key Research and Development Program(Grant No.BE2022363)+2 种基金Project of Jiangsu Modern Agricultural Machinery Equipment&Technology Demonstration and Promotion(Grant No.NJ2022-03)National Natural Science Fund of China(Grant No.61473155)Six Talent Peaks Project in Jiangsu Province of China(Grant No.GDZB-039).
文摘To address the nonlinearities and external disturbances in unstructured and complex agricultural environments,this paper investigates an autonomous trajectory tracking control method for agricultural ground vehicles.Firstly,this paper presents the design and implementation of a lightweight,modular two-wheeled differential drive vehicle equipped with two drive wheels and two caster wheels.The vehicle comprises drive wheel modules,passive wheel modules,battery modules,a vehicle frame,a sensor system,and a control system.Secondly,a novel robust trajectory tracking method was proposed,utilizing an improved pure pursuit algorithm.Additionally,an Online Particle Swarm Optimization Continuously Tuned PID(OPSO-CTPID)controller was introduced to dynamically search for optimal control gains for the PID controller.Simulation results demonstrate the superiority of the improved pure pursuit algorithm and the OPSO-CTPID control strategy.To validate the performance,the vehicle was integrated with a seeding and fertilizing machine to realize autonomous wheat seeding in an agricultural environment.Experimental outcomes reveal that the vehicle of this study completed a seeding operation exceeding 1 km in distance.The proposed method can robustly and smoothly track the desired trajectory with an accuracy of less than 10 cm for the root mean square error(RMSE)of the curve and straight lines,given a suitable set of parameters,meeting the requirements of agricultural applications.The findings of this study hold significant reference value for subsequent research on trajectory tracking algorithms for ground-based agricultural robots.
文摘A new parameter identification method is proposed to solve the slippage problem when tracked mobile robots execute turning motions.Such motion is divided into two states in this paper:pivot turning and coupled turning between angular velocity and linear velocity.In the processing of pivot turning,the slippage parameters could be obtained by measuring the end point in a square path.In the process of coupled turning,the slippage parameters could be calculated by measuring the perimeter of a circular path and the linear distance between the start and end points.The identification results showed that slippage parameters were affected by velocity.Therefore,a fuzzy rule base was established with the basis on the identification data,and a fuzzy controller was applied to motion control and dead reckoning.This method effectively compensated for errors resulting in unequal tension between the left and right tracks,structural dimensions and slippage.The results demonstrated that the accuracy of robot positioning and control could be substantially improved on a rigid floor.
基金supported by the Research“Advances in Applied Nonlinear Optimal Control”under Grant No.6065。
文摘The article proposes a nonlinear optimal(H-infinity)control approach for the model of a tracked robotic vehicle.The kinematic model of such a tracked vehicle takes into account slippage effects due to the contact of the tracks with the ground.To solve the related control problem,the dynamic model of the vehicle undergoes first approximate linearization around a temporary operating point which is updated at each iteration of the control algorithm.The linearization process relies on first-order Taylor series expansion and on the computation of the Jacobian matrices of the state-space model of the vehicle.For the approximately linearized description of the tracked vehicle a stabilizing H-infinity feedback controller is designed.To compute the controller’s feedback gains an algebraic Riccati equation is solved at each time-step of the control method.The stability properties of the control scheme are proven through Lyapunov analysis.It is also demonstrated that the control method retains the advantages of linear optimal control,that is fast and accurate tracking of reference setpoints under moderate variations of the control inputs.
基金the National Natural Science Foundation of China(No.61773262)the China Aviation Science Foundation(No.20142057006)
文摘In this paper, an adaptive generalized predictive control(GPC) based on hierarchical control strategy is designed for a quadrotor with a robotic arm. For this nonlinear and coupled system, a two-layer control structure is adopted to achieve more precise trajectory tracking and keep the tracking performance after aerial grasping.The inner-layer controller is a proportional-derivative(PD) controller. The outer-layer subsystem is linearized by input-output linearization first and an adaptive generalized predictive controller is applied. The effectiveness of this approach is verified through the simulation using MATLAB/Simulink. A PD controller with feedforward control input is applied on such a system for a comparative study. Simulation results show that a better tracking performance can be achieved by the proposed strategy.
