Adaptive steering control of a farm tractor with varying yaw rate properties

Derrick, John; Bevly, David M.

doi:10.1002/rob.20291

Cited by 24 publications

(14 citation statements)

References 19 publications

(22 reference statements)

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“…Various implementation examples to control tractor with/without trailer system are seen in literature. In order to follow straight lines, model reference adaptive control was erdal@ntu.edu.sg proposed for the control of a tractor configured with different trailers in [1], and a linear quadratic regulator was used to control a tractor-trailer system in [2]. Both controllers have been designed based on dynamic models.…”

Section: Introductionmentioning

confidence: 99%

Robust Tube-Based Decentralized Nonlinear Model Predictive Control of an Autonomous Tractor-Trailer System

Kayacan

Ramón

et al. 2015

IEEE/ASME Trans. Mechatron.

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This paper addresses the trajectory tracking problem of an autonomous tractor-trailer system by using a decentralized control approach. A fully decentralized model predictive controller is designed in which interactions between subsystems are neglected and assumed to be perturbations to each other. In order to have a robust design, a tube-based approach is proposed to handle the differences between the nominal model and real system. Nonlinear moving horizon estimation is used for the state and parameter estimation after each new measurement, and the estimated values are fed the to robust tubebased decentralized nonlinear model predictive controller. The proposed control scheme is capable of driving the tractor-trailer system to any desired trajectory ensuring high control accuracy and robustness against neglected subsystem interactions and environmental disturbances. The experimental results show an accurate trajectory tracking performance on a bumpy grass field.Index Terms-agricultural robot, tractor-trailer system, autonomous vehicle, decentralized nonlinear model predictive control, nonlinear moving horizon estimation, tube-based nonlinear model predictive control.

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Section: Introductionmentioning

confidence: 99%

Robust Tube-Based Decentralized Nonlinear Model Predictive Control of an Autonomous Tractor-Trailer System

Kayacan

Ramón

et al. 2015

IEEE/ASME Trans. Mechatron.

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“…Various control techniques have been used to solve the trajectory tracking problem for tractors with and without trailers [8], [9]. An adaptive controller was employed for a tractor assembled with dissimilar trailers in order to track straight lines [10]. Moreover, a linear optimal control method was proposed for a tractor-trailer system [11].…”

Section: Introductionmentioning

confidence: 99%

Experimental Validation of Linear and Nonlinear MPC on an Articulated Unmanned Ground Vehicle

Kayacan

Saeys

Ramón

et al. 2018

IEEE/ASME Trans. Mechatron.

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This paper focuses on the trajectory tracking control problem for an articulated unmanned ground vehicle. We propose and compare two approaches in terms of performance and computational complexity. The first uses a nonlinear mathematical model derived from first principles and combines a nonlinear model predictive controller (NMPC) with a nonlinear moving horizon estimator (NMHE) to produce a control strategy. The second is based on an input-state linearization (ISL) of the original model followed by linear model predictive control (LMPC). A fast real-time iteration scheme is proposed, implemented for the NMHE-NMPC framework and benchmarked against the ISL-LMPC framework, which is a traditional and cheap method. The experimental results for a time-based trajectory show that the NMHE-NMPC framework with the proposed real-time iteration scheme gives better trajectory tracking performance than the ISL-LMPC framework and the required computation time is feasible for real-time applications. Moreover, the ISL-LMPC produces results of a quality comparable to the NMHE-NMPC framework at a significantly reduced computational cost.

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“…Studies on intelligent tractors mainly focus on automatic navigation control, especially on the steering control and algorithms for positioning in navigation [2][3][4][5][6], and theoretical studies of automatic control of tractor speed and gear-shift schedules are lacking.…”

Section: Introductionmentioning

confidence: 99%

Research on Economic Comprehensive Control Strategies of Tractor-Planter Combinations in Planting, Including Gear-Shift and Cruise Control

Sun

et al. 2018

Energies

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An automatic control strategy for forward speed in the planting process is proposed to improve the fuel economy and reduce the labor intensity of drivers. Models of tractors with power-shift transmission (PST) and a precise pneumatic planter with an electric-driven seed metering device are built as research objects and simulated using Matlab with Simulink. The economic comprehensive control strategies for forward speed, including gear-shift schedule and cruise control strategy, are developed. Four levels control mode with different fuel economy performances are implemented to meet different driver or operation condition requirements. In addition, the control strategy is developed for the seed-metering device motor to maintain the required seed spacing in planting. Finally, the fuel economy and effectiveness of the control strategies for forward speed and planting quality are verified by simulations with Matlab/Simulink and Matlab/Stateflow. The simulation results verify the satisfactory performance of the proposed control strategies. The error of seed spacing is less than 3% when planting with speed fluctuation. Under the premise of ensuring planting quality and driver's demands, the cruise control strategies for forward speed have more significant effects on the fuel economy than previous cruise control strategies. Furthermore, the control mode with higher level has better fuel economy and a larger speed deviation range.

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Adaptive steering control of a farm tractor with varying yaw rate properties

Cited by 24 publications

References 19 publications

Robust Tube-Based Decentralized Nonlinear Model Predictive Control of an Autonomous Tractor-Trailer System

Robust Tube-Based Decentralized Nonlinear Model Predictive Control of an Autonomous Tractor-Trailer System

Experimental Validation of Linear and Nonlinear MPC on an Articulated Unmanned Ground Vehicle

Research on Economic Comprehensive Control Strategies of Tractor-Planter Combinations in Planting, Including Gear-Shift and Cruise Control

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