Reliable adaptive H∞ path following control for autonomous ground vehicles in finite frequency domain

Industry 4.0 accelerates the growth of unmanned technology that reduces the labor cost and creates high automation in manufacturing system. The automated guided vehicle which is capable of transferring materials or executing tasks without human intervention becomes a necessary system for modern unmanned factories. The study explores the guidance and control design to accomplish the common task of path-following control for unmanned ground vehicles (UGV). A complete design method is presented that includes the lateral-directional autopilot, the vector field guidance for path-following, and multi-sensor fusion. The lateral-directional autopilot produces the low-level control action, the higher level guidance indicates the course direction of UGV at every spatial point based on the lateral path error, and the accurate UGV position relies on the estimate obtained by dynamically fusing sensors with extended Kalman filter. The design parameters in every stage are analyzed theoretically first and then fine-tuned in practice. The process is clearly described in this study, and the field test results are discussed in details to verify the performance of the proposed method and demonstrate the superiority over others.

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Observer-based state-feedback robust control for path following of autonomous ground vehicles

Proceedings of the Institution of Mechanical Engineers Part I Journal of Systems and Control Engineering ◽

10.1177/0959651819851676 ◽

2019 ◽

Vol 234 (2) ◽

pp. 222-239 ◽

Cited By ~ 1

Author(s):

Pengpeng Feng ◽

Jianwu Zhang ◽

Weimiao Yang

Keyword(s):

State Feedback ◽

Longitudinal Velocity ◽

Path Following ◽

Linear Matrix ◽

Ground Vehicles ◽

Parameter Uncertainties ◽

Lateral Velocity ◽

External Disturbances ◽

Static State ◽

Autonomous Ground Vehicles

In this article, a robust [Formula: see text] observer-based static state-feedback controller is designed for the path following of autonomous ground vehicles. The Takagi–Sugeno fuzzy modeling technique is used for modeling of vehicle dynamics with varying longitudinal velocity first. Then considering the high cost of direct lateral velocity measurement, an observer is designed to estimate the value of lateral velocity. Meanwhile, a robust controller is proposed to deal with the parameter uncertainties and external disturbances simultaneously, including the variation of the tire-cornering stiffness of both front and rear tires. Afterward, the condition of designing such an observer-based controller is transformed into the feasible problem of linear matrix inequalities. Numerical simulations using a high-fidelity and full vehicle model are performed based on a Carsim–Simulink joint platform. Simulation results under different conditions and comparison with other controller show that the proposed controller is effective irrespective of the variation in the road condition, the change in the vehicle longitudinal velocity and the external disturbances.

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