A model predictive speed tracking control approach for autonomous ground vehicles

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• 作者：Min ZhuAuthor Vitae ; Huiyan Chen ; ^{chen_h_y@263.net}Author Vitae ; Guangming XiongAuthor Vitae
• 关键词：Speed tracking ; Speed control ; Autonomous ground vehicles ; Model predictive control ; Real-time optimization
• 刊名：Mechanical Systems and Signal Processing
• 出版年：2017
• 出版时间：15 March 2017
• 年：2017
• 卷：87
• 期：part_PB
• 页码：138-152
• 全文大小：1657 K
• 卷排序：87

文摘

This paper presents a novel speed tracking control approach based on a model predictive control (MPC) framework for autonomous ground vehicles. A switching algorithm without calibration is proposed to determine the drive or brake control. Combined with a simple inverse longitudinal vehicle model and adaptive regulation of MPC, this algorithm can make use of the engine brake torque for various driving conditions and avoid high frequency oscillations automatically. A simplified quadratic program (QP) solving algorithm is used to reduce the computational time, and the approach has been applied in a 16-bit microcontroller. The performance of the proposed approach is evaluated via simulations and vehicle tests, which were carried out in a range of speed-profile tracking tasks. With a well-designed system structure, high-precision speed control is achieved. The system can robustly model uncertainty and external disturbances, and yields a faster response with less overshoot than a PI controller.