A model predictive speed tracking control approach for autonomous ground vehicles. (15th March 2017)

• Record Type: Journal Article
• Authors: Zhu, Min; Chen, Huiyan; Xiong, Guangming
• Is Part Of: Mechanical systems and signal processing. Volume 87:Part B(2017)
• Page Start: 138
• Page End: 152
• Publication Date: 2017-03-15
• Subjects: Speed tracking -- Speed control -- Autonomous ground vehicles -- Model predictive control -- Real-time optimization; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2016.03.003
• Languages: English
• ISSNs: 0888-3270

Abstract

Abstract: 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.