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Mixed Linear Quadratic Regulator Controller Design for Path Tracking Control of Autonomous Tracked Vehicles

  • Baiyu Tian,
  • Tianliang Lin,
  • Chunhui Zhang,
  • Zhongshen Li,
  • Shengjie Fu,
  • Qihuai Chen

摘要

With the advancements in autonomous driving technology, artificial intelligence and computer science have facilitated the autonomous operation of machinery. Industrial production efficiency is enhanced by this autonomy in construction machinery. Furthermore, personal safety for machine operators is also improved. Among these advancements, path tracking control emerges as a critical component for the automation of construction machinery. It primarily focuses on the lateral and longitudinal control of the machinery, enabling stable tracking of a predefined path even under challenging operational conditions. To enhance the accuracy and robustness of path tracking, this paper proposes a mixed linear quadratic regulator (LQR) controller specifically designed for autonomous tracked vehicles. This approach uses the LQR control algorithm to suppress the noise generated by complex construction environments and accurately track the desired path. The effectiveness and practicality of this method are validated through simulation experiments.