Design and rapid levelling control strategy of omnidirectional levelling system for tractor seat in hilly and mountainous terrain

Abstract

To address the problem of reduced comfort caused by vehicle tilt for tractor drivers in hilly terrain, a novel seat posture omnidirectional levelling system is designed, and an omnidirectional rapid levelling control strategy (QBP-PID) is proposed, which fuses Q-learning, back propagation (BP) neural network, and proportional-integral-derivative (PID) control. Firstly, an omnidirectional levelling system for seat posture is designed based on kinematic principles. On this basis, a model for the omnidirectional levelling system is established using valve-controlled hydraulic cylinder principles. Subsequently, addressing the challenge of difficult parameter tuning for the levelling system’s PID control, a multi-level parameter update strategy employing QBP-PID is proposed for rapid omnidirectional levelling control. Simulation results show that under QBP-PID control, the 15^◦ lateral levelling time is 2.98 s with an overshoot of 0.32^◦; meanwhile, longitudinal levelling time at 20^◦ is 3.41 s with an overshoot of 0.95^◦. Compared to BP-PID and PID, lateral levelling time is reduced by 18.13% and 27.66%, respectively, while longitudinal levelling time decreases by 17.63% and 31.6%, respectively. The superiority of the QBP-PID omnidirectional rapid levelling control strategy is thus demonstrated.