Track tension is a major factor influencing the reliability of a track. In order to reduce the risk of track peel-off, it is necessary to keep track tension constant. However, it is difficult to measure the dynamic tension during off-road operation. Based on the analysis of the relation and external forces depending on free body diagrams of the idler, idler arm, road wheel and road arm, a theoretical estimation model of track tension is built. Comparing estimation results with multibody dynamics simulation results, the rationality of track tension monitor is validated. By the aid of this monitor, a track tension control system is designed, which includes a self-tuning proportional-integral-derivative (PID) controller based on radial basis function neural network, an electro-hydraulic servo system and an idler arm. The tightness of track can be adjusted by turning the idler arm. Simulation results of the vehicle starting process indicate that the controller can reach different expected tensions quickly and accurately. Compared with a traditional PID controller, the proposed controller has a stronger anti-disturbance ability by amending control parameters online.

履带张力是影响履带可靠性的主要因素。为了降低履带脱落的风险，必须保持履带张力恒定。然而，在越野操作期间很难测量动态张力。根据惰轮、惰轮臂、负重轮和负重臂的自由体图分析其关系与外力关系，建立履带张力的理论估算模型。将估计结果与多体动力学仿真结果进行对比，验证了履带张力监测的合理性。借助该监视器，设计了履带张力控制系统，该系统包括基于径向基函数神经网络的自整定比例积分微分（PID）控制器、电液伺服系统和惰轮臂。可以通过转动惰轮臂来调整履带的松紧度。车辆启动过程的仿真结果表明，控制器可以快速准确地达到不同的预期张力。与传统的PID控制器相比，所提出的控制器通过在线修改控制参数具有更强的抗干扰能力。