This paper studies the tracking control of the SbW system with unknown nonlinear friction torque and the unmeasured angular velocity. An observer-based adaptive interval type-2 fuzzy logic system controller is proposed to eliminate the adverse influence of the friction torque on the SbW system. Firstly, the angular velocity of the front wheels is estimated via the observer, such that the system sensitivity to measurement noise, the hardware cost, and the structural complexity are reduced. Then, an interval type-2 fuzzy logic system (IT2 FLS) is used to model the friction torque, in which the model and parameters are not effectively identified. IT2 FLS has a more exceptional ability to deal with uncertainties than the traditional type-1 fuzzy logic system (T1 FLS), so the friction modeling based on IT2 FLS has more satisfactory effect in practical application. Finally, an adaptive interval type-2 fuzzy logic system controller is proposed to achieve excellent tracking performance. The tracking error can be guaranteed to converge asymptotically to zero by the Lyapunov stability theory. The numerical simulations and hardware-in-loop (HIL) experiments verify the effectiveness and superiority of the proposed friction modeling method and control strategy.

本文研究了具有未知非线性摩擦转矩和未测角速度的SbW系统的跟踪控制。为了消除摩擦转矩对SbW系统的不利影响，提出了一种基于观测器的自适应区间2型模糊逻辑系统控制器。首先，通过观察者估计前轮的角速度，从而降低了系统对测量噪声的敏感性，硬件成本和结构复杂性。然后，使用间隔2型模糊逻辑系统（IT2 FLS）对摩擦转矩建模，在该模型中无法有效地识别模型和参数。与传统的Type-1模糊逻辑系统（T1 FLS）相比，IT2 FLS具有更出色的处理不确定性的能力，因此，基于IT2 FLS的摩擦建模在实际应用中效果更为理想。最后，提出了一种自适应区间2型模糊逻辑系统控制器，以实现出色的跟踪性能。利用李雅普诺夫稳定性理论，可以保证跟踪误差渐近收敛到零。数值仿真和硬件在环（HIL）实验验证了所提出的摩擦建模方法和控制策略的有效性和优越性。