This paper introduces a two-tier feedback control law for the path tracking of a mobile robot equipped with N on-axle trailers. Initially, through a recursive design process, the curvature-tracking challenge is converted into stabilizing the joint angles at predefined reference values. This design approach is straightforward and can be easily extended to configurations with multiple trailers. Using input-to-state stability analysis, we demonstrate the asymptotic stability of the closed-loop system, which is structured in cascade form. Furthermore, we reformulate the path-tracking problem as a curvature-planning challenge and propose an algorithm to determine the desired curvature for the tail trailer. The simulation results validate the effectiveness of this novel algorithm in truck-trailer systems.

Autonomous tractor–trailer robots possess a broad spectrum of applications but pose significant challenges in control due to their nonlinear and underactuated dynamics. Unlike the tractor, the motion of the trailer cannot be directly actuated, which often results in a deviation from the intended path. In this study, we introduce a novel method for generating and following trajectories that circumvent obstacles, tailored for a tractor–trailer robotic system constrained by multiple factors. Firstly, leveraging the state information of both the obstacles and the desired trajectory, we formulate an improved trajectory for obstacle avoidance using the nonlinear least squares method. Subsequently, we propose an innovative tracking controller that integrates a universal barrier function with a state transformation strategy. This amalgamation facilitates the accurate tracking of the prescribed trajectory. Our theoretical analysis substantiates that the proposed control methodology ensures exponential convergence of the line-of-sight (LOS) distance and angle tracking errors, while enhancing the transient performance. To validate the efficacy of our approach, we present a series of simulation results, which demonstrate the applicability of the developed control strategy in managing the complex dynamics of tractor–trailer robots.

With the rapid growth of the civil aviation industry, the aircraft towing and taxiing (ATT) system has gained significant attention in the literature. Due to its nonlinear and underactuated characteristics, the path tracking and control of the ATT system is a challenging issue. Therefore, in this paper, a robust adaptive cascade control structure is proposed for the path tracking of the ATT system. Firstly, the system description is established via kinematic and dynamics modeling, and the lumped system disturbance is derived for the controller design. Next, the robust adaptive cascade control structure consisting of the adaptive MPC and the CSMC or the RASMC-based dynamics controller is designed with the application of the extended Kalman filter. The system stability in the dynamics loop is verified through the Lyapunov method. The simulation results reveal that the combination of the adaptive MPC and the RASMC can provide a more accurate tracking performance and smoother trajectories under the given disturbances and uncertainties, while both ensuring passenger comfort and meeting the civil aviation regulations, indicating its potential in practical applications.