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Tractor-trailer wheeled mobile robot (TTWMR) is a robotic system that consists of a tractor module towing a trailer. Trajectory tracking is one of the challenging problems which is focused in the context of wheeled mobile robots (WMRs) that has been discussed in this paper. First, kinematic equations of TTWMR are obtained. Then, reference trajectories for tracking problem are produced. Subsequently, an output feedback kinematic control law and a dynamic Fuzzy Sliding Mode Control (FSMC) are designed for the TTWMR. The proposed controller steer the TTWMR asymptotically follow reference trajectories. Finally, experimental results of the designed controller on an experimental setup and comparison results are presented. Obtained results show the effectiveness of the proposed controller.

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Trajectory tracking is one of the main control problems in the context of Wheeled Mobile Robots (WMRs). Besides, control of underactuated systems possesses a particular complexity and importance; so it has been focused by many researchers in recent years. In this paper, these two important control subjects are discussed regarding a Tractor-Trailer Wheeled Mobile Robot (TTWMR); which includes a differential drive wheeled mobile robot towing a passive spherical wheeled trailer. The use of spherical wheels instead of standard wheels in trailer makes the robot highly underactuated with severe nonlinearities. Spherical wheels are used for the trailer to increase robots’ maneuverability. In fact, standard wheels create nonholonomic constraints by means of pure rolling and nonslip conditions, and reduce robot maneuverability. In this paper, after introducing the robot, kinematics and kinetics models are obtained, and combined as the dynamics model. Then, based on physical intuition a new controller is developed for the robot, named as Lyapaunov-PID control algorithm. Then, singularity avoidance of the proposed algorithm is discussed and the stability of the algorithm is discussed. Simulation results reveal the suitable performance of the proposed algorithm. Finally, experimental implementation results are presented which verify the simulation results.

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One of the main topics in the field of robotics is the formation control of the group of robots in trajectory tracking problem. Using organized robots has many advantages compared to using them individually. Among them the efficiency of using resources, the possibility of robots' cooperation, increasing reliability and resistance to defects can be pointed out. Therefore, formation control of multi-body robotic systems and intelligent vehicles attracted considerable attention that is discussed in this paper. First, kinematic and kinetic equations of a differential drive wheeled robot are obtained. Then, reference trajectories for tracking problem of the leader robot are produced. Next, a kinematic control law is designed for trajectory tracking of the leader robot. The proposed controller steer the leader robot asymptotically follow reference trajectories. Subsequently, a dynamic control algorithm for generating system actuator toques is designed based on feedback linearization method. Afterwards, formation control of the robots has been considered and an appropriate algorithm is designed in order to organize the follower robots in the desired configurations, meanwhile tracking control of the wheeled robot. Furthermore the stability of the presented algorithms for kinematic, dynamic and formation control laws is analyzed using Lyapunov method. Finally, obtained results for different reference paths are presented which represents the effectiveness of the proposed controller.

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One of the main topics in the field of robotics is the motion control of wheeled mobile robots. Motion control encompasses trajectory tracking and point stabilization problems. In this paper these control problems will be considered for the tractor-trailer wheeled robots and a predictive control algorithm is developed for solving these problems. Therefore first kinematic model of the tractor_trailer robot is developed. Next, reference trajectories is produced for the system. Subsequently, predictive control law is designed for the trajectory tracking and point stabilization problems. Predictive control based on the known values of reference trajectories in the future, produces the control inputs in present time. Consequently the error signal with respect to the reference trajectory in future will be used in order to control the system at the present instant of time. This method is developed for solving the aforementioned control problems and is employed on the tractor_trailer wheeled robot. As can be seen from the results, the proposed control algorithm steer the wheeled robot asymptotically follow reference trajectories. Obtained results from the implementation of the proposed method for solving trajectory tracking and point stabilization problems, demonstrate the effectiveness of the presented algorithm.

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There exist satisfactory results in the analysis of the motion control of the vehicles with the assumption of nonslip (pure rolling) condition of robot wheeles, But unfortunately in practice due to the presence of uncertainties such as sliding of wheels especially in agriculture applications where working conditions are rough the results and the quality of the control performance of the system are affected. The ideal control of wheeled systems is performed with the assumption of the existence of nonholonomic non-slip constraints, while in the real system these constraints are violated due to the presence of slippages. In this paper the problem of trajectory tracking control of wheeled vehicles in the presence of sliding is addressed. To take sliding effects into account, sliding models are introduced into the kinematic model. In other words, these effects are added as unknown parameters to the ideal kinematic model. For taking into account the sliding effects their mathematical models are introduced in system kinematic model. In another word these effects as an unknown parameters are added to the system ideal kinematics. An integrating parameter adaptation technique and backstepping control algorithm has been utilized in order to control the system. The backstepping control law is designed to track the reference trajectories and make the robot asymptotically stable around the reference trajectories. Finally, the obtained results are presented for tracking reference trajectories and comparison results shows the efficiency of using the estimation of slips in control of the system.

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