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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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In this paper, trajectory tracking control of a wheeled mobile robot is analyzed. Wheeled mobile robot is a nonlinear system. This system including three generalized coordinates (x,y,ϕ), and a nonholonomic constraint. First, system kinematic and dynamic equations are obtained. A non-model-based control algorithm using PD-action filtered errors has been used in order to control the wheeled mobile robot. Non-model-based controllers are always more appropriate than model-based algorithms due to independency from dynamic models, lower computational costs and also robustness to uncertainties. Asymptotic stability of the closed loop system for trajectory tracking control of wheeled mobile robot has been investigated using appropriate Lyapunov function and also Barbalat’s lemma method. Finally, in order to show the effectiveness of the proposed approach simulation and experimental results have been presented. Obtained results show that without requiring a priori knowledge of plant dynamics, and with reduced computational burden, the tracking performance of the presented algorithm is quite satisfactory. Therefore, the proposed control algorithm is well suited to most industrial applications where simple efficient algorithms are more appropriate than complicated theoretical ones with massive computational burden.

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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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In this paper, a new controller is presented based on robust feedback linearization controller in combination with integral-exponential error dynamics and potential functions for tracking control of an underwater robot in an obstacle-rich environment. Underwater robots are considered as nonlinear, underactuated systems with indefinite, uncertain dynamics. In this research, by assuming a boundary for external disturbances and uncertainties a proposed robust control method has been put to use. Along with the robust feedback linearization algorithm which has been developed based on the dynamics of the nonlinear error defined for the underwater robot, and in order to avoid the obstacles, the control laws are combined with the virtual potential functions. The considered virtual potential functions make a repulsive force between the robot and the obstacles which intersect the desired path and then they bring about a safe move of the robot in obstacle-rich environments. Finally, the performance of the proposed new control algorithm is compared with the results of the implementation of classical sliding mode control laws. The results show the effectiveness of potentially directed proposed controller through obstacle-rich paths which operate far better facing obstacles.

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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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In recent years, advancements in driver assistance technology have significantly minimized the impact of human error on traffic accidents. The development of these systems is of great interest, especially for critical and accident-causing maneuvers such as critical lane change on the highway. One of the important parts of automatic lane change is the motion planning. In this research, taking into account the criteria of collision avoidance and feasibility of the path, an algorithm for the motion planning is proposed. The main innovation of the present research is that the dynamic limits and stability margins of the vehicle have been converted into quantitative criteria and considered in the motion planning. To evaluate the performance of the motion planning algorithm, the complete model of the car is used in the Carsim-Simulink software. Also, to follow the designed path, an integrated longitudinal-lateral control has been designed and implemented. The simulation results show that the proposed method provides a more accurate assessment of the trajectory dynamic feasibility in high-speed critical lane change maneuvers compared to the previous methods. This issue is especially evident for critical maneuvers where the lateral acceleration of the trajectory is more dominant than the longitudinal acceleration.