Robust Sliding Mode Trajectory Tracking Controller for a Nonholonomic Spherical Mobile Robot

In this study, two different control logics have been designed for the position control of a robot with five degrees of freedom (DOFs). First, a sliding mode control with a sliding perturbation observer (SMCSPO) has been proposed. The SMCSPO is robust against perturbation, which is the sum of nonlinearities, parametric uncertainties, and external disturbances. To implement the SMCSPO, linear parameters of the system are required; however, these are difficult to identify. Moreover, it is exigent to derive the equation of motion for the multi-DOF robot. Accordingly, an integral sliding mode control (ISMC) has been designed for the position control of this multi-DOF robot. The ISMC controller does not require a mathematical model of the system. The ISMC control input applies a switching gain to compensate for the perturbation and system dynamics. In comparison with the SMCSPO, the ISMC has improved the tracking performance of the system because of its unique characteristics. Both control schemes have been implemented in MATLAB/Simulink. It has been observed that the tracking error of each ISMC joint is lower than that of the SMCSPO.

A spherical robot is a nonlinear, nonholonomic, and unstable system which increases the difficulty of the direction and trajectory tracking problem. In this study, we propose a new direction controller Hierarchical Terminal Sliding Mode Controller (HTSMC), an instruction planning controller called Model Prediction Control-based Planner (MPCBP), and a trajectory tracking framework named MPCBP-HTSMC-HSMC (MHH). The HTSMC is designed by integrating a fast terminal algorithm, a hierarchical method, the motion features of a spherical robot, and its dynamics. In addition, the new direction controller has an excellent control effect with a quick response speed and strong stability. MPCBP can obtain optimal commands that are then transmitted to the velocity and direction controller. Since the two torque controllers in MHH are all Lyapunov-based sliding mode controllers, the MHH framework may achieve optimal control performance while assuring stability. Finally, the two controllers eliminate the requirement for MPCBP's stability and dynamic constraints. Finally, hardware experiments demonstrate the efficacy of the HTSMC, MPCBP, and MHH.

Decentralized adaptive sliding mode control of a space robot actuated by control moment gyroscopes

In this paper, perfect trajectory tracking control of a non-holonomic Wheeled Mobile Robot (WMR) is tackled. First, a Sliding Mode Controller (SMC) is proposed to convergence of WMR on desired position, velocity and orientation trajectories. Due to the weak performance of the SMC against exogenous inputs, a Mamdani-type fuzzy system is designed to improve the tracking performance of the controller. However, the Fuzzy SMC (FSMC) cannot remove the chattering phenomena completely. Therefore, a supervisory Adaptive FSMC (AFSMC) is proposed to suppress the chattering effects. The superiority of the adaptive approach to the non-adaptive methods has been revealed through simulations.

The paper concerns the problem of trajectory tracking control of a four-wheeled PIAP SCOUT mobile robot with non-steered wheels. For this kind of wheeled robots, it is impossible to find kinematic relationship between robot’s body motion and motion of driven wheels, because of inherent sliding of wheels on the ground during turning. This is an important problem from the point of view of control of the robot. The approach followed in the present work relies on introducing a simple linear controller with feedback of actual yaw rate of robot’s body. The yaw velocity is measured by inexpensive MEMS gyroscope. Experiments were conducted on two kinds of floor typical for office buildings: PVC flooring and carpet flooring. Measurements of motion parameters were possible with INS technique. It was found that the proposed yaw rate controller significantly reduces the angular error of path tracking for 90 degrees turn maneuver.

Due to the under-actuated feature, the reference signals using the combination of the system outputs, whose number is larger than that of reference signal, are designed so that the number of control inputs and sliding surfaces is the same, and that the uncontrollable mode is indirectly controlled. Under the uncertain environment, the sliding-mode under-actuated control (SMUC) with the satisfaction of suitable condition is designed to asymptotically track the reference signal. Otherwise, a bounded tracking result is obtained for the mild condition. In this situation, an on-line fuzzy modeling for the uncertainty is employed to design a fuzzy model-based sliding-mode under-actuated control (FSMUC) to improve the system performance; e.g., the bounded tracking result of SMUC becomes an asymptotical tracking. The proposed hybrid fuzzy sliding-mode under-actuated control (HFSMUC) combining SMUC and FSMUC with a transition can be applied to a class of generalized, under-actuated and uncertain nonlinear systems, e.g., the trajectory tracking control of a differential mobile robot (DMR). Finally, the simulations of the HFSMUC system are presented to confirm the efficiency and effectiveness of the proposed control.

This paper presents a trajectory tracking control scheme for a three wheeled mobile robot using sliding mode control method system. The indoor mobile robot system is subject to parameter perturbation and external interference during trajectory tracking control, and the problem of slow tracking speed and large tracking error will occur. In order to improve the tracking precision, a sliding mode control algorithm based on new approach law is proposed. Firstly, the motion control model of mobile robot is established, and a sliding mode trajectory tracking controller is designed. Then adopting MATLAB to track the linear and circular trajectories, the tracking error converges to zero around 3s. Experimental results show that sliding mode control method effectively reduces sliding mode control input chattering, and the convergence speed and tracking accuracy improve. Finally, the effectiveness of the control method is thus verified in practice.

<abstract> <bold>Abstract.</bold> For the spraying mobile robot working in greenhouse, due to the inconsistency of drive motors and the rough walking surface, it is easy to track off. For the liquidity of pesticide, the load always changes even the speed jumps. Because of these uncertainties, external disturbances and the difficulty of constructing the system dynamic model, it is hard to implement the trajectory tracking control of the spraying mobile robot steadily, precisely and quickly. In order to solve the problem, a smooth sliding mode trajectory tracking control method is proposed based on the distribute control strategy for each branch. Moreover, its stability is proved using the Lyapunov function. The simulation results show that the proposed method can track the desired trajectories precisely, quickly and steadily under the strong white noise. The chattering phenomenon of the control is restrained compared to the conventional sliding mode control. The trajectory tracking performance is better than that of the fuzzy control. The designed method is easy to realize and doesn't need to construct the precise mathematical model, so, it affords an economical and convenient control method for solving the trajectory tracking problem of the greenhouse spraying mobile robot under various uncertain interferences.

PurposeThere are various uncertain and nonlinear problems in hydraulic legged robot systems, including parameter uncertainty, unmodeled dynamics and external disturbances. This study aims to eliminate uncertainties and improve the foot trajectory tracking control performance of hydraulic legged robots, a high-performance foot trajectory tracking control method based on fixed-time disturbance observers for hydraulic legged robots is proposed.Design/methodology/approachFirst, the robot leg mechanical system model and hydraulic system model of the hydraulic legged robot are established. Subsequently, two fixed-time disturbance observers are designed to address the unmatched lumped uncertainty and match lumped uncertainty in the system. Finally, the lumped uncertainties are compensated in the controller design, and the designed motion controller also achieves fixed-time stability.FindingsThrough simulation and experiments, it can be found that the proposed tracking control method based on fixed-time observers has better tracking control performance. The effectiveness and superiority of the proposed method have been verified.Originality/valueBoth the disturbance observers and the controller achieve fixed-time stability, effectively improving the performance of foot trajectory tracking control for hydraulic legged robots.

An indirect adaptive fuzzy sliding mode controller is presented for trajectory tracking control of uncertain multi-link robots. This approach combines adaptive fuzzy control and global fast sliding mode control, and adopts a global fast sliding mode manifold which can drive system to reach balance point in finite time. Three fuzzy systems are designed to learn the uncertain robot parameters and external disturbances. So the control system can automatically track the robot parameters and disturbances, and reduces chattering of the controller. Prediction estimation for robot parameters and disturbances is not needed too. The control speed is quickened by simplifying the robot structure and decreasing learning parameters of the uncertain robot. Moreover, the system stability is proved by Lyapunov principle. Simulation results verify the validity of the control scheme.

The tracking control of wheeled mobile robot is a complex problem that is encountered in robotic science. In real applications, many serious difficulties affect the control of the robot. Nonlinear model, parameters uncertainties, and external disturbances limit the study of mobile robot tracking control. To reduce the mobile robot tracking error, we propose an adaptive law based on sliding mode control applied to a nonlinear model and taking into account uncertainties. Using the Lyapunov theory, the stability and the convergence of the tracking errors are proved. Simulations are used to illustrate the efficiency of the proposed controller.

Some robust control methods have been developed in the past in order to increase tracking performance in the presence of parametric uncertainties. In the presence of parametric uncertainty, unmodelled dynamics and other sources of uncertainties, robust control laws are used. Corless-Leitmann [1] approach is a popular approach used for designing robust controllers for robot manipulators. In early application of Corless-Leitmann [1] approach to robot manipulators [2, 3], it is difficult to compute uncertainty bound precisely. Because, uncertainty bound on parameters depends on the inertia parameters, the reference trajectory and manipulator state vector. Spong [4] proposed a new robust controller for robot manipulators using the Lyapunov theory that guaranties stability of uncertain systems. In this approach, Leithmann [5] or Corless-Leithman [1] approach is used for designing the robust controller. One of the advantage of Spong’s approach [4] is that uncertainty on parameter is needed to derive robust controller and uncertainty bound parameters depends only on the inertia parameters of the robots. Yaz [6] proposed a robust control law based on Spong’s study [4] and global exponential stability of uncertain system is guaranteed. However, disturbance and unmodelled dynamics are not considered in algorithm of [4, 6]. Danesh at al [7] develop Spong’s approach [4] in such a manner that control scheme is made robust not only to uncertain inertia parameters but also to robust unmodelled dynamics and disturbances. Koo and Kim [8] introduce adaptive scheme of uncertainty bound on parameters for robust control of robot manipulators. In [8], upper uncertainty bound is not known as would be in robust controller [4] and uncertainty bound is estimated with estimation law in order to control the uncertain system. A new robust control approach is proposed by Liu and Goldenerg [9] for robot manipulators based on a decomposition of model uncertainty. Parameterized uncertainty is distinguished from unparameterized uncertainty and a compensator is designed for parameterized and unparameterized uncertainty. A decomposition-based control design framework for mechanical systems with model uncertainties is proposed by Liu [10]. In order to increases tracking performance of uncertain systems, design of uncertainty bound estimation functions are considered. For this purpose, some uncertainty bound estimation functions are developed [11-15] based on a Lyapunov function, thus, stability of

In this paper, a nonlinear robust output feedback control is proposed for a class of autonomous underwater vehicles. In specific, we consider the nonlinear mathematical model of a heavy-weight torpedo and design a sliding mode controller to achieve robust stabilization of the closed-loop system in the presence of environmental disturbances and parametric uncertainties. Lyapunovs method is used to present the closed-loop stability analysis of the system. Then, the state feedback sliding mode control law is extended to an output feedback control design using a fourth order observer. It is highlighted that the performance of the state feedback control is recovered arbitrarily fast by the proposed output feedback controller in the presence of parametric uncertainties and environmental disturbances. Finally, the performance of the proposed control design is shown using simulation.

Trajectory tracking control of space robots in task space is of great importance to space missions, which require on-orbit manipulations. This paper focuses on position and attitude tracking control of a free-floating space robot in task space. Since neither the nonlinear terms and parametric uncertainties of the dynamic model, nor the external disturbances are known, an adaptive radial basis function network based nonsingular terminal sliding mode (RBF-NTSM) control method is presented. The proposed algorithm combines the nonlinear sliding manifold with the radial basis function to improve control performance. Moreover, in order to account for actuator physical constraints, a constrained adaptive RBF-NTSM, which employs a RBF network to compensate for the limited input is developed. The adaptive updating laws acquired by Lyapunov approach guarantee the global stability of the control system and suppress chattering problems. Two examples are provided using a six-link free-floating space robot. Simulation results clearly demonstrate that the proposed constrained adaptive RBF-NTSM control method performs high precision task based on incomplete dynamic model of the space robots. In addition, the control errors converge faster and the chattering is eliminated comparing to traditional sliding mode control.

This paper was concerned with the trajectory tracking control of wheeled mobile robots using aperiodic intermittent control. By establishing the corresponding motion model of the wheeled mobile robot, a tracking control strategy was proposed based on the intermittent control approach and backstepping method. Compared to the controllers using continuous state feedback, the proposed control strategy was activated only on separate time intervals, which combined the features of closed- and open-loop control. An example was given to illustrate the effectiveness of the obtained result.