Trajectory Tracking Control Of Robot Research Articles

A hierarchical constraint approach for dynamic modeling and trajectory tracking control of a mobile robot

The dynamic modeling and trajectory tracking control of a mobile robot is handled by a hierarchical constraint approach in this study. When the wheeled mobile robot with complex generalized coordinates has structural constraints and motion constraints, the number of constraints is large and the properties of them are different. Therefore, it is difficult to get the dynamic model and trajectory tracking control force of the wheeled mobile robot at the same time. To solve the aforementioned problem, a creative hierarchical constraint approach based on the Udwadia–Kalaba theory is proposed. In this approach, constraints are classified into two levels, structural constraints are the first level and motion constraints are the second level. In the second level constraint, arbitrary initial conditions may cause the trajectory to diverge. Thus, we propose the asymptotic convergence criterion to deal with it. Then, the analytical dynamic equation and trajectory tracking control force of the wheeled mobile robot can be obtained simultaneously. To verify the effectiveness and accuracy of this methodology, a numerical simulation of a three-wheeled mobile robot is carried out.

Design Parametric Optimization Of Wall Following Robot

In recent years, the trajectory tracking control of mobile robots has been a subject of research. This aim of the work is to achieve a minimum path traveling time of the wall following robot by optimizing the design parameters of the robot. The input parameters are wheel diameter, caster wheel position and turn radius. The output parameter is the tracking time. Three levels of wheel size, castor wheel position and turn radius are considered. The methods used are Taguchi method, Hybrid Neural network fuzzy logic method and Genetic algorithm.The values obtained from neural network algorithm are very close to the experimental value.

Industrial Robot Trajectory Tracking Control Using Multi-Layer Neural Networks Trained by Iterative Learning Control

Fast and precise robot motion is needed in many industrial applications. Most industrial robot motion controllers allow externally commanded motion profiles, but the trajectory tracking performance is affected by the robot dynamics and joint servo controllers, to which users have no direct access and about which they have little information. The performance is further compromised by time delays in transmitting the external command as a setpoint to the inner control loop. This paper presents an approach for combining neural networks and iterative learning controls to improve the trajectory tracking performance for a multi-axis articulated industrial robot. For a given desired trajectory, the external command is iteratively refined using a high-fidelity dynamical simulator to compensate for the robot inner-loop dynamics. These desired trajectories and the corresponding refined input trajectories are then used to train multi-layer neural networks to emulate the dynamical inverse of the nonlinear inner-loop dynamics. We show that with a sufficiently rich training set, the trained neural networks generalize well to trajectories beyond the training set as tested in the simulator. In applying the trained neural networks to a physical robot, the tracking performance still improves but not as much as in the simulator. We show that transfer learning effectively bridges the gap between simulation and the physical robot. Finally, we test the trained neural networks on other robot models in simulation and demonstrate the possibility of a general purpose network. Development and evaluation of this methodology are based on the ABB IRB6640-180 industrial robot and ABB RobotStudio software packages.

Development of an Adaptive Trajectory Tracking Control of Wheeled Mobile Robot

Classical modeling and control methods applied to differential locomotion mobile robots generate mathematical equations that approximate the dynamics of the system and work relatively well when the system is linear in a specific range. However, they may have low accuracy when there are many variations of the dynamics over time or disturbances occur. To solve this problem, we used a recursive least squares (RLS) method that uses a discrete-time structure first-order autoregressive model with exogenous variable (ARX). We design and modify PID adaptive self-adjusting controllers in phase margin and pole allocation. The main contribution of this methodology is that it allows the permanent and online update of the robot model and the parameters of the adaptive self-adjusting PID controllers. In addition, a Lyapunov stability analysis technique was implemented for path and trajectory tracking control, this makes the errors generated in the positioning and orientation of the robot when performing a given task tend asymptotically to zero. The performance of the PID adaptive self-adjusting controllers is measured through the implementation of the criteria of the integral of the error, which allows to determine the controller of best performance, being in this case, the PID adaptive self-adjusting type in pole assignment, allowing the mobile robot greater precision in tracking the trajectories and paths assigned, as well as less mechanical and energy wear, due to its smooth and precise movements.

Fuzzy-Torque Approximation-Enhanced Sliding Mode Control for Lateral Stability of Mobile Robot

Accurate path tracking and stability are the main challenges of lateral motion control in mobile robots, especially under the situation with complex road conditions. The interaction force between robots and the external environment may cause interference, which should be considered to guarantee its path tracking performance in dynamic and uncertain environments. In this article, a flexible lateral control scheme is considered for the developed wheel-legged robot, which consists of a cubature Kalman algorithm to evaluate the centroid slip angle and the yaw rate. Furthermore, a fuzzy compensation and preview angle-enhanced sliding model controller to improve the tracking accuracy and robustness. Finally, some simulations and experimental demonstrations using the four-wheel-legged robot (BIT-NAZA) are carried out to illustrate the effectiveness and robustness, and the proposed method has achieved satisfactory results in high-precision trajectory tracking and stability control of the mobile robot.

Trajectory Tracking Control of Differential Wheeled Mobile Robots Based on Rhombic Input Constraints

Trajectory Tracking Control of Differential Wheeled Mobile Robots Based on Rhombic Input Constraints

Tracking control for lower limb rehabilitation robots based on polynomial nonlinear uncertain models

AbstractThis paper aims to propose a novel idea for the modeling and trajectory tracking control of a lower limb rehabilitation robot. A polynomial nonlinear uncertain model is established to deal with the difficulty of accurate modeling for the lower limb rehabilitation robot with complex dynamic characteristics. A high‐order nonlinear disturbance observer (HONDO) is utilized to estimate the lumped disturbance with fast time‐varying and the corresponding observer gain matrix is obtained by H∞ performance. Then an HONDO‐based composite tracking controller is designed to achieve good tracking performance of the lower limb rehabilitation robot. In addition, all solvability conditions can be directly handled by sum of squares programming, effectively avoiding the calculation problem. Finally, numerical simulations are conducted to verify the validity of the proposed method.

Trajectory Tracking Control of Multi-DOF Robot without Considering System Dynamics

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.

Robust zeroing neural network for fixed-time kinematic control of wheeled mobile robot in noise-polluted environment

Based on a new robust zeroing neural network (RZNN) model, the trajectory tracking control of a wheeled mobile robot (WMR) within fixed-time in noise-polluted environment is presented in this paper. Unlike most of the previous reported works, the RZNN model approach for trajectory tracking control of the WMR reaches fixed-time convergence and noise suppression simultaneously. Besides, detailed theoretical analysis of its convergence and robustness are provided. Numerical simulation verification is also provided to demonstrate the superior robustness and accurateness of the RZNN model approach for trajectory tracking control of the WMR in noise-polluted environment. Both of the theoretical analysis and numerical simulation results verify the effectiveness and robustness of the RZNN model approach.

Nonholonomic Wheeled Mobile Robot Trajectory Tracking Control Based on Improved Sliding Mode Variable Structure

Several research studies are conducted based on the control of wheeled mobile robots. Nonholonomy constraints associated with wheeled mobile robots have encouraged the development of highly nonlinear control techniques. Nonholonomic wheeled mobile robot systems might be exposed to numerous payloads as per the application requirements. This can affect statically or dynamically the complete system mass, inertia, the location of the center of mass, and additional hardware constraints. Due to the nonholonomic and motion limited properties of wheeled mobile robots, the precision of trajectory tracking control is poor. The nonholonomic wheeled mobile robot tracking system is therefore being explored. The kinematic model and sliding mode control model are analyzed, and the trajectory tracking control of the robot is carried out using an enhanced variable structure based on sliding mode. The shear and sliding mode controls are designed, and the control stability is reviewed to control the trajectory of a nonholonomic wheeled mobile robot. The simulation outcomes show that the projected trajectory track control technique is able to improve the mobile robot’s control, the error of a pose is small, and the linear velocity and angular speed can be controlled. Take the linear and angular velocity as the predicted trajectory.

Par4 Parallel Robot Trajectory Tracking Control Based on DMR-GWO2 and Fuzzy Predictive

Par4 Parallel Robot Trajectory Tracking Control Based on DMR-GWO2 and Fuzzy Predictive

Omnidirectional Mobile Robot Trajectory Tracking Control with Diversity of Inputs

Omnidirectional Mobile Robot Trajectory Tracking Control with Diversity of Inputs

Real-time trajectory tracking control of a parallel robot with flexible links

Real-time end-effector trajectory tracking is applied to a newly developed parallel robotic system with two highly flexible links. In contrast to previous works, which are typically based on offline precalculations or rigid model inversion, a dynamic flexible multibody model is inverted online. As the underactuated system is non-minimum phase, the inverse model needs to be rendered stable for real-time integration. Therefore, three approaches are developed for the considered robot. Firstly, output redefinition is applied by directly weighting the elastic deformations and rotations of the links. Secondly, a small counter weight is attached at an advantageous location on the robot having only a minor influence on the eigenfrequencies. Lastly, the rotational degree of freedom of the end-effector is used to stabilize the internal dynamics of the inverse model with a small motion of a rotary motor. The concepts and real-time applicability are validated within experiments which extends the related literature being highly based on theoretical investigations. The experimental end-effector tracking performance based on the three minimum phase approaches is close to the desired trajectory and clearly outperforms classical rigid body inversion.

Trajectory tracking control of delta parallel robot based on disturbance observer

Delta parallel robot is widely used in the manufacturing process of food, medicine, electronics and military industries, which is a highly nonlinear system with strongly uncertain dynamics. Therefore, there are many difficulties in the controller design of delta robot. Based on the simplified dynamic model, a nonlinear PD+ controller with nonlinear disturbance observer is proposed for Delta parallel robot in this article, which can realize high-precision trajectory tracking in high-speed and high-acceleration motion. Then, the asymptotic stability of the closed-loop system’s equilibrium point is proven by utilizing Lyapunov techniques and LaSalle’s invariance theorem. It is obvious that the proposed controller is significantly less dependent on the accuracy of the dynamic model. Besides, a disturbance observer based on the generalized momentum is constructed, which can effectively observe and compensate the disturbances. What’s more, the constructed disturbance observer avoids the calculation of the inverse of inertia matrix, which will greatly improve the response speed of the controller. The simulation results show that the proposed controller can assure better trajectory tracking accuracy in high-speed and high-acceleration motion. And the disturbance observer can effectively estimate the disturbance. The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article:This work was supported by the National Natural Science Foundation of China (grant number51474320).

Adaptive trajectory tracking control of a free-flying space robot subject to input nonlinearities

The input nonlinearities widely exist in a large range of mechanical systems. Nonetheless, they were relatively less considered in the trajectory tracking control of a space robot in the previous studies. In this paper, an adaptive neural network (NN) control method is proposed for the fast and exact trajectory tracking control of an attitude-controlled free-flying space robot subject to input nonlinearities. The parametric uncertainties and external disturbances are also taken into the consideration. First, a model-based controller is designed to track the desired trajectory of the space robot within a framework of backstepping technique. Then, an adaptive NN controller is designed by using two NNs to compensate for the lumped uncertainties caused by parametric uncertainties and external disturbances and the input nonlinearities, respectively. Rigorous theoretical analysis for the semiglobal uniform ultimate boundedness of the whole closed-loop system is provided. The proposed adaptive NN controller is structurally simple and model-independent, which makes the controller affordable for practical applications. In addition, the proposed adaptive NN controller can guarantee the position and velocity tracking errors converge to the small neighborhoods about zero even in the presence of parametric uncertainties, external disturbances, and input nonlinearities. To the best of the authors’ knowledge, there are really limited existing controllers can achieve such excellent performance in the same conditions. Numerical simulations illustrate the effectiveness and superiority of the proposed control method.

Trajectory tracking control of a wheeled mobile robot in the presence of matched uncertainties via a composite control approach

AbstractIn the present work, a novel method is devised for controlling an uncertain wheeled mobile robot (WMR) in a desired path. To achieve this objective, an optimal and robust control system with adaptive gains is combined to benefit from the advantages of both methods. In fact, applying this controller not only controls a nonlinear system robustly against uncertainties and external disturbances, but also optimizes a quadratic cost function. Also, since the upper bound of uncertainty is determined by an adaptive law, it does not need to be adjusted manually. To ensure the designed controller's finite time stability, Lyapunov theory is used. Finally, to illustrate the effectiveness of the proposed control method, a case study involving a WMR is presented. By comparing the results of this approach with those of an adaptive sliding mode control (ASMC), it is shown that the proposed controller uses less control effort, relative to the ASMC controller, to stabilize the uncertain WMR in the presence of external disturbances.

Research on a LADRC Strategy for Trajectory Tracking Control of Delta High-Speed Parallel Robots

In order to better track the planned trajectory of Delta high-speed parallel robot, this paper proposes a dynamics control strategy for Delta high-speed parallel robots based on the linear active disturbance rejection control (LADRC) strategy which realizes decoupling control through observing and compensating the coupling and internal and external disturbances between the three joints. Firstly, the structure and dynamics model of the Delta high-speed parallel robot are analyzed, respectively. Secondly, the control scheme of the Delta high-speed parallel robot dynamic LADRC strategy is constructed, and then, the system stability is analyzed. Taking a representative 8-shaped space helical variance trajectory as a given input of the system and a triangular wave as an external disturbance as given disturbance input of the system, simulations are carried out to demonstrate the effectiveness of the proposed LADRC strategy; results indicate that the system with the LADRC strategy has a good quick and precise real-time trajectory tracking and strong robustness.

Adaptive Super-Twisting Sliding Mode Control for Mobile Robots Based on High-Gain Observers

In this paper, a robust adaptive output feedback control strategy based on a sliding mode super-twisting algorithm is designed for the trajectory tracking control of a wheeled mobile robot. First, a robust adaptive law is designed to eliminate the influence of parameter uncertainties. Second, a double-power sliding mode surface is designed to improve the response speed of the robot system. Finally, a high-gain observer is employed to estimate the speed information. The stability of the closed-loop system is proved using the Lyapunov stability theorem. The effectiveness of the proposed control strategy is verified by simulation.

Parallel structure of six wheel-legged robot trajectory tracking control with heavy payload under uncertain physical interaction

PurposeThis paper aims on the trajectory tracking of the developed six wheel-legged robot with heavy load conditions under uncertain physical interaction. The accuracy of trajectory tracking and stable operation with heavy load are the main challenges of parallel mechanism for wheel-legged robots, especially in complex road conditions. To guarantee the tracking performance in an uncertain environment, the disturbances, including the internal friction, external environment interaction, should be considered in the practical robot system.Design/methodology/approachIn this paper, a fuzzy approximation-based model predictive tracking scheme (FMPC) for reliable tracking control is developed to the six wheel-legged robot, in which the fuzzy logic approximation is applied to estimate the uncertain physical interaction and external dynamics of the robot system. Meanwhile, the advanced parallel mechanism of the electric six wheel-legged robot (BIT-NAZA) is presented.FindingsCo-simulation and comparative experimental results using the BIT-NAZA robot derived from the developed hybrid control scheme indicate that the methodology can achieve satisfactory tracking performance in terms of accuracy and stability.Originality/valueThis research can provide theoretical and engineering guidance for lateral stability of intelligent robots under unknown disturbances and uncertain nonlinearities and facilitate the control performance of the mobile robots in a practical system.

Trajectory tracking control of 7-DOF redundant robot based on estimation of intention in physical human-robot interaction.

Collaborative robot has been widespread application prospect, such as homes, manufacturing, and health-care etc. In physical human-robot interaction, the external force appears inevitably in contact with environment or human, especially the interactive tasks such as trajectory tracking requirements and force compliance control. In this article, a method based on interaction intention estimation, which solve the problem of trajectory tracking accuracy and force compliance control in the same direction for the 7-DOF robot, is proposed. The increased virtual force depended on the manipuility performance index and inverse kinematic solution used the kinematic decoupling method based on the redundant angle avoid the singularity of redundant robot. Then, based on interactive intention estimation, a control strategy of variable impedance sliding mode theory in the presence of virtual force and contact force is proposed to achieve the trajectory tracking. We adopted hyperbolic tangent function to alleviate the chattering problem caused by switch function and validated the control system stability by Lyapunov theorem. Finally, Matlab simulations exhibit a 97.8% of high tracking accuracy amid the external force is 43% less than variable impedance parameters. It is therefore proved that the proposed method can achieve asymptotic tracking and the compliant behavior in physical human-robot interaction.