Trajectory Tracking Control Of Robot Research Articles

Non-Autonomous Wheeled Mobile Robot Trajectory Tracking Control Based on the Navigation via WSN

Trajectory tracking control is a major control problem in the application of the wheeled mobile robots (WMRs). However, many of the WMRs are autonomous which are equipped with several kinds of sensor to detect the position and orientation by itself, such as ultrasonic, laser, infrared and visual. This paper studies the implementation for a distributed network feedback control system and the trajectory tracking control algorithm for a non-autonomous WMR. The control system consists of a wireless sensor network (WSN) and a monitoring base station for measurement and feedback, and a non-autonomous WMR as controlled plant. To cope with the distributed and asynchronous measurements and slow response of the feedback channel, the sectional error amplitude limited algorithm is studied and the results show the system can effectively track a reference trajectory.

From Nonlinear to Fuzzy Approaches in Trajectory Tracking Control of Wheeled Mobile Robots

AbstractIn this paper, two knowledge based controllers are proposed to overcome the difficulties of a computed torque nonlinear controller (NC) in perfect trajectory tracking of nonholonomic wheeled mobile robots (WMRs). First, the effects of different dynamic models developed in angular and Cartesian coordinate systems are fully examined on the persistent excitation condition and consequently on the trajectory tracking performance of WMRs. Using the dynamic model coordinated in the Cartesian frame as the base of the NC results in perfect compensation of large position off‐tracks and unbiased estimation of the plant's unknown parameters. However, using the WMR's dynamic model with rotation angles of driving wheels as the base of nonlinear and fuzzy controllers leads to accurate orientation tracking. Through replacing the proportional and differential terms of the NC by fuzzy functions, a fuzzy nonlinear controller (FNC) is generated. Due to the complicated dynamics of the WMR in which the center of mass does not coincide with the center of rotation, the expert knowledge of fuzzy controllers is extracted considering the rotation angles and rates of driving wheels as input variables. Fuzzy tuning of the NC results in a superior tracking performance against measurement noises, though the control torques are decreased and smoothed significantly. Second, a complete fuzzy controller (FC) is generated to make perfect tracking of the WMR's position and orientation. The local stability analysis of fuzzy controllers is examined considering the corresponding analytical structures as nonlinear controllers. The superior performances of the proposed fuzzy controllers compared to those of the NCs are evaluated through simulations.

Trajectory Tracking Control of Omni-directional Wheeled Robot for Lower Limbs Rehabilitative Training

Omni-directional wheeled robot for lower limbs rehabilitative training needs to track trajectory which is set by doctors.The uncertainties of the robot and the disturbances caused by trained patient affect the tracking performances. A nonlinear robust L_2 controller is presented to solve disturbance rejection problems.Kinematics model of lower limbs rehabilitative training robot is presented,thereby,a kinematics model of the position error system is established.The tracking and uncertain disturbance rejection are formulated as an L_2 control question to design control law with backstepping algorithm in a built storage function.A trajectory tracking controller meeting the disturbance rejection requirement is constructed. Simulation and experiment results show that the proposed controller is effective.

다중 입력 T-S 퍼지 궤환 선형화 기법을 이용한 이동로봇의 궤도 추적 제어

In this paper, we propose a T-S fuzzy feedback linearization method for controlling a non-linear system with multi-input, and the method is applied for trajectory tracking control of wheeled mobile robot. First, an error dynamic equation of wheeled mobile robot is represented by a T-S fuzzy model, and then the T-S fuzzy model is transformed to a linear control system through the nonlinear fuzzy coordinate change and the nonlinear state feedback input. Simulation results showed that the trajectory tracking controller by using the proposed multi-input feedback linearization method gives better performance than the trajectory tracking controller by using the PDC(Parallel Distributed Compensation) method for controlling the T-S Fuzzy system.

Two-state trajectory tracking control of a spherical robot using neurodynamics

SUMMARYSpherical robot is a special kind of nonholonomic system that cannot be converted to chained form, which means most of the well-known control methodologies are not suitable for this system. For the trajectory tracking of BHQ-1, a spherical robot designed by our lab, a two-state trajectory tracking controller is proposed in this paper. First, the kinematic model of the robot is built using screw theory and exponential method and the controllability is proved based on the differential geometric control theory. Then to solve the two-state trajectory tracking problem of BHQ-1, a shunting model of neurodynamics and Lyapunov's direct method are combined to design a two-state trajectory tracking controller, of which the Lyapunov stability is validated. Finally, typical simulation examples, such as tracking linear, circular, and sinusoidal trajectories, are introduced to verify the effectiveness of the proposed controller. In this paper the proposed method can also be applied to the control of other spherical robots.

Adaptive observer-based trajectory tracking control of nonholonomic mobile robots

In this paper, an adaptive observer-based trajectory tracking problem is solved for nonholonomic mobile robots with uncertainties. An adaptive observer is first developed to estimate the unmeasured velocities of a mobile robot with model uncertainties. Using the designed observer and the backstepping technique, a trajectory tracking controller is designed to generate the torque as an input. Using Lyapunov stability analysis, we prove that the closed-loop system is asymptotically stable with respect to the estimation errors and tracking errors. Finally, the simulation results are presented to validate the performance and robustness of the proposed control system against uncertainties.

Dynamic Sliding Mode Controller for Trajectory Tracking Of Nonholonomic Mobile Robots

AbstractIn this paper, a Dynamic Sliding Mode Controller (DSMC) is proposed for trajectory tracking control of a nonholonomic Wheeled Mobile Robot (WMR) in which the centroid doesn't coincide to the connection center of driving wheels. This robust controller is designed based on the developed dynamical model of WMR in Cartesian coordinates, therefore, the application limits in polar coordinates is removed. The asymptotic stability and the convergence of WMR to the desired position, velocity and orientation trajectories are proved according to the Lyapanove's direct method. Simulation results show the superiority of the proposed DSMC to the recent methods.

Feedback‐linearization and fuzzy controllers for trajectory tracking of wheeled mobile robots

PurposeThe purpose of this paper is to focus on perfect trajectory tracking control of 2 DOF non‐holonomic mobile robots in which the guidance and control commands are imposed through independent driver wheels. Model‐based nonlinear controllers for these robots with unknown parameters require estimation of a specified set of the robot parameters. The effects of the proposed model dynamics in both local and global coordinate systems are fully examined on the parameter estimation and tracking performance.Design/methodology/approachDesign of suitable feedback linearization (FL) controllers for trajectory tracking control of wheeled mobile robots (WMRs) is first reviewed. A FL controller whose parameters are tuned using fuzzy computations (fuzzy if‐then rules) is then developed. In the line of the other contributions of the paper, a pure fuzzy controller that is merely based on fuzzy if‐then rules is proposed to trajectory tracking control of the mobile robots.FindingsUse of global dynamics for designing a suitable FL control system leads to a perfect compensation for initial off‐tracks. Furthermore, the estimated parameters are unbiased because the corresponding regressor/signal matrix indicates a high rank of persistent excitation. Fuzzy tuning of the controller instead of keeping the gains fixed makes the overall system more robust against measurement noises while upper bounds and fluctuations of the input torques are both remarkably reduced. The pure fuzzy controller is naturally independent of the robot dynamics and therefore, the necessity of parameter estimation algorithm is removed.Originality/valueThe paper provides some new nonlinear controllers for WMRs, in order to make perfect trajectory tracking and initial off‐tracks compensation.

吸着式車輪型壁面移動ロボットの軌道追従制御法(機械力学,計測,自動制御)

吸着式車輪型壁面移動ロボットの軌道追従制御法(機械力学,計測,自動制御)

Investigations on the Hybrid Tracking Control of an Underactuated Autonomous Underwater Robot

The problem of trajectory tracking control of an underactuated autonomous underwater robot (AUR) in a three-dimensional (3-D) space is investigated in this paper. The control of an underactuated robot is different from fully actuated robots in many aspects. In particular, these robot systems do not satisfy Brockett's necessary condition for feedback stabilization and no continuous time-invariant state feedback control law exists that makes a specified equilibrium of the closed-loop system asymptotically stable. The uncertainty of hydrodynamic parameters, along with the coupled, nonlinear dynamics of the underwater robot, also makes the navigation and tracking control a difficult task. The proposed hybrid control law is developed by combining sliding mode control (SMC) and classical proportional–integral–derivative (PID) control methods to reduce the tracking errors arising out of disturbances, as well as variations in vehicle parameters like buoyancy. Here, a trajectory planner computes the body-fixed linear and angular velocities, as well as vehicle orientations corresponding to a given 3-D inertial trajectory, which yields a feasible 6-d.o.f. trajectory. This trajectory is used to compute the control signals for the three available controllable inputs by the hybrid controller. A supervisory controller is used to switch between the SMC and PID control as per a predefined switching law. The switching function parameters are optimized using Taguchi design techniques. The effectiveness and performance of the proposed controller is investigated by comparing numerically with classical SMC and traditional linear control systems in the presence of disturbances. Numerical simulations using the full set of nonlinear equations of motion show that the controller does quite well in dealing with the plant nonlinearity and parameter uncertainties for trajectory tracking. The proposed controller response shows less tracking error without the usually present control chattering. Some practical features of this control law are also discussed.

Adaptive Reaction Control for Space Robotic Applications with Dynamic Model Uncertainty

This paper proposes adaptive control methods based on reaction dynamics for different types of space robotic systems. Reaction dynamics feature the dynamic coupling between an actively operated part and a passively moving part in a multibody robotic system. The reaction dynamics have been used to develop trajectory tracking control of a free-floating space robot or vibration suppression control of a flexible-structure-based manipulator system. However, the presence of dynamic parameter uncertainties degrades the control performance of the above-mentioned methods, since the methods require accurate values of both kinematic and dynamic parameters. To resolve such parameter uncertainties, practical adaptive control methods are proposed in this study. The proposed methods overcome two inherent difficulties in the adaptive control design of space robotic systems, such as nonlinear parameterization of the dynamic equation and uncertainties in coordinate mapping from Cartesian space to joint space. To confirm the validity of the proposed methods, numerical simulations are carried out using three-dimensional realistic models of two types of space robotic systems.

A generalized trajectory tracking controller for robot manipulators with bounded inputs

A generalized controller based on stability theory of singularly perturbed systems is proposed, to deal with the problem of bounded actuator inputs in robot trajectory tracking control. The saturation function with error-gain matrix is applied in the torque control law, which ensures the upper bound of torque inputs in any given limited range. Through appropriately setting the entries of the error-gain matrix, the tracking performance can be improved. Moreover, a pseudo signal is generated from a linear filter to substitute for the actual velocity error, eliminating the need for velocity measurements. Finally, to verify the effectiveness of the generalized controller, a new saturated controller with error-gain-contained arc tangent function is designed. Comparison experiments show that the proposed controller can strictly guarantee the bound of the torque inputs in situations with non-zero initial tracking errors, and gives a better tracking result than other controllers.

Trajectory tracking control of parallel robots in the presence of joint drive flexibility

Trajectory tracking control of parallel manipulators is aimed in the presence of flexibility at the joint drives. Joint structural damping is also considered in the dynamic model. The system is first converted into an open-tree structure by disconnecting a sufficient number of unactuated joints. The closed loops are then expressed by constraint equations. It is shown that, in a parallel robot with flexible joint drives, the acceleration level inverse dynamics equations are singular because the control torques do not have an instantaneous effect on the end-effector accelerations due to the elastic media. Eliminating the Lagrange multipliers and the intermediate variables, a fourth-order input–output relation is obtained between the actuator torques and the end-effector position variables. The proposed control law decouples and linearizes the system and achieves asymptotic stability by feedback of positions and velocities of the actuated joints and rotors. As a case study, a three degree of freedom, two legged planar parallel manipulator is simulated to illustrate the performance of the method. The end-effector desired trajectory is chosen such that the kinematic and drive singular positions are avoided.

Trajectory tracking control of mobile robot by fluid model

AbstractThis paper describes a fluid model‐based path planning of mobile robot. In previous research, the authors proposed TBSA (Time‐Based Spline Approach) for smooth motion of industrial robots [1]. The TBSA is a powerful method in industrial applications, but the future position and velocity commands must be known to use it. In the general applications of repeat motion, this assumption is acceptable. In the path planning of a mobile robot, however, the future position and velocity commands are unknown. To address the above issue, a strategy to generate the path of a mobile robot based on the fluid model is proposed in this paper. The combination of the TBSA and the generated path by the fluid model brings a smooth motion of mobile robots. © 2008 Wiley Periodicals, Inc. Electron Comm Jpn, 91(5): 41–48, 2008; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecj.10114

DECOUPLING NEURAL SLIDING MODE CONTROL FOR MULTI-LINK ROBOTS

A decoupling neural sliding mode controller is given for trajectory tracking control of multi-link robots with external disturbances and uncertain system parameter errors. Different from general combining the sliding mode control (SMC) and neural network control (NNC), this approach decouples a robot with n links into n subsystems and the state response of each subsystem can be governed by a corresponding sliding mode manifold. The whole system is controlled by a whole sliding mode manifold selected to be a global fast terminal sliding mode manifold, which guarantees that the controlled system can reach the sliding mode manifold and equilibrium point in finite time. A radius basis function (RBF) neural network is applied to learn the limit of system parameter errors and external disturbances for every subsystem, and enforce sliding mode motion by minimizing the cost function that is with respect to the distance from the sliding mode manifold. The switching gain of sliding mode control can be automatically adjusted according to system parameter errors and external disturbances by RBF neural network's learning. The controller's chattering is reduced without sacrificing robustness, even eliminated after RBF neural network's learning for a short time. Moreover, the stability of the controlled system is proven and the convergence of tracking error is also proven by Lyapnov function. Simulation results verify the performance of the control scheme.

Experimental Comparison of Control Approaches on Trajectory Tracking Control of a 3-DOF Parallel Robot

In this paper, the effect of control approaches on improvement of trajectory tracking accuracy of a 3-degree-of-freedom (DOF) planar parallel robot is studied through the experimental evaluation of four controllers: proportional-integral (PI)-type synchronized control, adaptive synchronized (A-S) control, conventional proportional-integral-differential (PID) control and adaptive control. The adaptive control and A-S control are dynamic model-based while the PID and PI-type synchronized control are not. Given the closed-loop kinematic chain mechanism structure, tracking control of the planar parallel robot may be treated as a synchronization control problem; hence, use of the synchronized-type control approaches can substantially improve tracking accuracy of the robot end-effector compared with use of the nonsynchronized-type control approaches. Further, with uncertain dynamic parameters, use of the A-S control, a model-based synchronized control approach, can, thus, improve the tracking performance. Through experiments conducted on an experimental 3-DOF planar parallel robot, the previous claims are demonstrated.

動力学モデルに基づく蛇型ロボットの軌道追従制御

動力学モデルに基づく蛇型ロボットの軌道追従制御

Trajectory tracking control of mobile robot by time‐based spline approach

AbstractA mobile robot must move without unacceptable rapid motion. To address this issue, we propose a preview controller using the time‐based spline approach. With this approach, it is also important to plan an adequate trajectory. Here an approach to trajectory planning which has the trajectory determination strategy via a virtual manipulator is proposed. Numerical and experimental results are shown to confirm the proposed algorithm. © 2005 Wiley Periodicals, Inc. Electr Eng Jpn, 151(4): 65–71, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/eej.10349

Adaptive control of free-floating space robots in Cartesian coordinates

An adaptive control scheme is proposed for the end-effector trajectory tracking control of free-floating space robots. In order to cope with the nonlinear parameterization problem of the dynamic model of the free-floating space robot system, the system is modeled as an extended robot which is composed of a pseudo-arm representing the base motions and a real robot arm. An on-line estimation of the unknown parameters along with a computed-torque controller is used to track the desired trajectory. The proposed control scheme does not require measurement of the accelerations of the base and the real robot arm. A two-link planar space robot system is simulated to illustrate the validity and effectiveness of the proposed control scheme.

Based on Hierarchical Strategy of Adaptive Tracking Control of Mobile Robots Using Backstepping Design

A hierarchical control architecture, divided into upper and lower control levels, for the trajectory tracking control of mobile robots is proposed in this paper. The objective of the upper control level is to navigate the mobile robot on the desired trajectories by means of the kinematic model. A control law based on backstepping techniques is synthesized to make the posture error asymptotically stable. On the lower control level, the dynamic model of the robot is adopted from practical viewpoint. In order to guarantee the global asymptotic stability and demanded performance, a time-varying adaptive tracking control is designed such that the generalized velocities can converge to the upper control level's inputs. A hybrid controller is developed to incorporate the kinematic controller into the dynamic controller to deal with uncertain dynamic parameters of the mobile robot. Simulation results are utilized to illustrate the effectiveness of the proposed control algorithm.