Control Problem Of Manipulators Research Articles

Force/motion control of constrained mobile manipulators including actuator dynamics

This paper deals with the force and motion control problem of holonomic constrained nonholonomic mobile manipulators by including actuator dynamics with the manipulator’s dynamics. Even though, the force/motion control problem of holonomic constrained nonholonomic mobile manipulators has been enthusiastically studied. But there is little research on the force/motion control of rigid-link electrically driven mobile manipulators. Considering the actuator dynamics together with the manipulator’s dynamics, the controller is designed not only at the dynamic level, but also at the actuator level. This class of rigid link electrically driven electromechanical systems can be disturbed with the structured and unstructured uncertainties and disturbances. The structured and unstructured uncertainties and the coupling terms between the mobile base and the robotic arm can not be handled properly by the model-based controller. Also it is not possible to get the exact knowledge of dynamical model in real applications. Therefore, a model-based control scheme is combined with the RBF neural network based model-free control scheme for the approximation of the nonlinear mechanical dynamics. In order to compensate for the deviations due to the presence of the external disturbances, friction terms, and reconstruction error of the neural network, an adaptive bound part is also added to the controller. Moreover for the approximation of the unknown electrical dynamics, RBF neural network is employed. The designed control scheme provides that the position tracking errors and the constraint force congregate to the desired levels asymptotically. The designed control scheme also controls the direct current motors, being used to provide the desired currents and torques. The Lyapunov theorem is utilized to prove the stability of the designed controller. Finally, to illustrate the designed control scheme, numerical simulation results are produced in a comparative manner to show superior robustness in coping with the uncertainties.

On global trajectory tracking control of robot manipulators in cylindrical phase space

ABSTRACT In this paper a novel approach to the global trajectory tracking control problem for manipulators is presented. The generalised coordinates of such mechanical systems include the link angles, that makes it possible to consider the trajectory tracking control problem in a cylindrical phase space. We propose a design procedure for nonlinear controller with computed feedforward of robot manipulators. Stability proof of the closed-loop system is given by constructing the Lyapunov function which is periodic in angular coordinates with a semi-definite time derivative and using the quasi-invariance principle for non-autonomous systems of ordinary differential equations. We illustrate the implementation of the controller using simulation example.

Proportional Retarded Control of Robot Manipulators

In the present contribution, a methodology to solve the tracking control problem of robot manipulators through the use of a Proportional Retarded plus Gravity (PR+G) compensation scheme is presented. The main advantage of the proposal is to avoid the necessity of velocity measurements or their estimation, which is commonly used in most control schemes, such as the proportional derivative-type controllers or the computed torque control. The design of the PR+G controller is addressed via σ-stability analysis and its performance is tested in an experimental platform that consists of 2 degrees of the freedom robot manipulator. The proposed controller is compared with a classic proportional derivative plus gravity compensation scheme. The results are analyzed from a frequency perspective and measured by a quadratic error index.

Stress and rigidity comparison and improved vibration control of flexible carbon-fiber and epoxy-glass composite manipulators under end-point load

This paper presents the vibration control problem of the single-link flexible composite manipulators. Two different materials of composite which are epoxy-glass and carbon-fiber are considered for both simulation and experimental analyses. Manipulators are obliged to perform a job such as pick and place applications and machining a workpiece. Therefore, a payload is attached to the manipulators. If the system is suitable for loading applications, the improved vibration control method is used to suppress the residual vibrations of the manipulators. The simulation results are verified with experimental results and it is observed that the proposed vibration control method significantly reduces the residual vibrations compared to passive vibration control method in literature. Additionally, the stresses during motion are analyzed for both simulation and experiment and the effectiveness of the proposed method on the stresses is investigated. Results showed that only the carbon-fiber manipulator is suitable for payload applications and its utilization efficiency can be greatly improved by the proposed method.

Back Propagation Method of Artificial Neural Networks for Finding the Position Control of Stanford Manipulator and Direct Kinematic Analysis of Elbow Manipulator

Nowadays the robot technology is advancing rapidly and the use of robots in industries has been increasing. In designing a robot manipulator, kinematicsplays a vital role. The kinematic problem of manipulator control is divided into two types, direct kinematics and inverse kinematics. Robot inverse kinematics, which is important in robot path planning, is a fundamental problem in robotic control. Past solutions for this problem have been through the use of various algebraic or algorithmic procedures, which may be less accurate and time consuming. Artificial neural networks have the ability to approximate highly non-linear functions applied in robot control. The neural network approach deserves examination because of the fundamental properties of computation speed, and they can generalize untrained solutions. In the present work an attempt has been made to evaluate the problemof robot inverse kinematics of Stanford manipulator using artificial neural network approach. Finally two programs are written using C language to solve inverse kinematic problem of Stanford manipulator using Back propagation method of artificial neural network. In this network, the input layer has six nodes, the hidden layer has three nodes, and the output layer has two nodes. And also Elbow manipulator was modelled and its direct kinematics was analysed.

Practical continuous fractional-order nonsingular terminal sliding mode control of underwater hydraulic manipulators with valve deadband compensators

For the multi-degrees of freedom control problem of underwater hydraulic manipulators with non-ignorable valve deadband and strong lumped nonlinearities and uncertainties, a practical continuous fractional-order nonsingular terminal sliding mode control design together with a deadband compensator is presented and studied. The presented method contains three parts a time delay estimation utilized to nearly estimate and compensate the extremely complicated system dynamics, a continuous fractional-order nonsingular terminal sliding mode used to ensure high control performance against the strong lumped nonlinearities and uncertainties, and a valve deadband compensator used to compensate for the non-ignorable valve deadband. The proposed method is model-free thanks to the time delay estimation, and can ensure satisfactory control performance thanks to the continuous fractional-order nonsingular terminal sliding mode and deadband compensator. Stability of the closed-loop control system including the deadband compensator is proved rigorously. Finally, practical 2-degrees of freedom experiments are performed, and corresponding results effectively demonstrate the superiorities of the newly presented controller with deadband compensator.

Intelligent Tracking Control of Redundant Robot Manipulators including Actuator Dynamics

In this paper, the trajectory tracking control problem of redundant robot manipulators at the actuator level is studied. In the proposed control scheme, RBF (Radial Basis Function) neural network and adaptive bound part is combined with the model based controller. All the existing uncertainties are learned with the RBF neural network without offline learning. The uncertain parameters, the bounded external disturbances and the neural network reconstruction error are approximated by the adaptive bound part. The hybrid controller is designed in such a way that both the trajectory tracking error and subtask task tracking error converges to zero as well as it controls the DC motors that are used to provide the required currents and torques. Finally, the Lyapunovs stability analysis is used to prove the overall closed loop system to be asymptotically stable.

On Global Trajectory Tracking Control of Robot Manipulators with Flexible Joints

Abstract In this paper a novel approach to the global trajectory tracking control problem for manipulators with flexible joints is presented. The dynamic model of such mechanical systems has a cascade structure that allows to decouple the links dynamics from the actuators ones. We propose a design procedure for nonlinear controller with computed feedforward of robot manipulators with revolute joints in a cylindrical phase space. Stability proof of the closed-loop system is given by constructing a Lyapunov function which is periodic on angular coordinates. We illustrate the implementation of the controller using simulation example.

Robust prescribed performance tracking control for free-floating space manipulators with kinematic and dynamic uncertainty

This paper investigates the task-space prescribed performance tracking control problem of free-floating space manipulators with kinematic and dynamic uncertainty. In order to formulate and solve this prescribed performance tracking problem on SE(3), we first select a suitable tracking error vector and prescribed performance bound which characterizes the minimum convergence rate and maximum overshoot of the tracking error vector. Then, two robust tracking controllers based on the prescribed performance bound are designed to solve the tracking control problem. Compared with the existing work on the guaranteeing prescribed performance control, a linear switching surface is incorporated into the controller design procedure, which makes it easy to cope with kinematic and dynamic uncertainty. A rigorous mathematical stability proof is given. Finally, numerical simulations are presented to demonstrate the effectiveness and robustness of the proposed controller.

Zeroing neural-dynamics approach and its robust and rapid solution for parallel robot manipulators against superposition of multiple disturbances

Abstract This paper proposes a zeroing neural-dynamics (ZND) approach as well as its associated model for solving the real-time kinematic control problem of parallel robot manipulators. Unlike existing works relying on the plausibly impractical assumption that neural network models are free of external disturbances, the proposed model features the suppression of multiple disturbances in addition to its nonlinear processing and control. Theoretical analyses prove that the ZND approach and its associated model inherently possess robustness. In addition, by using an appropriate activation function, the rapid convergence performance of the corresponding ZND model is further achieved. Simulation studies and comprehensive comparisons substantiate the effectiveness, robustness and superiority of the proposed ZND approach as well as its associated model for solving the real-time kinematic control problem of parallel robot manipulators against the superposition of multiple disturbances. Moreover, results of extensive tests verify that the processing of the ZND model can be accelerated by using an appropriate activation function.

On position/force tracking control problem of cooperative robot manipulators using adaptive fuzzy backstepping approach

In this paper, the position and force tracking control problem of cooperative robot manipulator system handling a common rigid object with unknown dynamical models and unknown external disturbances is investigated. The universal approximation properties of fuzzy logic systems are employed to estimate the unknown system dynamics. On the other hand, by defining new state variables based on the integral and differential of position and orientation errors of the grasped object, the error system of coordinated robot manipulators is constructed. Subsequently by defining the appropriate change of coordinates and using the backstepping design strategy, an adaptive fuzzy backstepping position tracking control scheme is proposed for multi-robot manipulator systems. By utilizing the properties of internal forces, extra terms are also added to the control signals to consider the force tracking problem. Moreover, it is shown that the proposed adaptive fuzzy backstepping position/force control approach ensures all the signals of the closed loop system uniformly ultimately bounded and tracking errors of both positions and forces can converge to small desired values by proper selection of the design parameters. Finally, the theoretic achievements are tested on the two three-link planar robot manipulators cooperatively handling a common object to illustrate the effectiveness of the proposed approach.

Neural Network Control of a Robotic Manipulator with Time-Varying Output Constraints by State Feedback

In this paper, the control problem of uncertain n-DOF robotic manipulators with time-varying output constraints is studied. In order to solve the uncertain problem, a neural network based on radial basis function (RBF) is used to estimate the unknown dynamics of the robot manipulator. In the controller design process, we use the asymmetric barrier Lyapunov function (BLF) to avoid the violation of time-varying output constraints. Simulation results verify the effectiveness of the proposed control scheme.

Adaptive Control of Robot Manipulators With Uncertain Kinematics and Dynamics

In this paper, we investigate the adaptive control problem for robot manipulators with both the uncertain kinematics and dynamics. We propose two adaptive control schemes to realize the objective of task-space trajectory tracking irrespective of the uncertain kinematics and dynamics. The proposed controllers have the desirable separation property, and we also show that the first adaptive controller with appropriate modifications can yield improved performance, without the expense of conservative gain choice. The performance of the proposed controllers is shown by numerical simulations.

Third order sliding mode control of a medical robot for tele-echography

This paper deals with the control problem of robotic manipulators, which are always subject to nonlinear uncertainties. In particular, a dynamic system with fast actuators is exposed to many disrupting risks, generally induced by the presence of parametric uncertainties and unmoderated dynamics. So the dynamic model becomes highly nonlinear, which requires the use of a robust stabilising control. In this context, we propose a solution based on the third order sliding mode control (SMC) approach, in order to ensure a performant trajectory tracking motion control for a medical task. The proposed controller is expected to remove the standard sliding mode restrictions, to provide for a higher accuracy and robustness in realisation with respect to the current existence of imperfections. Simulation results confirm the effectiveness of the proposed third order SMC design with respect to disturbances, mainly affecting control systems.

Third order sliding mode control of a medical robot for tele-echography

This paper deals with the control problem of robotic manipulators, which are always subject to nonlinear uncertainties. In particular, a dynamic system with fast actuators is exposed to many disrupting risks, generally induced by the presence of parametric uncertainties and unmoderated dynamics. So the dynamic model becomes highly nonlinear, which requires the use of a robust stabilising control. In this context, we propose a solution based on the third order sliding mode control (SMC) approach, in order to ensure a performant trajectory tracking motion control for a medical task. The proposed controller is expected to remove the standard sliding mode restrictions, to provide for a higher accuracy and robustness in realisation with respect to the current existence of imperfections. Simulation results confirm the effectiveness of the proposed third order SMC design with respect to disturbances, mainly affecting control systems.

Control Parameters Tuning Method of Nonlinear Model Predictive Controller Based on Quantitatively Analyzing

[abstFig src='/00280005/11.jpg' width='300' text='ANMPC controller' ] The parameter-tuning method we discuss is for an Adaptive Nonlinear Model Predictive Controller (ANMPC). The MPC is optimization-based controller and decides control input to realize system output that tracks a reference trajectory through “optimal computation.” The reference trajectory is ideal trajectory of system output to converge on a desired value, i.e. controlled system performance depends on the reference trajectory. As a MPC controller which applies to the nonlinear systems, our group has already proposed an adaptive nonlinear MPC (ANMPC) for a tracking control problem of nonlinear two-link planar manipulators. This ANMPC uses a new reference trajectory having control parameters that must be tuned based on the desired controlled system’s responses and properties. To reduce troublesome parameter tuning, we propose new parameter-tuning method for ANMPC by a quantitative analysis of the relationship between a system’s behavior and ANMPC parameters. Numerically simulating the two-link nonlinear manipulator’s tracking control under various conditions demonstrates that proposed tuning method tunes the ANMPC effectively.

Fractional-order nonsingular terminal sliding mode control of hydraulic manipulators using time delay estimation

For the trajectory tracking control problem of rigid hydraulic manipulators under heavy uncertainties and nonlinearities, a novel fractional-order nonsingular terminal sliding mode (FO-NTSM) control method based on time-delay estimation (TDE) is proposed. The proposed control scheme mainly contains two parts: a TDE term and a FO-NTSM term. The TDE term is applied to approximately cancel the complex system dynamics using the intentionally time-delayed information leading to an attractive model-free nature. Meanwhile, the FO-NTSM term, based on a novel fractional-order terminal sliding surface, is designed to stabilize the tracking error to zero in finite time. Stability of the closed-loop control system is analyzed based on the Lyapunov stability theory. Finally, comparative degrees of freedom (2-DOF) practical experiments are performed and the results show that the new proposed method can ensure faster convergence rate and higher tracking precision under heavy lumped uncertainties and nonlinearities compared with its integer-order counterpart.

ℒ2 performance control of robot manipulators with kinematics, dynamics and actuator uncertainties

Summary This paper deals with the task-space trajectory tracking control problem of robot manipulators. An improved adaptive backstepping controller is proposed to deal with the uncertainties in kinematics, dynamics, and actuator modeling. To avoid the explosion of computation in conventional backstepping techniques, a modified dynamic surface control algorithm is proposed, which guarantees the asymptotic convergence rather than the uniformly ultimately boundedness of tracking errors in conventional dynamic surface control methods. Furthermore, the expression of the ℒ2 norm of tracking errors is explicitly derived in relation to the controller parameters, which provides instructions on tuning controller parameters to adjust the system performance. Moreover, the passivity structure of the designed adaptation law is thoroughly analyzed. Simulation of a free-floating space robot is used to verify the effectiveness of the proposed control strategy in comparison with the conventional tracking control schemes. Copyright © 2016 John Wiley & Sons, Ltd.

Adaptive Task-Space Cooperative Tracking Control of Networked Robotic Manipulators Without Task-Space Velocity Measurements.

In this paper, the task-space cooperative tracking control problem of networked robotic manipulators without task-space velocity measurements is addressed. To overcome the problem without task-space velocity measurements, a novel task-space position observer is designed to update the estimated task-space position and to simultaneously provide the estimated task-space velocity, based on which an adaptive cooperative tracking controller without task-space velocity measurements is presented by introducing new estimated task-space reference velocity and acceleration. Furthermore, adaptive laws are provided to cope with uncertain kinematics and dynamics and rigorous stability analysis is given to show asymptotical convergence of the task-space tracking and synchronization errors in the presence of communication delays under strongly connected directed graphs. Simulation results are given to demonstrate the performance of the proposed approach.

Intelligent Mechatronic Model Reference Theory for Robot End-effector Control

The control problem for manipulators is to determine the joint inputs required to case the endeffector execute the commanded motion. The nonminimum phase characteristic of a rigid manipulator makes the design of stable controller that ensures stringent tracking requirements a highly nontrivial and challenging problem. A useful controller in the computed torque family is the gravity controller. To compensate the dynamic parameters, fuzzy logic methodology is used and applied parallel to this method. When the arm is at rest, the only nonzero terms in the dynamic is the gravity. Proposed method can cancels the effects of the terms of gravity. In this case inorder to decrease the error and satteling time, higher gain controller is design and applied to nonlinear system.