Journal Article•
On the Voltage-Based Control of Robot Manipulators
TL;DR: In this article, a novel approach for controlling electrically driven robot manipulators based on voltage control is presented, where feedback linearization is applied on the electrical equations of the dc motors to cancel the current terms which transfer all manipulator dynamics to the electrical circuit of motor.
Abstract: This paper presents a novel approach for controlling electrically driven robot manipulators based on voltage control. The voltage-based control is preferred comparing to torque-based control. This approach is robust in the presence of manipulator uncertainties since it is free of the manipulator model. The control law is very simple, fast response, efficient, robust, and can be used for high-speed tracking purposes. The feedback linearization is applied on the electrical equations of the dc motors to cancel the current terms which transfer all manipulator dynamics to the electrical circuit of motor. The control system is simulated for position control of the PUMA 560 robot driven by permanent magnet dc motors.
Citations
More filters
TL;DR: A robust task-space control approach using a direct adaptive Taylor series controller for electrically driven robot manipulators and the upper bound of approximation error is estimated to form a robustifying term and the asymptotic convergence of task- space tracking error and its time derivative is proven based on the stability analysis.
Abstract: This paper presents a robust task-space control approach using a direct adaptive Taylor series controller for electrically driven robot manipulators. In an adaptive Taylor series control scheme, the parameters of controller are directly tuned in order to reduce the task-space tracking error in the presence of structured and unstructured uncertainty. Also, the upper bound of approximation error is estimated to form a robustifying term and the asymptotic convergence of task-space tracking error and its time derivative is proven based on the stability analysis. Simulation results are included to verify the effectiveness of the proposed control method.
19 citations
Cites methods from "On the Voltage-Based Control of Rob..."
...The decentralized controllers have been designed based on the voltage control strategy for electrically driven robot manipulators (Fateh, 2008; Zirkohi and Fateh, 2017)....
[...]
TL;DR: In this article, an adaptive observer for robust control of robotic manipulators is proposed, where the lumped uncertainty is estimated using Chebyshev polynomials, based on strictly positive-real (SPR) Lyapunov theory, the stability of the closed-loop system can be verified.
Abstract: In this paper, an adaptive observer for robust control of robotic manipulators is proposed. The lumped uncertainty is estimated using Chebyshev polynomials. Usually, the uncertainty upper bound is required in designing observer-controller structures. However, obtaining this bound is a challenging task. To solve this problem, many uncertainty estimation techniques have been proposed in the literature based on neuro-fuzzy systems. As an alternative, in this paper, Chebyshev polynomials have been applied to uncertainty estimation due to their simpler structure and less computational load. Based on strictly-positive-real (SPR) Lyapunov theory, the stability of the closed-loop system can be verified. The Chebyshev coefficients are tuned based on the adaptation rules obtained in the stability analysis. Also, to compensate the truncation error of the Chebyshev polynomials, a continuous robust control term is designed while in previous related works, usually a discontinuous term is used. An SCARA manipulator actuated by permanent magnet DC motors is used for computer simulations. Simulation results reveal the superiority of the designed method.
18 citations
TL;DR: This paper develops a novel indirect adaptive fuzzy control for electrically driven flexible-joint robot manipulators in which a novel estimation technique is introduced to estimate the uncertainty.
Abstract: A robot manipulator including its actuators is a complex system due to the nonlinearity, uncertainty and joint flexibility. To overcome complexity, this paper develops a novel indirect adaptive fuzzy control for electrically driven flexible-joint robot manipulators in which a novel estimation technique is introduced to estimate the uncertainty. The control structure differs from the previous ones due to using the voltage control strategy instead of the torque control strategy. The control design has only one control loop whereas the commonly used control design employs two control loops. Moreover, it is a decentralized control whereas the torque-based control design is a centralized control. The required feedbacks for each controller are the motor current, joint position, joint velocity and motor velocity. Some advantages are: considering the whole robotic system including robot and its actuators as a fifth-order model, simplicity of control design, computational efficiency, good performance, and guaranteed stability. Simulation results and comparisons show the effectiveness and superiority of the control approach over two control approaches. The first approach is a modified fuzzy proportional-integral control as a torque-based control method and the second one is a robust control as a voltage-based control method.
17 citations
TL;DR: The paper shows how this drawback can be overcome by using a model-based trajectory tracking controller, which makes the closed-loop system passive from an auxiliary control input to a filtered error signal, which ensures that the access to I/O ports and the computation of the control algorithms meet timing requirements accurately.
17 citations
TL;DR: The fuzzy coordinator is used to improve the performance of control system affected by imprecise transformations including the imprecising path transformation and the approximated feedback linearization.
Abstract: This paper introduces a fuzzy coordinator as a novel application of fuzzy controller. A control transformation from the task space to the joint space is required to control a robot manipulator in the task space. Because the actuators operate in the joint space while the manipulator is controlled in the task space. A conflict between two spaces is produced due to using an imprecise transformation. Fuzzy coordinator coordinates two spaces by modifying the control transformation affected by uncertainties. The fuzzy coordinator is designed simply and operates as a robust controller. The role of fuzzy coordinator is analyzed and illustrated in the robust control of a welding robot in the task space. A circular trajectory is planned for a welding task performed by a SCARA robot. The fuzzy coordinator is then used to improve the performance of control system affected by imprecise transformations including the imprecise path transformation and the approximated feedback linearization.
17 citations
Cites background from "On the Voltage-Based Control of Rob..."
...Therefore, voltage control is preferred as compared with torque control of robot manipulator [22]....
[...]
References
More filters
Book•
01 Jan 1986
TL;DR: This chapter discusses Jacobians: Velocities and Static Forces, Robot Programming Languages and Systems, and Manipulator Dynamics, which focuses on the role of Jacobians in the control of Manipulators.
Abstract: 1. Introduction. 2. Spatial Descriptions and Transformations. 3. Manipulator Kinematics. 4. Inverse Manipulator Kinematics. 5. Jacobians: Velocities and Static Forces. 6. Manipulator Dynamics. 7. Trajectory Generation. 8. Manipulator Mechanism Design. 9. Linear Control of Manipulators. 10. Nonlinear Control of Manipulators. 11. Force Control of Manipulators. 12. Robot Programming Languages and Systems. 13. Off-Line Programming Systems.
5,992 citations
"On the Voltage-Based Control of Rob..." refers background in this paper
...Many industrial robots use a form of so called PID control law [ 21 ] as...
[...]
Book•
01 Jan 1989
TL;DR: This self-contained introduction to practical robot kinematics and dynamics includes a comprehensive treatment of robot control, providing background material on terminology and linear transformations and examples illustrating all aspects of the theory and problems.
Abstract: From the Publisher:
This self-contained introduction to practical robot kinematics and dynamics includes a comprehensive treatment of robot control. Provides background material on terminology and linear transformations, followed by coverage of kinematics and inverse kinematics, dynamics, manipulator control, robust control, force control, use of feedback in nonlinear systems, and adaptive control. Each topic is supported by examples of specific applications. Derivations and proofs are included in many cases. Includes many worked examples, examples illustrating all aspects of the theory, and problems.
3,736 citations
"On the Voltage-Based Control of Rob..." refers background in this paper
...The electrical circuit of the permanent magnet dc motor provides the following equation [ 14 ]...
[...]
...So far, most industrial robots are controlled by independent joint control strategy while robots are high nonlinear multi-input/multi-output systems with complex couplings [ 14 ]....
[...]
Book•
01 May 1991
TL;DR: Invention to Robotics provides both an introductory text for students coming new to the field and a survey of the state of the art for professional practitioners.
Abstract: From the Publisher:
Introduction to Robotics provides both an introductory text for students coming new to the field and a survey of the state of the art for professional practitioners.
2,354 citations
"On the Voltage-Based Control of Rob..." refers background in this paper
...Many industrial robots use a form of so called PID control law [21] as...
[...]
TL;DR: The Robotics Toolbox is a software package that allows a MATLAB user to readily create and manipulate datatypes fundamental to robotics such as homogeneous transformations, quaternions and trajectories.
Abstract: The Robotics Toolbox is a software package that allows a MATLAB user to readily create and manipulate datatypes fundamental to robotics such as homogeneous transformations, quaternions and trajectories. Functions provided, for arbitrary serial-link manipulators, include forward and inverse kinematics, Jacobians, and forward and inverse dynamics. This article introduces the Toolbox in tutorial form, with examples chosen to demonstrate a range of capabilities. The complete Toolbox and documentation is freely available via anonymous ftp.
867 citations
"On the Voltage-Based Control of Rob..." refers methods in this paper
...The simulation model of PUMA 560 [24] is used in the control system....
[...]
Book•
07 Apr 1988TL;DR: Model-based control of a robot manipulator has been studied in this paper, where the authors present the first integrated treatment of many of the most important recent developments in using detailed dynamic models of robots to improve their control.
Abstract: Model-Based Control of a Robot Manipulator presents the first integrated treatment of many of the most important recent developments in using detailed dynamic models of robots to improve their control. The authors' work on automatic identification of kinematic and dynamic parameters, feedforward position control, stability in force control, and trajectory learning has significant implications for improving performance in future robot systems. All of the main ideas discussed in this book have been validated by experiments on a direct-drive robot arm.The book addresses the issues of building accurate robot models and of applying them for high performance control. It first describes how three sets of models - the kinematic model of the links and the inertial models of the links and of rigid-body loads - can be obtained automatically using experimental data. These models are then incorporated into position control, single trajectory learning, and force control. The MIT Serial Link Direct Drive Arm, on which these models were developed and applied to control, is one of the few manipulators currently suitable for testing such concepts.Contents: Introduction. Direct Drive Arms. Kinematic Calibration. Estimation of Load Inertial Parameters. Estimation of Link Inertial Parameters. Feedforward and Computed Torque Control. Model-Based Robot Learning. Dynamic Stability Issues in Force Control. Kinematic Stability Issues in Force Control. Conclusion.Chae An is Research Staff Member, IBM T.J. Watson Research Center, Christopher Atkeson is an Assistant Professor and John Hollerbach is an Associate Professor in the MIT Department of Brain and Cognitive Sciences and the MIT Artificial Intelligence Laboratory. Model-Based Control of a Robot Manipulator is included in the Artificial Intelligence Series edited by Patrick Winston and Michael Brady.
452 citations