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.
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01 Feb 2017
TL;DR: In this article, a robust control law is proposed to solve the problem of external disturbances, parametric uncertainties and unmodeled dynamic characteristics in control engineering, and also seriously affect the performance of the controller.
Abstract: Usually, the uncertainty bound is needed to design the control law in conventional robust control approaches. However, the proposed bound may increase the amplitude of the control signal and damage the system. To solve this problem, a robust control law is proposed in this paper. The uncertainty bound of the proposed control law is calculated by Legendre polynomials. Compared to conventional robust controllers, the proposed controller is simpler, less computational and requires less feedback. By a SCARA robot manipulator control law proposed simulation, the simulation results verify the effectiveness of the proposed control approach. Introduction In the past decades, the adaptive control and robust control of robot manipulators have been extensively studied in task space [1] and joint space [2]. Robust and adaptive control are considered important because they can overcome the uncertainty between the nominal model and the actual model due to mismatches. External disturbances, parametric uncertainties and unmodeled dynamic characteristics are the main sources of uncertainty in control engineering, and also seriously affect the performance of the controller. In the early studies of robust control methods [3], controller designs are often based on nominal models. A robust control term is then added to the control law to compensate for the uncertainty, which needs to be determined by the Lyapunov stability analysis. In these methods, uncertain boundaries need to be used to determine the stability of the system and to design the control law. Normally this boundary is the upper limit of the system state and external disturbance. Therefore, all required feedback should be available, and the upper limit of parameter uncertainty and external interference should be known in advance. In addition, the linear parameterization of the manipulator kinematics equation is necessary in most robust and adaptive control methods [4]. The controller motion equation should be modeled completely to determine the regression matrix. Most of the research in the field of robot control is based on the torque control strategy (TCS). But often TCS ignores the dynamic performance of the drive. To solve this problem, a simple and convenient voltage control strategy (voltage-based controller, VCS) was proposed. Voltage-based manipulator controller stability analysis has been studied [5]. Based on the VCS, scholars have proposed different robust control methods [6,7]. Recently, a number of adaptive control methods for regressions have been proposed [8], and the uncertainty has been estimated using the Fourier series. Based on the Lyapunov stability, some adaptive rules are deduced to adjust the Fourier series coefficients. According to [9], some other orthogonal functions, such as Legendre and Chebyshev polynomials, can be approximated to continuous time functions at arbitrary precision. In this paper, we use this idea to estimate the uncertain boundary of the Robot Task Space Control for the electrodynamic robot. Based on the above analysis, this paper presents a more simple method compared with the literature [10,11]. In this paper, the lumped uncertainty for each joint is estimated. Another 7th International Conference on Education, Management, Computer and Medicine (EMCM 2016) Copyright © 2017, the Authors. Published by Atlantis Press. This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/). Advances in Computer Science Research, volume 59
Cites methods from "On the Voltage-Based Control of Rob..."
...Voltage-based manipulator controller stability analysis has been studied [5]....
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DOI•
01 Sep 2020TL;DR: The method is compared with an adaptive robust sub-controller and a Taylor-series-based adaptive robust controller, through simulations in passive range of motion and active assistive rehabilitation exercises and the results show the superiority of the proposed method in tracking performance and the time of calculations.
Abstract: This paper presents a novel optimal impedance voltage-controller for Electrically Driven Lower Limb Rehabilitation Robots (EDLR). To overcome the dynamical complexities, and handle the uncertainties, the proposed method employs an expected forward model of the actuator. The difference between this model’s output and the actual output represents the existing value of lamped uncertainty. A voltage-controller is designed based on this uncertainty estimator, which compensate for the uncertainties. Parameters of the controller have been optimized using genetic algorithms. Key contributions of this paper are I) estimation of the uncertainty by the expected model’s output, II) overcoming the changes in motor parameters, III) introducing a class of closed-loop system termed as “Repeatable”, and IV) designing an optimal impedance voltage-controller that is non-sensitive to the parameter variations. Significant merits of the approach are swift calculations, efficiency, robustness, and guaranteed stability. Furthermore, the simplicity of design, ease of implementation and model-free independent joint structure of the approach are noticeable. The method is compared with an adaptive robust sub-controller and a Taylor-series-based adaptive robust controller, through simulations in passive range of motion and active assistive rehabilitation exercises. The results show the superiority of the proposed method in tracking performance and the time of calculations.
08 May 2018
TL;DR: A novel robust control approach equipped with an adaptive Taylor series estimator for robot manipulators including actuator dynamics and the effectiveness of the proposed control approach is shown through simulations applied on the SCARA robot manipulator driven by permanent magnet dc motors.
Abstract: This paper presents a novel robust control approach equipped with an adaptive Taylor series estimator for robot manipulators including actuator dynamics. The estimator design is simple and model-free in a decentralized structure. Based on the proposed sliding mode control (SMC) design, an uncertain nonlinear function is estimated by the Taylor series estimator and employed in the structure of the SMC and the uniformly ultimately boundedness of the tracking error and its time derivative are proven via a stability analysis. Finally, the effectiveness of the proposed control approach is shown through simulations applied on the SCARA robot manipulator driven by permanent magnet dc motors.
Additional excerpts
...In the past decade, the decentralized controllers have been designed based on the voltage control strategy for electrically-driven robot manipulators [24-25]....
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Journal Article•
TL;DR: In this article, a robust fractional order control for flexible-joint electrically driven robots under imperfect transformation of control space is presented, which is free from manipulator dynamics, thus free from problems associated with t orque control strategy in the design and implementation.
Abstract: This paper presents a robust fractional order contr oller for flexible-joint electrically driven robots under imperfect transformation of control space. Th e proposed approach is free from manipulator dynamics, thus free from problems associated with t orque control strategy in the design and implementation. As a result, the proposed controlle r is simple, fast response and superior to the torque control approaches. It can guarantee robustn ess of control system to both structured and unstructured uncertainties associated with robot dy namics. The control method is verified by stability analysis. Simulation results on a two-lin k actuated flexible-joint robot show the effectiveness of the proposed control approach.
Additional excerpts
...To overcome these weaknesses, voltage control strategy was proposed [13]....
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References
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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...
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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 ]...
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...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 ]....
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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....
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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