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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TL;DR: In this article, a nonlinear adaptive fuzzy estimation and compensation of uncertainty is proposed to model the uncertainty as a non-linear function of the joint position error and its time derivative, and a comparison between the proposed Nonlinear Adaptive Fuzzy Control and a Robust Nonlinear Control (NAFC) is presented.
Abstract: This paper presents a novel robust decentralized control of electrically driven robot manipulators by adaptive fuzzy estimation and compensation of uncertainty. The proposed control employs voltage control strategy, which is simpler and more efficient than the conventional strategy, the so-called torque control strategy, due to being free from manipulator dynamics. It is verified that the proposed adaptive fuzzy system can model the uncertainty as a nonlinear function of the joint position error and its time derivative. The adaptive fuzzy system has an advantage that does not employ all system states to estimate the uncertainty. The stability analysis, performance evaluation, and simulation results are presented to verify the effectiveness of the method. A comparison between the proposed Nonlinear Adaptive Fuzzy Control (NAFC) and a Robust Nonlinear Control (RNC) is presented. Both control approaches are robust with a very good tracking performance. The NAFC is superior to the RNC in the face of smooth uncertainty. In contrast, the RNC is superior to the NAFC in the face of sudden changes in uncertainty. The case study is an articulated manipulator driven by permanent magnet dc motors.
103 citations
Cites background or methods from "On the Voltage-Based Control of Rob..."
...To solve the aforementioned problems, voltage control strategy has been devoted to the electrically driven robot manipulators [11]....
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...The proposed control approach is based on the voltage control strategy [11] using the model of motor (10) which is much simpler than the model of robot manipulator (1)....
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TL;DR: In this paper, the authors used voltage control strategy to develop robust tracking control of electrically driven flexible-joint robot manipulators, which is computationally simple, decoupled, well-behaved and has a fast response.
Abstract: So far, control of robot manipulators has frequently been developed based on the torque-control strategy. However, two drawbacks may occur. First, torque-control laws are inherently involved in complexity of the manipulator dynamics characterized by nonlinearity, largeness of model, coupling, uncertainty and joint flexibility. Second, actuator dynamics may be excluded from the controller design. The novelty of this paper is the use of voltage control strategy to develop robust tracking control of electrically driven flexible-joint robot manipulators. In addition, a novel method of uncertainty estimation is introduced to obtain the control law. The proposed control approach has important advantages over the torque-control approaches due to being free of manipulator dynamics. It is computationally simple, decoupled, well-behaved and has a fast response. The control design includes two interior loops; the inner loop controls the motor position and the outer loop controls the joint position. Stability analysis is presented and performance of the control system is evaluated. Effectiveness of the proposed control approach is demonstrated by simulations using a three-joint articulated flexible-joint robot driven by permanent magnet dc motors.
98 citations
Cites background from "On the Voltage-Based Control of Rob..."
...It is found that the voltage control strategy [ 25 ] is superior to the torque-control strategy in the robust control of rigid manipulators [26] in terms of simplicity in the controller design and performance of the control system....
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TL;DR: In this article, a nonlinear tracking control of electrically driven flexible-joint manipulators using the voltage control strategy is proposed, which is based on a simple robust adaptive control under both structured and unstructured uncertainty.
Abstract: This paper is devoted to the nonlinear tracking control of electrically driven flexible-joint manipulators using the voltage control strategy. Despite the torque control laws that are involved in the complexity of manipulator dynamics, the proposed control law is free from manipulator dynamics. This novelty is for adopting the voltage control strategy to derive a simple robust adaptive control under both structured and unstructured uncertainty. The proposed control approach has a fast response with a good tracking performance under the well-behaved control efforts in the form of decentralized control. The control method is justified by the stability analysis and simulated on a flexible-joint electrically driven robot manipulator.
59 citations
Cites background or methods from "On the Voltage-Based Control of Rob..."
...The voltage control strategy is found to be superior to the torque control strategy for being free from manipulator dynamics [ 23 , 24]....
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...To control such a complicated system we propose a novel simple control using the voltage control strategy [ 23 , 24]....
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TL;DR: This paper intuitively shows that in order to perform repetitive tasks; the least common multiple (LCM) of fundamental period durations of the desired trajectories of the joints is a proper value for the fundamental period duration of the Fourier series expansion.
Abstract: This paper presents a novel control algorithm for electrically driven robot manipulators. The proposed control law is simple and model-free based on the voltage control strategy with the decentralized structure and only joint position feedback. It works for both repetitive and non-repetitive tasks. Recently, some control approaches based on the uncertainty estimation using the Fourier series have been presented. However, the proper value for the fundamental period duration has been left as an open problem. This paper addresses this issue and intuitively shows that in order to perform repetitive tasks; the least common multiple (LCM) of fundamental period durations of the desired trajectories of the joints is a proper value for the fundamental period duration of the Fourier series expansion. Selecting the LCM results in the least tracking error. Moreover, the truncation error is compensated by the proposed control law to make the tracking error as small as possible. Adaptation laws for determining the Fourier series coefficients are derived according to the stability analysis. The case study is an SCARA robot manipulator driven by permanent magnet DC motors. Simulation results and comparisons with a voltage-based controller using adaptive neuro-fuzzy systems show the effectiveness of the proposed control approach in tracking various periodic trajectories. Moreover, the experimental results on a real SCARA robot manipulator verify the successful practical implementation of the proposed controller.
58 citations
Cites background from "On the Voltage-Based Control of Rob..."
...Using (52) and its time derivative, the lumped uncertainty F(t) in (18) can be rewritten as F(t) = F1(q)̇q̈ + F2(q, q̇)q̈ + F3(q, q̇)q̇ + F4(q, q̇) (53)...
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...in which F(t) = RIa + Lİa + (Kbr−1 − In)q̇ (18)...
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TL;DR: In this paper, a robust task-space control of electrically driven robot manipulators using voltage control strategy is proposed. But, the complexity of the robust control law is high, and it requires some feedbacks of the system states which providing them may be expensive.
Abstract: This paper deals with the robust task-space control of electrically driven robot manipulators using voltage control strategy. In conventional robust control approaches, the uncertainty bound is needed to design the control law. Usually, this bound is proposed conservatively which may increase the amplitude of the control signal and damage the system. Moreover, calculation of this bound requires some feedbacks of the system states which providing them may be expensive. The novelty of this paper is proposing a robust control law in which the uncertainty bound is calculated by Legendre polynomials. Compared to conventional robust controllers, the proposed controller is simpler, less computational and requires less feedbacks. Simulation results and comparisons verify the effectiveness of the proposed control approach applied on a SCARA robot manipulator driven by permanent magnet DC motors.
50 citations
References
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TL;DR: Simulation results show that the suggested simple model-free approach can control a complex flexible-joint manipulator to meet stringent requirements for both transient and steady-state performances.
Abstract: The increased complexity of the dynamics of robots considering joint elasticity makes conventional model-based control strategies complex and difficult to synthesize. In this paper, a model-free control using integrated PID-type learning and fuzzy control for flexible-joint manipulators is proposed. Optimal PID gains can be learned by a neural network learning algorithm and then a simple standard fuzzy control could be incorporated in the overall control strategy, if needed, for enhancing the system responses. A modified recursive least squares algorithm is suggested for faster learning of the connection weights representing the PID-like gains. Simulation results show that the suggested simple model-free approach can control a complex flexible-joint manipulator to meet stringent requirements for both transient and steady-state performances.
13 citations
"On the Voltage-Based Control of Rob..." refers methods in this paper
...A model-free control was proposed using integrated PID-type learning and fuzzy control for flexible-joint manipulators [20]....
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25 Jun 2006
TL;DR: To enhance computed torque control (CTC) based method, robust neural networks (RNN) compensating control scheme is developed to compensate structured and unstructured uncertainties.
Abstract: There are many uncertainties in real dynamics system of reconfigurable manipulator that makes PID etc. traditional methods control imprecisely. Thus, robust neural networks compensating control scheme is developed to compensate structured and unstructured uncertainties to enhance computed torque control based method. Kinematics is described by POE formula and the dynamics are derived by Newton-Euler algorithm of geometric form. They are better on computation aspects and more universal on n-links model than other modeling methods for reconfigurable manipulator system proved by many researchers. Under some mild assumptions, a stability analysis guarantees that tracking errors are uniformly ultimately bounded. Finally, simulations of the proposed controller on a RRP reconfigurable manipulator demonstrate the effectiveness on satisfactory tracking performance.
3 citations
"On the Voltage-Based Control of Rob..." refers background in this paper
...For instance, the complicated control laws were proposed in robust control [3-4], adaptive control [5], and intelligent control [6-9]....
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30 Aug 2006
TL;DR: In this article, robust neural networks (RNN) compensating control scheme is developed to compensate structured and unstructured uncertainties in real dynamics system of reconfigurable manipulator that makes PID etc. control imprecisely.
Abstract: There are many uncertainties in real dynamics system of reconfigurable manipulator that makes PID etc. traditional methods control imprecisely. Thus, in this paper, to enhance computed torque control (CTC) based method, robust neural networks (RNN) compensating control scheme is developed to compensate structured and unstructured uncertainties. The controller for a RRP reconfigurable manipulator is designed, uniformly ultimately bounded (UUB) stability is proved by Lyapunov theory and simulations show its effectiveness on satisfactory tracking performance.
1 citations