Experimental Results on the Robust and Adaptive Control of Robot Manipulators Without Velocity Measurements

Arteaga, Marco A.; Pliego‐Jiménez, Javier; Romero, José Guadalupe

doi:10.1109/tcst.2019.2945915

Cited by 24 publications

(28 citation statements)

References 16 publications

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“…To the best of our knowledge, currently, the setting parameters, including the adaptation gain, are set by a predetermined fixed value through a series of trial and error methods. [41][42][43] Predefining the setting parameters is a challenging task, because these parameters have a significant effect on the system stability, while the system condition may vary. In this paper, as an innovation, we introduce a method to find an optimal value for the adaptation gain parameter.…”

Section: Bi-level Adaptive Optimization Approachmentioning

confidence: 99%

“…However, to the best of our knowledge, they do not pay attention to the optimality of this convergence. [41][42][43] Here, we proposed an optimal adaptive rule that guarantees the optimal convergences, by solving the subproblem.…”

Section: θ(T) = Y(t)e I (T)mentioning

confidence: 99%

“…40 (5) A novel BLOP is defined to determine the optimal values of the tuning gains of adaptation rules, which were previously determined by the trial and error in the literature. [41][42][43] Accordingly, an optimal robust adaptive mechanism for parameter estimation is achieved. Therefore, the parameter estimation convergence along with the Lyapunov-based stability of the closed-loop system during the estimation is guaranteed.…”

Section: Introductionmentioning

confidence: 99%

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Bi-Level Adaptive Computed-Current Impedance Controller for Electrically Driven Robots

Jalaeian-F¹,

Fateh²,

Rahimiyan³

2020

Robotica

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SUMMARY This paper presents a bi-level adaptive computed-current impedance controller for electrically driven robots. This study aims to reduce calculation complexities by utilizing the electrical equations of actuators, instead of the entire model of the electromechanical system. Moreover, taking the dynamical effects of mechanical parts into account through the current’s feedback, external disturbances are compensated. In order to handle uncertainties, a bi-level optimization problem is formulated to obtain guaranteed stability besides the estimation convergence. An adaptation rule and its optimal tuning gain are achieved. The proposed method is applied to control of a rehabilitation robot to evaluate its performance.

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Section: Bi-level Adaptive Optimization Approachmentioning

confidence: 99%

Section: θ(T) = Y(t)e I (T)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Bi-Level Adaptive Computed-Current Impedance Controller for Electrically Driven Robots

Jalaeian-F¹,

Fateh²,

Rahimiyan³

2020

Robotica

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“…The development of the adaptive controller usually relies on the assumption of linearly parameterized system [19]. To handle the uncertain nonlinearities and external disturbance, the robust control method is usually adopted.…”

Section: Introductionmentioning

confidence: 99%

“…By adding adaptive term to a robust control algorithm, i.e. sliding mode controller, the superior performance of the proposed controller is demonstrated with an industrial robot manipulator in [19] with comparison to the controller without adaptive term. In [21], the integral suboptimal second order sliding mode control algorithm is developed to reduce the reaching phase and enhance the robustness; experimental results demonstrated the better robustness of the proposed method compared to conventional PD control.…”

Section: Introductionmentioning

confidence: 99%

Robust Region Tracking Control for a Robot Manipulator

Li¹,

Lü²,

Chen³

et al. 2021

Preprint

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n this work, the uncertainty and disturbance estimator (UDE)-based robust region reaching controller for a robot manipulator is developed to achieve the moving target region trajectory tracking and complaint human robot interaction inside the target region. The regional feedback error is derived from the potential function to drive the robot manipulator end effector converging into the target region. Under the back-stepping control framework, the UDE is fused into the region tracking control law to estimate and compensate the model uncertainty and external disturbance. Both simulation and experimental studies are carried out with a universal robots (UR) 10 manipulator to demonstrate the effectiveness of the proposed method for moving target trajectory tracking, model uncertainty and external disturbance rejection, and compliant human robot interaction within the target region.

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On the adaptive control of robot manipulators with velocity observers

Arteaga

Ortiz–Espinoza

Romero

et al. 2020

Intl J Robust & Nonlinear

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SummaryTo achieve accurate tracking control of robot manipulators many schemes have been proposed. A common approach is based on adaptive control techniques, which guarantee trajectory tracking under the assumption that the robot model structure is perfectly known and linear in the unknown parameters, while joint velocities are available. Despite tracking errors tend to zero, parameter errors do not unless some persistent excitation condition is fulfilled. There are few works dealing with velocity observation in conjunction with adaptive laws. In this note, an adaptive control/observer scheme is proposed for tracking position of robot manipulators. It is shown that tracking and observation errors are ultimately bounded, with the characteristic that when a persistent excitation condition is matched then they, as well as the parameter errors, tend to zero. Simulation results are in good agreement with the developed theory.

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Experimental Results on the Robust and Adaptive Control of Robot Manipulators Without Velocity Measurements

Cited by 24 publications

References 16 publications

Bi-Level Adaptive Computed-Current Impedance Controller for Electrically Driven Robots

Bi-Level Adaptive Computed-Current Impedance Controller for Electrically Driven Robots

Robust Region Tracking Control for a Robot Manipulator

On the adaptive control of robot manipulators with velocity observers

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