Adaptive Impedance Control of Robot Manipulators with Parametric Uncertainty for Constrained Path–Tracking

Bonilla, Isela; Mendoza, Marco; Campos-Delgado, Daniel U.; Hernández-Alfaro, Diana E.

doi:10.2478/amcs-2018-0027

Cited by 13 publications

(6 citation statements)

References 35 publications

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“…e impedance model refers to the dynamic relationship between the input flow and the output effort at the interaction port between a manipulator and its environment [17]. is paper regarded the robotic ankle joint as an impedance model and used it to estimate the ankle disturbance torque.…”

Section: Disturbance Torque Estimationmentioning

confidence: 99%

Variable Impedance Control for Bipedal Robot Standing Balance Based on Artificial Muscle Activation Model

Yin

Xue

Yang

et al. 2021

Journal of Robotics

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The bipedal robot should be able to maintain standing balance even in the presence of disturbing forces. The control schemes of bipedal robot are conventionally developed based on system models or fixed torque-ankle states, which often lack robustness. In this paper, a variable impedance control based on artificial muscle activation is investigated for bipedal robotic standing balance to address this limitation. The robustness was improved by applying the artificial muscle activation model to adjust the impedance parameters. In particular, an ankle variable impedance model was used to obtain the antidisturbance torque which combined with the ankle dynamic torque to estimate the desired ankle torque for robotic standing balance. The simulation and prototype experimentation results demonstrate that the control method improves the robustness of bipedal robotic standing balance control.

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Section: Disturbance Torque Estimationmentioning

confidence: 99%

Variable Impedance Control for Bipedal Robot Standing Balance Based on Artificial Muscle Activation Model

Yin

Xue

Yang

et al. 2021

Journal of Robotics

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“…Note that the robot kinematic parameters uncertainties are always existed such as link 6 Complexity length and mass so that the Jacobian matrix ( ) cannot be known precisely. Therefore, define the estimated Jacobian matrix̂( ,̂) ∈ R × , the estimation̂̇oḟand the estimation̂of can be represented aŝ̇=̂( ,̂)̇= ( ,)̂ (36) =̂T ( ,̂) = ( , )̂,…”

Section: Adaptive Jacobian and Rbfnn Position Tracking Conmentioning

confidence: 99%

“…Literatures [27,34,35] used two-loop controllers, which included the inner-loop position control and the outer-loop force control, to achieve the position and force tracking control. Based on these methods, Bonilla et al [36] proposed an inverse dynamical control law based on impedance control to achieve the position path tracking in both free and constrained spaces, which mainly focused on developing the compliant control scheme for constrained path tracking; however, the force tracking was not involved.…”

Section: Introductionmentioning

confidence: 99%

Position/Force Tracking Impedance Control for Robotic Systems with Uncertainties Based on Adaptive Jacobian and Neural Network

Peng

Yang

2019

Complexity

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In this paper, an adaptive Jacobian and neural network based position/force tracking impedance control scheme is proposed for controlling robotic systems with uncertainties and external disturbances. To achieve precise force control performance indirectly by using the position tracking, the control scheme is divided into two parts: the outer-loop force impedance control and the inner-loop position tracking control. In the outer-loop, an improved impedance controller, which combines the traditional impedance relationship with the PID-like scheme, is designed to eliminate the force tracking error quickly and to reduce the force overshoot effectively. In this way, the satisfied force tracking performance can be achieved when the manipulator contacts with environment. In the inner-loop, an adaptive Jacobian method is proposed to estimate the velocities and interaction torques of the end-effector due to the system kinematical uncertainties, and the system dynamical uncertainties and the uncertain term of adaptive Jacobian are compensated by an adaptive radial basis function neural network (RBFNN). Then, a robust term is designed to compensate the external disturbances and the approximation errors of RBFNN. In this way, the command position trajectories generated from the outer-loop force impedance controller can be then tracked so that the contact force tracking performance can be achieved indirectly in the forced direction. Based on the Lyapunov stability theorem, it is proved that all the signals in closed-loop system are bounded and the position and velocity errors are asymptotic convergence to zero. Finally, the validity of the control scheme is shown by computer simulation on a two-link robotic manipulator.

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“…In most applications, impedance control tracking methods based on force control has been widely used (Davliakos and Papadopoulos, 2009; Duan et al , 2018a; Gierlak and Szuster, 2017; Bonilla et al , 2018). However, the existing commercial robot emphasizes the accuracy of position tracking and does not apply force control mode to achieve good interaction with the environment, so the impedance control method based on force control can not be popularized in the actual operation process.…”

Section: System and Collision Detectionmentioning

confidence: 99%

Collision detection and force control based on the impedance approach and dynamic modelling

Wang

Zhang

2019

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Purpose This paper aims to address the collision problem between robot and the external environment (including human) in an unstructured situation. A new collision detection and torque optimization control method is proposed. Design/methodology/approach Firstly, when the collision appears, a second-order Taylor observer is proposed to estimate the residual value. Secondly, the band-pass filter is used to reduce the high-frequency torque modeling dynamic uncertainty. With the estimate information and the torque value, a variable impedance control approach is then synthesized to guarantee that the collision is avoided or the collision will be terminated with different contact models and positions. However, in terms of adaptive linear force error, the variation of the thickness of the boundary layer is controlled by the new proximity function. Findings Finally, the experimental results show the better performance of the proposed control method, realizing the force control during the collision process. Originality/value Origin approach and origin experiment.

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Adaptive Impedance Control of Robot Manipulators with Parametric Uncertainty for Constrained Path–Tracking

Cited by 13 publications

References 35 publications

Variable Impedance Control for Bipedal Robot Standing Balance Based on Artificial Muscle Activation Model

Variable Impedance Control for Bipedal Robot Standing Balance Based on Artificial Muscle Activation Model

Position/Force Tracking Impedance Control for Robotic Systems with Uncertainties Based on Adaptive Jacobian and Neural Network

Collision detection and force control based on the impedance approach and dynamic modelling

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