Zener Model based Impedance Control for High-Precision Force Tracking of Robot-Environment Interaction

For the robot system with the uncertain model and unknown environment parameters, a control scheme combining impedance and finite time is proposed. In order to obtain accurate force control performance indirectly by using position tracking, the control scheme is divided into two parts: an outer loop for force impedance control and an inner loop for position tracking control. In the outer loop, in order to eliminate the force tracking error quickly, the impedance control based on force is adopted; when the robot contacts with the environment, the satisfactory force tracking performance can be obtained. In the inner loop, the finite-time control method based on the homogeneous system is used. Through this method, the desired virtual trajectory generated by the outer loop can be tracked, and the contact force tracking performance can be obtained indirectly in the direction of force. This method does not need the dynamics model knowledge of the robot system, thus avoiding the online real-time calculation of the inverse dynamics of the robot. The unknown uncertainty and external interference of the system are obtained online by using the time-delay estimation, and the control process is effectively compensated, so the algorithm is simple, the convergence speed is fast, and the practical application is easy. The theory of finite-time stability is used to prove that the closed-loop system is finite-time stable, and the effectiveness of the algorithm is proved by simulations.

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Model-based Control Techniques for Large-Scale High-Precision Stage

IEEJ Transactions on Industry Applications ◽

10.1541/ieejias.140.272 ◽

2020 ◽

Vol 140 (4) ◽

pp. 272-280

Author(s):

Wataru Ohnishi ◽

Hiroshi Fujimoto ◽

Koichi Sakata

Keyword(s):

High Precision ◽

Large Scale ◽

Model Based Control ◽

Precision Stage ◽

Control Techniques ◽

Model Based

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Development of an autonomous robotic system for beard shaving assistance of disabled people based on an adaptive force tracking impedance control

Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science ◽

10.1177/0954406220984821 ◽

2021 ◽

pp. 095440622098482

Author(s):

Oladayo S Ajani ◽

Samy FM Assal

Keyword(s):

Impedance Control ◽

Environmental Parameters ◽

Robotic System ◽

Robotic Systems ◽

Full Potential ◽

Robotic Assistance ◽

Head Pose ◽

Detection And Tracking ◽

Control Scheme ◽

Force Tracking

Recently, people with upper arm disabilities due to neurological disorders, stroke or old age are receiving robotic assistance to perform several activities such as shaving, eating, brushing and drinking. Although the full potential of robotic assistance lies in the use of fully autonomous robotic systems, these systems are limited in design due to the complexities and the associated risks. Hence, rather than the shared controlled or active robotic systems used for such tasks around the head, an adaptive compliance control scheme-based autonomous robotic system for beard shaving assistance is proposed. The system includes an autonomous online face detection and tracking as well as selected geometrical features-based beard region estimation using the Kinect RGB-D camera. Online trajectory planning for achieving the shaving task is enabled; with the capability of online re-planning trajectories in case of unintended head pose movement and occlusion. Based on the dynamics of the UR-10 6-DOF manipulator using ADAMS and MATLAB, an adaptive force tracking impedance controller whose parameters are tuned using Genetic Algorithm (GA) with force/torque constraints is developed. This controller can regulate the contact force under head pose changing and varying shaving region stiffness by adjusting the target stiffness of the controller. Simulation results demonstrate the system capability to achieve beard shaving autonomously with varying environmental parameters that can be extended for achieving other tasks around the head such as feeding, drinking and brushing.

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Suppress Vibration on Robotic Polishing with Impedance Matching

Actuators ◽

10.3390/act10030059 ◽

2021 ◽

Vol 10 (3) ◽

pp. 59

Author(s):

Junjie Dai ◽

Chin-Yin Chen ◽

Renfeng Zhu ◽

Guilin Yang ◽

Chongchong Wang ◽

...

Keyword(s):

Contact Force ◽

Force Control ◽

Impedance Control ◽

Impedance Matching ◽

Industrial Robots ◽

Contact Phase ◽

Dynamic Tracking ◽

Force Tracking ◽

The Difference ◽

End Effectors

Installing force-controlled end-effectors on the end of industrial robots has become the mainstream method for robot force control. Additionally, during the polishing process, contact force stability has an important impact on polishing quality. However, due to the difference between the robot structure and the force-controlled end-effector, in the polishing operation, direct force control will have impact during the transition from noncontact to contact between the tool and the workpiece. Although impedance control can solve this problem, industrial robots still produce vibrations with high inertia and low stiffness. Therefore, this research proposes an impedance matching control strategy based on traditional direct force control and impedance control methods to improve this problem. This method’s primary purpose is to avoid force vibration in the contact phase and maintain force–tracking performance during the dynamic tracking phase. Simulation and experimental results show that this method can smoothly track the contact force and reduce vibration compared with traditional force control and impedance control.

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Fractional-order Impedance Control Method with Enhanced Force Tracking

2020 Chinese Automation Congress (CAC) ◽

10.1109/cac51589.2020.9327795 ◽

2020 ◽

Author(s):

Tong Yang ◽

Zhengxiong Liu ◽

Xi Wu ◽

Zhiqiang Ma

Keyword(s):

Fractional Order ◽

Control Method ◽

Impedance Control ◽

Force Tracking

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Novel fractional hybrid impedance control of series elastic muscle-tendon actuator

Industrial Robot the international journal of robotics research and application ◽

10.1108/ir-10-2020-0236 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Mohammad Javad Fotuhi ◽

Zafer Bingul

Keyword(s):

Contact Stress ◽

Impedance Control ◽

Robustness Analysis ◽

Simulation Models ◽

Experimental Results ◽

Uncertain Environments ◽

Content Type ◽

Force Tracking ◽

Comparative Results ◽

Series Elastic

Purpose This paper aims to develope a novel fractional hybrid impedance control (FHIC) approach for high-sensitive contact stress force tracking control of the series elastic muscle-tendon actuator (SEM-TA) in uncertain environments. Design/methodology/approach In three different cases, the fractional parameters of the FHIC were optimized with the particle swarm optimization algorithm. Its adaptability to the pressure of the sole of the foot on real environments such as grass (soft), carpet (medium) and solid floors (hard) is far superior to traditional impedance control. The main aim of this paper is to derive the dynamic simulation models of the SEM-TA, to develop a control architecture allowing for high-sensitive contact stress force control in three cases and to verify the simulation models and the proposed controller with experimental results. The performance of the optimized controllers was evaluated according to these parameters, namely, maximum overshoot, steady-state error, settling time and root mean squared errors of the positions. Moreover, the frequency robustness analysis of the controllers was made in three cases. Findings Different simulations and experimental results were conducted to verify the control performance of the controllers. According to the comparative results of the performance, the responses of the proposed controller in simulation and experimental works are very similar. Originality/value Origin approach and origin experiment.

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Adaptive neural network force tracking impedance control for uncertain robotic manipulator based on nonlinear velocity observer

Neurocomputing ◽

10.1016/j.neucom.2018.11.068 ◽

2019 ◽

Vol 331 ◽

pp. 263-280 ◽

Cited By ~ 15

Author(s):

Zeqi Yang ◽

Jinzhu Peng ◽

Yanhong Liu

Keyword(s):

Neural Network ◽

Impedance Control ◽

Robotic Manipulator ◽

Adaptive Neural Network ◽

Force Tracking ◽

Velocity Observer ◽

Nonlinear Velocity

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A model reference adaptive variable impedance control method for robot

MATEC Web of Conferences ◽

10.1051/matecconf/202133603005 ◽

2021 ◽

Vol 336 ◽

pp. 03005

Author(s):

Xinchao Sun ◽

Lianyu Zhao ◽

Zhenzhong Liu

Keyword(s):

Real Time ◽

Tracking Control ◽

Control Method ◽

Impedance Control ◽

Tracking Error ◽

Reference Trajectory ◽

Control Parameters ◽

Model Reference ◽

Force Tracking ◽

Model Reference Adaptive

As a simple and effective force tracking control method, impedance control is widely used in robot contact operations. The internal control parameters of traditional impedance control are constant and cannot be corrected in real time, which will lead to instability of control system or large force tracking error. Therefore, it is difficult to be applied to the occasions requiring higher force accuracy, such as robotic medical surgery, robotic space operation and so on. To solve this problem, this paper proposes a model reference adaptive variable impedance control method, which can realize force tracking control by adjusting internal impedance control parameters in real time and generating a reference trajectory at the same time. The simulation experiment proves that compared with the traditional impedance control method, this method has faster force tracking speed and smaller force tracking error. It is a better force tracking control method.

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