Design of a Fat-Based Adaptive Visual Servoing for Robots with Time Varying Uncertainties

Chien, Ming-Chih; Huang, An‐Chyau

doi:10.1080/15599612.2010.484524

Cited by 9 publications

(6 citation statements)

References 45 publications

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“…It is because of the fact that the output of a stable linear filter, whose inputs are bounded, must also be bounded. The boundedness of the internal force errors can be also seen from the following equation derived from ( 14), ( 18), (22), and ( 27) as…”

Section: Stability Analysismentioning

confidence: 99%

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FAT-based robust adaptive control of cooperative multiple manipulators without velocity measurement

Deylami

Izadbakhsh

2021

Robotica

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This article addresses the problem of pose and force control in a cooperative system comprised of multiple n-degree-of-freedom (n-DOF) electrically driven robotic arms that move a payload. The proposed controller should be capable of maintaining the position and orientation of the payload in the desired path. In addition, the force exerted by robot end effectors on the object must remain limited. The system has unmodeled dynamics, and measuring the robot joint velocities is impossible. Therefore, a FAT-based observer–controller is designed to estimate the uncertainty and velocities based on universal approximation property of Fourier series expansion. The stability of the system is confirmed based on Lyapunov’s stability theorem. Finally, the proposed adaptive controller–observer is applied on two 3-DOF cooperative robotic arms carrying a payload, and the results are precisely analyzed. The results of the proposed approach are also compared with two state-of-art powerful approximation method.

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Section: Stability Analysismentioning

confidence: 99%

“…FAT-based estimators, on the other hand, approximate functions as time series and are not dependent on system states. This results in the reduction of system computational load [22]. Table I compares the main properties of function approximation techniques, fuzzy approaches, and neural networks.…”

Section: Introductionmentioning

confidence: 99%

FAT-based robust adaptive control of cooperative multiple manipulators without velocity measurement

Deylami

Izadbakhsh

2021

Robotica

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“…FAT‐based estimators, on the other hand, approximate functions as time series and are not dependent on system states. This results in the reduction of system computational load 22,23 . Table 1 compares the main properties of function approximation techniques, fuzzy approaches, and neural networks.…”

Section: Introductionmentioning

confidence: 99%

“…This results in the reduction of system computational load. 22,23 In this article, the FAT is used to deal with unmodulated dynamics and disturbances so that the impact of these factors does not cause a decline in system performance. For this purpose, the Mastroianni operator is used to estimate of uncertainties and disturbances, and the coefficients of this operator are updated by developing adaptive rules.…”

Section: Introductionmentioning

confidence: 99%

Observer‐based adaptive control of cooperative multiple manipulators using the Mastroianni operators as uncertainty approximator

Deylami

Izadbakhsh

2022

Intl J Robust & Nonlinear

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This article addresses the multi‐objective problem of pose and force control in a cooperative system comprised of multiple n‐degree‐of‐freedom (n‐DOF) robotic arms that move a payload. The proposed controller should be capable of maintaining the position and orientation of the payload in the desired path. In addition, the force exerted by robot end‐effectors on the object must remain limited. The system has unmodeled dynamics, and measuring the robot joint velocities is impossible. In other words, joint positions are the only measured states. Therefore, a Mastroianni operator‐based observer is first designed to estimate the uncertainty and velocities based on its universal approximation property. Then, using these estimations, a feedback controller is proposed to establish a robust and precise tracking performance. The stability of this system is confirmed based on Lyapunov's stability theorem. This article is the first study on utilizing the adaptive form of Mastroianni operators in robust adaptive controller design. Moreover, the introduced structure is regressor‐free and does not depend on velocity measurements. Finally, the proposed adaptive observer‐controller is applied on two 3‐DOF cooperative robotic arms carrying a payload, and the results are precisely analyzed. The results of the proposed approach are also compared with a state‐of‐art powerful approximation method.

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“…Once it is obtained, we may find that, for most robots, elements in the unknown vector are simple combinations of system parameters such as link mass, link length and moment of inertia, and these are sometimes relatively easy to measure. 13 Huang and Chen 14 proposed an adaptive backstepping-like controller based on FAT [15][16][17][18][19][20][21][22][23][24][25][26][27][28] for single-link flexible-joint robots with mismatched uncertainties. Similar to most backstepping designs, the derivation is too complex to robots with more joints.…”

Section: Introductionmentioning

confidence: 99%

A Regressor-free Adaptive Control for Flexible-joint Robots based on Function Approximation Technique

Chien¹,

Huang²

2010

Advances in Robot Manipulators

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An adaptive controller is presented in this paper to control an n-link flexible-joint manipulator with time-varying uncertainties. The function approximation technique (FAT) is utilized to represent time-varying uncertainties in some finite combinations of orthogonal basis. The tedious computation of the regressor matrix needed in traditional adaptive control is avoided in the new design, and the controller does not require the variation bounds of time-varying uncertainties needed in traditional robust control. In addition, the joint acceleration is not needed in the controller realization. Via the Lyapunov-like stability theory, adaptive update laws are derived to give convergence of the output tracking error. Moreover, the upper bounds of tracking errors in the transient state are also derived. A 2 DOF planar manipulator with flexible joints is used in the computer simulation to verify the effectiveness of the proposed controller.

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Design of a Fat-Based Adaptive Visual Servoing for Robots with Time Varying Uncertainties

Cited by 9 publications

References 45 publications

FAT-based robust adaptive control of cooperative multiple manipulators without velocity measurement

FAT-based robust adaptive control of cooperative multiple manipulators without velocity measurement

Observer‐based adaptive control of cooperative multiple manipulators using the Mastroianni operators as uncertainty approximator

A Regressor-free Adaptive Control for Flexible-joint Robots based on Function Approximation Technique

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