Advanced parameter identification for a linear-motor-driven motion system using disturbance observer

Pan, Yi Ren; Shih, Yu-Tai; Horng, Rong Hwang; Lee, An-Chen

doi:10.1007/s12541-009-0069-1

Cited by 29 publications

(11 citation statements)

References 24 publications

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“…This load was comprised of a constant gravity load and varying reaction forces. Different from a system having sliding joints with constant normal forces, such as in Pan et al [5], in this work, the total load resulted in varying normal forces, and therefore, varying friction forces. In fact, the normal forces varied because of the changing posture of the PKM.…”

Section: Introductionmentioning

confidence: 95%

Identification of the Dynamic Parameters of a Parallel Kinematics Mechanism with Prismatic Joints by Considering Varying Friction

Rosyid

El‐Khasawneh

2020

Applied Sciences

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This study proposed a novel approach for the offline dynamic parameter identification of parallel kinematics mechanisms in which the friction is significant and varying. Since the friction is significant, it should be incorporated to provide an accurate dynamic model. Furthermore, the varying normal forces as a result of the changing posture of the mechanism lead to varying friction forces, specifically varying static and Coulomb friction forces. By considering this variation, the static and Coulomb friction parameters are identified as coefficients instead of forces. A bound-constrained optimization technique using an iterative global search tool was employed in this work to minimize the residual errors while maintaining the physical feasibility of the solutions. Moreover, the friction was modeled by using the nonlinear Stribeck friction model since a linear friction model was not sufficient, whereas the variation of the friction followed the variation of the normal forces, which were evaluated through the Lagrange multipliers in the constrained dynamic model of the mechanism. The solutions obtained were verified by using some trajectories that were different from those used in the identification.

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Section: Introductionmentioning

confidence: 95%

Identification of the Dynamic Parameters of a Parallel Kinematics Mechanism with Prismatic Joints by Considering Varying Friction

Rosyid

El‐Khasawneh

2020

Applied Sciences

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“…Many studies have examined the identification and compensation of friction. 12,13 In this paper, the most widely used nonlinear expression of the LuGre model, 13 is applied to the resistance training machine. That is, Fig.…”

Section: Eccentric Contractionmentioning

confidence: 99%

Haptic-based resistance training machine and its application to biceps exercises

Park

Kim

Hong

2011

Int. J. Precis. Eng. Manuf.

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This paper introduces the design of a haptic-based resistance training machine and deals with the details of a control scheme for biceps exercises. The developed training machine has three components: 1) Machine hardware; 2) Impedance control based resistance generator; and 3) User interface. It can enable various resistance trainings considering the biomechanical behavior of individual user. That is, in contrast to conventional exercise machines, it can easily generate two-dimensional exercise motions and resistance profiles with respect to an individual's musculoskeletal characteristics. This feature can help users to easily execute an arbitrary exercise pattern that can maximize exercise performance. We choose the biceps exercise as its first application and implement an impedance control scheme for executing the newly suggested exercise protocol. Details of the experimental results are included for verification.

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“…x & and F v denote Coulomb, static, Stribeck velocity, and viscous coefficients, 10,11 respectively F d denotes disturbance.…”

Section: Stmentioning

confidence: 99%

A robust control of electro hydrostatic actuator using the adaptive back-stepping scheme and fuzzy neural networks

Kim

Park

Lee

et al. 2010

Int. J. Precis. Eng. Manuf.

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In general, the position control of electro hydrostatic actuator(EHA) systems is difficult because of the large variation of the effective bulk modulus of the working fluid, which is due to the absence of a heat exchanger like a reservoir tank, the friction between the cylinder and piston, and the external disturbance force. Moreover, it is difficult to identify the values of the effective bulk modulus and friction. In this paper, the variation of the effective bulk modulus, friction, and external disturbance are considered as uncertainties of EHA systems. To solve the problems due to these system uncertainties, an adaptive back-stepping control scheme with fuzzy neural networks(FNNs) is proposed. The effectiveness of the adaptive back-stepping control(ABSC) system with FNNs was compared with those of the standard back-stepping control(BSC) system and the ABSC system through computer simulation.

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Advanced parameter identification for a linear-motor-driven motion system using disturbance observer

Cited by 29 publications

References 24 publications

Identification of the Dynamic Parameters of a Parallel Kinematics Mechanism with Prismatic Joints by Considering Varying Friction

Identification of the Dynamic Parameters of a Parallel Kinematics Mechanism with Prismatic Joints by Considering Varying Friction

Haptic-based resistance training machine and its application to biceps exercises

A robust control of electro hydrostatic actuator using the adaptive back-stepping scheme and fuzzy neural networks

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