2015
DOI: 10.1117/12.2185682
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Force estimation in a 2-DoF piezoelectric actuator by using the inverse-dynamics based unknown input observer technique

Abstract: The aim of this paper is the estimation of force in a two degrees of freedom (2-DoF) piezoelectric actuator devoted to microrobotic manipulation tasks. Due to the limited space and to the small sizes of the actuator, the use of external sensors to measure both the displacement and the force played into role during the tasks are impossible. Therefore the deal in this study consists to propose observer techniques to bypass the use of force sensors. Based on the unknown input observer (UIO) technique, force along… Show more

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Cited by 2 publications
(4 citation statements)
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“…Jung et al [3] used a Kalman filter to estimate the contact force between a manipulator and its environment, but this paper only presents simulation results. Trenchant et al [4] used an unknown input observer to estimate the contact force between a two-degree-of-freedom piezoelectric actuator and its environment. The study [5] used the generalized proportional integral observer to estimate a contact force in a simulation study.…”
Section: Introductionmentioning
confidence: 99%
See 2 more Smart Citations
“…Jung et al [3] used a Kalman filter to estimate the contact force between a manipulator and its environment, but this paper only presents simulation results. Trenchant et al [4] used an unknown input observer to estimate the contact force between a two-degree-of-freedom piezoelectric actuator and its environment. The study [5] used the generalized proportional integral observer to estimate a contact force in a simulation study.…”
Section: Introductionmentioning
confidence: 99%
“…To counteract parametric uncertainties associated with the plant's mathematical model, the studies [8,9] proposed adaptive rules to adjust observer parameters for reducing parametric uncertainties. However, these studies [3][4][5][6][7][8][9] cannot consider unknown disturbances inherent to a servo system, such as the joint friction of a robotic arm. In other words, these force observers [3][4][5][6][7][8][9] are incapable of distinguishing the intrinsic disturbance force from the external contact force, which deteriorates the preciseness of force estimation.…”
Section: Introductionmentioning
confidence: 99%
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“…Notice that the LTI approximation of the creep is important within different applications: modeling, feedforward control, feedback control and signal estimation [5][6][7][8][9][10][11][12][13][14][15]. Γ d (u(s), s) is mainly described by a rate-dependent Prandtl-Ishlinskii model [16][17][18][19].…”
Section: Pea Nonlinear Modelingmentioning
confidence: 99%