A Novel Extended Desired Compensation Adaptive Law for High-Speed Pick-and-Throw with PKMs

G. Hassan; A. Chemori; M. Gouttefarde; M. El Rafei; C. Francis; P. E. Hervé; D. Sallé

doi:10.1016/j.ifacol.2022.07.382

A Novel Extended Desired Compensation Adaptive Law for High-Speed Pick-and-Throw with PKMs

G. Hassan, A. Chemori, M. Gouttefarde, M. El Rafei, C. Francis, P. E. Hervé, D. Sallé

Research output: Contribution to journal › Conference article › peer-review

1 Citation (Scopus)

Abstract

This paper focuses on the development of a new revised Desired Compensation Adaptive Law (DCAL). DCAL is a model-based adaptive control strategy consisting of three main parts: (i) an adaptive feedforward term, (ii) a linear PD feedback term, and (iii) a nonlinear compensation term. In order to deal with highly nonlinear dynamic systems characterized by their abundant uncertainties and parameters variations, we propose to revise the original DCAL control law by adopting adaptive feedback gains depending on the system state errors. Besides, DCAL controller is known for its robustness against measurement noise thanks to its desired compensation design, but a large amount of external disturbances are still not compensated by such a design. Therefore, the proposed DCAL with adaptive gains (DCAL-AG) is extended with a sliding-based term to further improve its robustness and the overall performance. A model-based robust adaptive feedback controller appropriate to the control of nonlinear systems in real-time applications is thereby obtained. To demonstrate the improvements brought by the proposed control strategy, numerical simulations have been conducted on a Delta-link parallel robot named T3KR in a "Pick-and-Throw" application task at different operating conditions.

Original language	English
Pages (from-to)	627-633
Number of pages	7
Journal	IFAC-PapersOnLine
Volume	55
Issue number	12
DOIs	https://doi.org/10.1016/j.ifacol.2022.07.382
Publication status	Published - 2022
Event	14th IFAC Workshop on Adaptive and Learning Control Systems, ALCOS 2022 - Casablanca, Morocco Duration: 29 Jun 2022 → 1 Jul 2022

Keywords

Robust DCAL
adaptive gains
numerical simulations
parallel kinematic manipulator
pick-and-throw

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10.1016/j.ifacol.2022.07.382

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title = "A Novel Extended Desired Compensation Adaptive Law for High-Speed Pick-and-Throw with PKMs",

abstract = "This paper focuses on the development of a new revised Desired Compensation Adaptive Law (DCAL). DCAL is a model-based adaptive control strategy consisting of three main parts: (i) an adaptive feedforward term, (ii) a linear PD feedback term, and (iii) a nonlinear compensation term. In order to deal with highly nonlinear dynamic systems characterized by their abundant uncertainties and parameters variations, we propose to revise the original DCAL control law by adopting adaptive feedback gains depending on the system state errors. Besides, DCAL controller is known for its robustness against measurement noise thanks to its desired compensation design, but a large amount of external disturbances are still not compensated by such a design. Therefore, the proposed DCAL with adaptive gains (DCAL-AG) is extended with a sliding-based term to further improve its robustness and the overall performance. A model-based robust adaptive feedback controller appropriate to the control of nonlinear systems in real-time applications is thereby obtained. To demonstrate the improvements brought by the proposed control strategy, numerical simulations have been conducted on a Delta-link parallel robot named T3KR in a {"}Pick-and-Throw{"} application task at different operating conditions.",

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AU - Hassan, G.

AU - Chemori, A.

AU - Gouttefarde, M.

AU - Rafei, M. El

AU - Francis, C.

AU - Hervé, P. E.

AU - Sallé, D.

PY - 2022

Y1 - 2022

N2 - This paper focuses on the development of a new revised Desired Compensation Adaptive Law (DCAL). DCAL is a model-based adaptive control strategy consisting of three main parts: (i) an adaptive feedforward term, (ii) a linear PD feedback term, and (iii) a nonlinear compensation term. In order to deal with highly nonlinear dynamic systems characterized by their abundant uncertainties and parameters variations, we propose to revise the original DCAL control law by adopting adaptive feedback gains depending on the system state errors. Besides, DCAL controller is known for its robustness against measurement noise thanks to its desired compensation design, but a large amount of external disturbances are still not compensated by such a design. Therefore, the proposed DCAL with adaptive gains (DCAL-AG) is extended with a sliding-based term to further improve its robustness and the overall performance. A model-based robust adaptive feedback controller appropriate to the control of nonlinear systems in real-time applications is thereby obtained. To demonstrate the improvements brought by the proposed control strategy, numerical simulations have been conducted on a Delta-link parallel robot named T3KR in a "Pick-and-Throw" application task at different operating conditions.

AB - This paper focuses on the development of a new revised Desired Compensation Adaptive Law (DCAL). DCAL is a model-based adaptive control strategy consisting of three main parts: (i) an adaptive feedforward term, (ii) a linear PD feedback term, and (iii) a nonlinear compensation term. In order to deal with highly nonlinear dynamic systems characterized by their abundant uncertainties and parameters variations, we propose to revise the original DCAL control law by adopting adaptive feedback gains depending on the system state errors. Besides, DCAL controller is known for its robustness against measurement noise thanks to its desired compensation design, but a large amount of external disturbances are still not compensated by such a design. Therefore, the proposed DCAL with adaptive gains (DCAL-AG) is extended with a sliding-based term to further improve its robustness and the overall performance. A model-based robust adaptive feedback controller appropriate to the control of nonlinear systems in real-time applications is thereby obtained. To demonstrate the improvements brought by the proposed control strategy, numerical simulations have been conducted on a Delta-link parallel robot named T3KR in a "Pick-and-Throw" application task at different operating conditions.

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A Novel Extended Desired Compensation Adaptive Law for High-Speed Pick-and-Throw with PKMs

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Keywords

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