A new algebraic LQR weight selection algorithm for tracking control of 2 DoF torsion system

• Autorzy: Elumalai V. K. , Subramanian R. G.

Identyfikatory

DOI

10.1515/aee-2017-0005

• Języki publikacji: EN

Abstrakty

EN

This paper proposes a novel linear quadratic regulator (LQR) weight selection algorithm by synthesizing the algebraic Riccati equation (ARE) with the Lagrange multiplier method for command following applications of a 2 degree of freedom (DoF) torsion system. The optimal performance of LQR greatly depends on the elements of weighting matrices Q and R. However, normally these weighting matrices are chosen by a trial and error approach which is not only time consuming but cumbersome. Hence, to address this issue, blending the design criteria in time domain with the ARE, we put forward an algebraic weight selection algorithm, which makes the LQR design both simple and modular. Moreover, to estimate the velocity of a servo angle, a high gain observer (HGO) is designed and integrated with the LQR control scheme. The efficacy of the proposed control scheme is tested on a benchmark 2 DoF torsion system for a trajectory tracking application. Both the steady state and dynamic characteristics of the proposed controller are assessed. The experimental results accentuate that the proposed HGO based LQR scheme can guarantee the system to attain the design requirements with minimal vibrations and tracking errors.

Słowa kluczowe

EN

ARE; high gain observer; LQR; Q and R matrices; 2 DoF torsion system; trajectory tacking

• Wydawca: Polish Academy of Sciences, Committee on Electrical Engineering
• Czasopismo: Archives of Electrical Engineering
• Rocznik: 2017
• Tom: Vol. 66, nr 1
• Strony: 55--75
• Opis fizyczny: Bibliogr. 22 poz., rys., tab., wz.

Twórcy

autor

Elumalai V. K.

• School of Electrical Engineering, VIT University Vellore, Tamilnadu, 632014, India

autor

Subramanian R. G.

• Eindhoven University of Technology 5612 AZ Eindhoven, the Netherlands

Bibliografia

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Uwagi

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).