Nonlinear Uncertain Servomechanism Tracking using an Integral Observer

Garrido, R.; Flores, Ernesto

doi:10.1109/iceee.2007.4345019

Cited by 2 publications

(2 citation statements)

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“…we get the same z 2 -dynamics as the one in (53), resulting in a bounded tracking error of the servo states. Remark 2: Comparing the control law (57), designed using the contraction analysis, with the ILESO-based PD controller in [17], that is based on Lyapunov design, we can conclude the following: 1) the inclusion of the term 4θ 3 e 0 in (57) and omitted in [17] guarantees the exponential convergence of x 1 and x 2 to x d andẋ d , respectively; and 2) the stability analysis based on the contraction theory presented here is relatively simpler than the Lyapunov stability analysis described in [17].…”

Section: Controller Design Without Employing the Identified Friction Modelmentioning

confidence: 99%

“…Its linear version LESO has a structure of a classical Luenberger observer with a single tuning parameter. Due to its simplicity, the LESO has been widely used in friction estimation applications, using either the position measurements [12], [13] or their integral as in the ILESO [17]. In these references, the friction force is considered as an extended state, which is then on-line compensated.…”

Section: Introductionmentioning

confidence: 99%

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A Contraction Theory-Based Tracking Control Design With Friction Identification and Compensation

Thenozhi

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Rodríguez‐Reséndiz

2022

IEEE Trans. Ind. Electron.

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This paper proposes a tracking controller for servomechanisms with a continuous friction model. The parameters of this model are estimated through a proposed two-step offline identification methodology that uses a Linear Extended State Observer (LESO) based on the integral of position measurements, termed as ILESO. In the first step, the viscous and Coulomb coefficients of this friction model are estimated by the ordinary Least Squares (LS) method. The second step employs these estimates to obtain the initial guess for the Nonlinear Least Squares (NLLS) method that identifies all the parameters of the nonlinearly parameterized friction model. Finally, a backstepping controller is designed for reference tracking, which uses the estimated off-line friction model and on-line estimations of the servo position, velocity, and system uncertainty. These on-line estimations are provided by a modified ILESO, termed as FILESO, that has a similar structure to that of the ILESO but incorporates the identified off-line friction model into its dynamics. The convergence and stability of the proposed observer and controller are established using contraction analysis. Experimental results show that the proposed approach exhibits satisfactory performance.

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Section: Controller Design Without Employing the Identified Friction Modelmentioning

confidence: 99%