Commande Et Regulation Par Calulateur Numerique

Foulard, Camille; Gentil, Stéphanie; Sandraz, J-P.; Gilles, G.

doi:10.1115/1.3426417

Cited by 9 publications

(7 citation statements)

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“…An integral action is also added in order to nullify the static error between the system outputs and the reference ones. Let us note that the principle of the reference model based quadratic control had been presented for discrete linear time invariant processes in [17]. Thus, we aim to develop this idea for the studied continuous nonlinear plant using a multimodel approach.…”

Section: Reference Model and Integral Action Based Quadratic Controlmentioning

confidence: 99%

Wind turbine power tracking using an improved multimodel quadratic approach

2010

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Section: Reference Model and Integral Action Based Quadratic Controlmentioning

confidence: 99%

Wind turbine power tracking using an improved multimodel quadratic approach

2010

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“…The precision of the identified parameters is calculated using statistical properties applied to the measured signal [5]. It is supposed that the system has the same structure as the model.…”

Section: Precision Of the Identified Parametersmentioning

confidence: 99%

Identification of mechanical parameters at low velocities for a micropositioning stage using a velocity hysteresis model

Bogdan

Abba

2012

2012 IEEE International Conference on Robotics and Automation

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The paper presents a velocity hysteresis friction model. This model can be used for simulation or control of an accurate micropositioning servomechanism. The mechanical and friction parameters are identified from measured signals at low velocities, and with the use of a closed loop identification method. The measured signals are very noised. The number of measurement samples available is very low. The friction model depends on position, velocity and acceleration and includes the Coulomb, Stribeck and viscous frictions. A hysteresis effect integrated by an exponential term and the acceleration is added in the model. The identified parameters are validated by applying an efficient precision method based on the sensitivity analysis of nonlinear models and a normalized mean-square-error criterion.

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“…Consider a plant which is represented by the following state space equation in discrete form: (16) where: According to the development given in Foulard et al [14], the optimal control law can be written as tbllows: (18) where…”

Section: Optimal Linear Quadratic Controlmentioning

confidence: 99%