Continuous-Time Model Identification of Robot Flexibilities for Fast Visual Servoing

Cuvillon, Loïc; Laroche, Édouard; Garnier, Hugues; Gangloff, Jacques; Mathelin, Michel de

doi:10.3182/20060329-3-au-2901.00204

Cited by 8 publications

(4 citation statements)

References 11 publications

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“…All of these interesting properties have been illustrated via Monte Carlo simulations and the application to both a winding process and an industrial binary distillation column. Another successful application of the proposed estimation scheme to identify a two inputtwo output flexible robotic arm designed for heart-beating tracking is also reported in Cuvillon et al (2006), demonstrating the wide practical applicability of the proposed identification approach.…”

Section: Discussionmentioning

confidence: 72%

An optimal IV technique for identifying continuous-time transfer function model of multiple input systems

Garnier

Gilson

Young

et al. 2007

Control Engineering Practice

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An instrumental variable method for continuous-time model identification is proposed for multiple input single output systems where the characteristic polynomials of the transfer functions associated with each input are not constrained to be identical. An associated model order determination procedure is shown to be reasonably successful. Monte Carlo simulation analysis are used to demonstrate the properties and general robustness of the model order selection and parameter estimation schemes. The results obtained to model a winding process and an industrial binary distillation column illustrate the practical applicability of the proposed identification scheme.

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Section: Discussionmentioning

confidence: 72%

An optimal IV technique for identifying continuous-time transfer function model of multiple input systems

Garnier

Gilson

Young

et al. 2007

Control Engineering Practice

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“…The IVSVF algorithm reduces the bias of the LSSVF algorithm, whereas the SRIV algorithm is the optimal identification algorithm. Hence, the Bode plot of the SRIV algorithm is the most appropriate for the actual model, and the results obtained using the IVSVF algorithm are better than those obtained using the LSSVF algorithm, as confirmed in [31,32]. To select an appropriate model structure, we utilized various criteria, such as the coefficient of determination (RT2), Young's information criterion (YIC), the condition number (Cond), the Akaike information criterion (AIC), and nb, nf, and nk denote the number of numerator and denominator parameters and number of samples for the delay of the system, which are shown in Table 2, in accordance with [31,32].…”

Section: Simulation Identificationmentioning

confidence: 73%

Section: Simulation Identificationmentioning

confidence: 74%

“…The input signal is a pseudo random binary sequence (PRBS). To select an appropriate model structure, we utilized various criteria, such as the coefficient of determination (RT2), Young's information criterion (YIC), the condition number (Cond), the Akaike information criterion (AIC), and nb, nf, and nk denote the number of numerator and denominator parameters and number of samples for the delay of the system, which are shown in Table 2, in accordance with [31,32]. Figure 4 shows the inputs of the motor during the identification simulation.…”

Section: Simulation Identificationmentioning

confidence: 99%

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Parameter Estimation, Robust Controller Design and Performance Analysis for an Electric Power Steering System

et al. 2019

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This paper presents a parameter estimation, robust controller design and performance analysis for an electric power steering (EPS) system. The parametrical analysis includes the EPS parameters and disturbances, such as the assist motor parameters, sensor-measurement noise, and random road factors, allowing the EPS stability to be extensively investigated. Based on the loop-shaping technique, the system controller is designed to increase the EPS stability and performance. The loop-shaping procedure is proposed to minimize the influence of system disturbances on the system outputs. The simplified refined instrumental variable (SRIV) algorithm, least squares state variable filter (LSSVF) algorithm and instrumental variable state variable filter (IVSVF) algorithm are applied to reduce the model mismatching between the theoretical EPS models and the real EPS model, as the EPS parameters can be accurately identified based on the experimental EPS data. The performance of the proposed method is thus compared to that of the proportional-integral-derivative (PID) test bench results for the EPS system. The experimental results demonstrated that the proposed loop-shaping controller provides good tracking performance while ensuring the stability of the EPS system.

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Robust Control of Robotic Manipulators with Structural Flexibilities

Halalchi¹,

Cuvillon²,

Mercère³

et al. 2013

Flexible Robotics

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Continuous-Time Model Identification of Robot Flexibilities for Fast Visual Servoing

Cited by 8 publications

References 11 publications

An optimal IV technique for identifying continuous-time transfer function model of multiple input systems

An optimal IV technique for identifying continuous-time transfer function model of multiple input systems

Parameter Estimation, Robust Controller Design and Performance Analysis for an Electric Power Steering System

Robust Control of Robotic Manipulators with Structural Flexibilities

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