A methodology to enhance the convergence of Output Error identification algorithms

Tohme, Elie; Ouvrard, Régis; Abche, Antoine; Trigeassou, Jean‐Claude; Poinot, Thierry; Mercère, Guillaume

doi:10.23919/ecc.2007.7068408

Cited by 14 publications

(5 citation statements)

References 7 publications

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“…The output is given by a state-space model output equation, which is typically the joint position for mechanical systems. Difficulties arise from the choice of initial conditions, resulting in multiple, local solutions [18]. The OE method has been used to identify electrical parameters of a synchronous machine, and a comparison with the IDIM-LS method showed very similar results [19].…”

Section: Introductionmentioning

confidence: 93%

“…An unbiased estimation of the standard deviation is (18) The covariance matrix of the estimation error is given by is the th diagonal coefficient of . The relative standard deviation % is given by % for (20) The OLS can be improved by taking into account different standard deviations on joint equations errors [9].…”

Section: Inverse Dynamic Identification Model Techniquementioning

confidence: 99%

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A New Closed-Loop Output Error Method for Parameter Identification of Robot Dynamics

Gautier

Janot

Vandanjon³

2013

IEEE Trans. Contr. Syst. Technol.

161

142

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Offline robot dynamic identification methods are mostly based on the use of the inverse dynamic model, which is linear with respect to the dynamic parameters. This model is sampled while the robot is tracking reference trajectories that excite the system dynamics. This allows using linear least-squares techniques to estimate the parameters. The efficiency of this method has been proved through the experimental identification of many prototypes and industrial robots. However, this method requires the joint force/torque and position measurements and the estimate of the joint velocity and acceleration, through the bandpass filtering of the joint position at high sampling rates. The proposed new method called DIDIM requires only the joint force/torque measurement, which avoids the calculation of the velocity and acceleration by bandpass filtering of the measured position. It is a closed-loop output error method where the usual joint position output is replaced by the joint force/torque. It is based on a closed-loop simulation of the robot using the direct dynamic model, the same structure of the control law, and the same reference trajectory for both the actual and the simulated robot. The optimal parameters minimize the 2-norm of the error between the actual force/torque and the simulated force/torque. This is a nonlinear least-squares problem which is dramatically simplified using the inverse dynamic model to obtain an analytical expression of the simulated force/torque, linear in the parameters. A validation experiment on a two degree-of-freedom direct drive rigid robot shows that the new method is efficient

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Section: Introductionmentioning

confidence: 93%

Section: Inverse Dynamic Identification Model Techniquementioning

confidence: 99%

A New Closed-Loop Output Error Method for Parameter Identification of Robot Dynamics

Gautier

Janot

Vandanjon³

2013

IEEE Trans. Contr. Syst. Technol.

161

142

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show abstract

“…However, Janot, Vandanjon & Gautier (2014) show that application of a multi-start Gauss-Newton algorithm for parameter estimation of a 6-DOF robot is not a proper strategy. The problem of multi-modality of the performance surface can be solved by the design of a suitable filter (Tohme et al, 2007), and the technique is efficient when the first and second order derivatives of the performance surface are available analytically. Unfortunately, this assumption is not valid in the present case since, due the complexity of the model, no closed-form analytical equation exists.…”

Section: Introductionmentioning

confidence: 99%

Dynamic modelling and parameter estimation of a hydraulic robot manipulator using a multi-objective genetic algorithm

Montazeri

West

Monk

et al. 2016

International Journal of Control

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This article concerns the problem of dynamic modeling and parameter estimation for a seven degree of freedom hydraulic manipulator. The laboratory example is a dual-manipulator mobile robotic platform used for research into nuclear decommissioning. In contrast to earlier control model orientated research using the same machine, the article develops a nonlinear, mechanistic simulation model that can subsequently be used to investigate physically meaningful disturbances. The second contribution is to optimize the parameters of the new model, i.e. to determine reliable estimates of the physical parameters of a complex robotic arm which are not known in advance. To address the nonlinear and non-convex nature of the problem, the research relies on the multi-objectivization of an output error single performance index. The developed algorithm utilises a multi-objective Genetic Algorithm (GA) in order to find a proper solution. The performance of the model and the GA is evaluated using both simulated (i.e. with a known set of 'true' parameters) and experimental data. Both simulation and experimental results show that multi-objectivization has improved convergence of the estimated parameters compared to the single objective output error problem formulation. This is achieved by integrating the validation phase inside the algorithm implicitly and exploiting the inherent structure of the multi-objective GA for this specific system identification problem.

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“…This approach is to minimize a quadratic error between an actual output and a simulated output of the system, assuming both the actual and simulated systems have the same input. A nonlinear optimization algorithm is required which is very sensitive to the choice of initial conditions to get the convergence [9]. The OE method has been used to identify electrical parameters of an asynchronous machine, and a comparison with the IDIM method showed very similar results [10].…”

Section: Introductionmentioning

confidence: 99%

“…But the two methods have a drawback. The IDIM method needs a good tuning of filters [3] [4] [5] while the OE method needs good initial conditions [9] and a powerful algorithm to solve non linear least squares [11]. By mixing these two approaches [12], our method overcomes these drawbacks.…”

Section: Introductionmentioning

confidence: 99%

Global identification of mechanical and electrical parameters of asynchronous motor driven joint with a fast CLOE method

Robet

Gautier

2013

2013 15th European Conference on Power Electronics and Applications (EPE)

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In many cases of new actuation of compliant controlled or bio-inspired joint driven robot, a global identification of electrical and mechanical coupled dynamics is required. This paper proposes a technique which mixes a closed loop output error method with the inverse dynamic identification model method which allows using linear least-squares technique to estimate the parameters. A first approach which has been validated on a DC motor allows a decoupled identification of the electrical and mechanical dynamics but fails to make a simultaneous identification. A major improvement of that method is proposed to carry out the coupled identification of both mechanical and electrical parameters. A validation on an asynchronous motor driven joint shows the effectiveness of the new procedure.

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A methodology to enhance the convergence of Output Error identification algorithms

Cited by 14 publications

References 7 publications

A New Closed-Loop Output Error Method for Parameter Identification of Robot Dynamics

A New Closed-Loop Output Error Method for Parameter Identification of Robot Dynamics

Dynamic modelling and parameter estimation of a hydraulic robot manipulator using a multi-objective genetic algorithm

Global identification of mechanical and electrical parameters of asynchronous motor driven joint with a fast CLOE method

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