Results 251 to 260 of about 1,806,131 (303)

Explicit Method for Parameter Identification

Journal of Guidance, Control, and Dynamics, 1997
Summary: Parameter identification of dynamical systems through a new method that treats the unknown parameters as time dependent is reported. With appropriate observational data, the unknown system parameters are guided from an arbitrary initial condition to their true value at a final time.
Tadi, M., Rabitz, Herschel
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Parameter identification for industrial robots

Proceedings of 1995 IEEE International Conference on Robotics and Automation, 2002
Models and model parameters form the base of a computer aided planning of robot manipulations. The identification procedure presented determines the independent, dynamic parameters by trajectories of optimal excitation without the need of disassembling the robot. Joint parameters are identified by fixing the arms and performing static and dynamic tests
Friedrich Pfeiffer, Josef Hölzl
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Parameter identification for dynamic simulation

Proceedings of International Conference on Robotics and Automation, 2002
Dynamic simulation is potentially a powerful tool for studying complex contact interactions between robots and their environments. One of the main problems of such a simulation is the determination of the model parameters which provide realistic behavior for objects. This paper describes how to identify such parameters for a masses/springs based system
Ammar Joukhadar, F. Garat, Christian Laugier   +2 more
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Parameter identification of induction motors. 2. Parameter subset identification

Proceedings of the 1998 IEEE International Conference on Control Applications (Cat. No.98CH36104), 2002
The model-based identification concept is applied to the problem of subset parameter identification and identification of repeated parameters in induction motors. The aim of the investigation is a simplification of the identifier dynamics with a reduction of the computational burden.
V. Pappano, S.E. Lyshevski, B. Friedland
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PARAMETERS IDENTIFICATION IN BIOLOGICAL SYSTEMS

Kybernetes, 1981
Many bio‐medical models leads to differential systems. Some coefficients (exchange parameters,…) must be identified from partial observation on the system's solution. We suggest methods to study the existence and unicity of the identification problem.
Cherruault, Y., Guillez, A.
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Recursive identification of lung parameters

Computer Methods and Programs in Biomedicine, 1989
Determination of lung capacity (FRC) using insoluble gas washout or equilibrium methods is a common procedure in respiratory tests. The lung model can be extended to include multiple compartments with differing volumes and ventilation fractions. A discrete-time mathematical model of a multi-compartment lung was developed based on mass conservation laws
C P, Valcke, J S, Jenkins, D S, Ward
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Identification of parameters in systems biology

Mathematical Biosciences, 2018
We consider the inverse problem for the identification of the finite dimensional set of parameters for systems of nonlinear ordinary differential equations (ODEs) arising in systems biology. A numerical method which combines Bellman's quasilinearization with sensitivity analysis and Tikhonov's regularization is implemented.
Abdulla, Ugur G., Poteau, Roby
openaire   +3 more sources

Analysis of a parameter identification problem

Applied Mathematics and Computation, 1997
We consider a special parameter identification problem occurring in marketing research, and give conditions on the empirical data which guarantee the existence of the solution to the problem. Furthermore, we analyze several different approaches and methods for solving this parameter identification problem.
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A filter technique for parameter identification

Mechanics Research Communications, 1983
Identification des parametres de systemes mecaniques lineaires soumis a une excitation stochastique. La methode utilise les moments seconds des processus de reponse ainsi que les reponses de filtres lineaires ajoutes aux dispositifs de mesure du systeme.
Weber, H. I., Schiehlen, W. O.
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Parameters identification of flexible robots

Proceedings. 1998 IEEE International Conference on Robotics and Automation (Cat. No.98CH36146), 2002
In the case of flexible robots we cannot apply the methods used in the case of rigid robots for the determination of exciting trajectories. Indeed the elastic degrees of freedom are not controllable: they are linked to the actuated degrees of freedom by a system of differential equations.
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