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This paper investigates the modelling, parameter identification and control of an unidirectional hydraulically actuated seismic isolator test rig.
As an example, the modelling, parameter identification, and filtering of a broadband acoustic noise produced by a rotating fan in a duct is considered.
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Some characterization test results to model parameters identification are included.
Modelling, parameters identification and performances of the robustified axes drive polynomial controllers are first validated within a virtual machine tool environment.
In this work I present a general algorithm for coupling state variable and model parameter identification.
This paper proposes an intelligent model parameter identification method using particle swarm optimization (PSO).
Model parameter identification and validation is accomplished by comparing numerically simulated and experimentally measured temperatures and outlet product concentrations.
This includes hardware design, sensor and actuator selection, system modeling, parameter identification, controller design and experimental testing.
A new explicit approach for the simultaneous online optimal experiment design (OED) and model parameter identification is presented.
The simplified refined instrument variable algorithm was used as a model parameter identification tool to obtain the best model order and parameters.
The simplified refined instrument variable algorithm was used as model parameter identification tool to obtain the best model order and parameters.
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