System identification

About: System identification is a research topic. Over the lifetime, 21291 publications have been published within this topic receiving 439142 citations.

Suboptimal feedback control by a scheme of iterative identification and control design

Abstract: In this paper a framework for an iterative procedure of identification and robust control design is introduced wherein the robust performance is monitored during the subsequent steps of the iterative scheme. By monitoring the performance via a model-based approach, the possibility to guarantee performance improvement in the iterative scheme is being employed. In order to monitor achieved performance (for a present controller) and to guarantee robust performance (for a future controller), an uncertainty set is used where the uncertainty structure is chosen in terms of model perturbations in the dual Youla parametrization. This uncertainty structure is shown to be particularly suitable for the control performance measure that is considered. The model uncertainty set can be identified by an uncertainty estimation procedure on the basis of closed-loop experimental data. To obtain performance robustness, robust control design tools are used to synthesise controllers on the basis of the identified uncertainty set.

A trajectory sensitivity method for the identification of nonlinear excitation system models

Abstract: A sensitivity method for identifying parameters of nonlinear synchronous generator models is proposed and applied to the identification of the parameters of IEEE type ST3 and DC1 models. The method generates the sensitivities directly from the nonlinear model and does not require linearization. The use of singular values and singular vectors to detect the identifiability of parameters is discussed. The identification of the parameters requires, in general, very few iterations. The presence of noise in data reduces the identifiability of the parameters. However, reasonable approximations can be obtained if the parameters to be identified are chosen carefully. >

System Identification for Small, Low-Cost, Fixed-Wing Unmanned Aircraft

Abstract: This paper describes a practical system identification procedure for small, low-cost, fixed-wing unmanned aircraft. Physical size and cost restrictions limit the sensing capabilities of these vehicles. The procedure is demonstrated on an Ultra Stick 25e, therefore emphasizing a minimum complexity approach compatible with a low-cost inertial sensor. A linear model, obtained from the generic nonlinear equations of motion for aircraft, is used as a basis for system identification. This model is populated with results from a first principles analysis to form a baseline model. Flight experiments are designed using the baseline model and operational constraints to collect informative data. Parameters of the linear model are identified by fitting the model to frequency responses extracted from the data. The parameters are integrated into the nonlinear equations of motion, and both linear and nonlinear models are validated in the time domain. Verification of model accuracy is extended with a sensitivity and resid...