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System identification
About: System identification is a research topic. Over the lifetime, 21291 publications have been published within this topic receiving 439142 citations.
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TL;DR: In this paper, a common family of estimation methods for system identification, viz, prediction error methods, is described and an overview of typica and typica-based methods is given.
Abstract: This contribution describes a common family of estimation methods for system identification, viz, prediction-error methods. The basic ideas behind these methods are described. An overview of typica ...
244 citations
TL;DR: In this paper, the authors consider experimental designs for discriminating between three or more rival regression models and show that the results are similar to those of the earlier one, except in some simple cases, a straightforward generalization of those when there are only two models.
Abstract: In this paper we consider experimental designs for discriminating between three or more rival regression models. In an earlier paper (Atkinson & Fedorov, 1975) we described optimal designs for discriminating between two models. Although the approach and nomenclature of the present paper are similar to those of the earlier one, the results are not, except in some simple cases, a straightforward generalization of those when there are only two models. We now suppose that there are v rival regression models
243 citations
TL;DR: This work model the input and output missing data as two separate Bernoulli processes characterised by probabilities of missing data, then a missing output estimator is designed, and a recursive algorithm for parameter estimation is developed by modifying the Kalman filter-based algorithm.
Abstract: We consider the problem of parameter estimation and output estimation for systems in a transmission control protocol (TCP) based network environment. As a result of networked-induced time delays and packet loss, the input and output data are inevitably subject to randomly missing data. Based on the available incomplete data, we first model the input and output missing data as two separate Bernoulli processes characterised by probabilities of missing data, then a missing output estimator is designed, and finally we develop a recursive algorithm for parameter estimation by modifying the Kalman filter-based algorithm. Under the stochastic framework, convergence properties of both the parameter estimation and output estimation are established. Simulation results illustrate the effectiveness of the proposed algorithms.
242 citations
01 Aug 1994
TL;DR: In this paper, the state of the art of motion systems particularly emphasizing both estimation and identification of parameters and control variables of an electric-motor-driven motion system is presented, and the total robustness is attained by integrating advances of control technique on the electrical aspect and the mechanical aspect.
Abstract: The paper presents the state of the art of motion systems particularly emphasizing both estimation and identification of parameters and control variables of an electric-motor-driven motion system. In a modern electrical drive system, it is required to take not only the electrical aspect but also the mechanical phase into total system consideration. Improvement in electrical aspect needs a variety of information pertaining to electrical machines and power electronic circuits for improving AC variable-speed drives. Important techniques of identification or estimation of parameters and control variables in AC drives are explained. Such information includes machine parameters, flux, speed, position, and so on. Also, the paper shows that there is some theoretical limit of performance. For improvement of the mechanical phase, the disturbance torque is the most important variable to be identified. It is used in motion control systems, for example, in the feedback loop. Various applications are possible by modification of such a basic approach. As a conclusion, the paper shows that the total robustness is attained by integrating advances of control technique on the electrical aspect and the mechanical aspect. There are numerous variations of controller by possible combinations of these two aspects according to applications. >
241 citations