Topic
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 article, a proportional, multiple-integral and derivative (PMID) observer is proposed to simultaneously estimate system states, fault signals, the derivatives of the faults, and attenuate disturbances successfully.
Abstract: We present a proportional, multiple-integral and derivative (PMID) observer technique that can simultaneously estimate system states, fault signals and the finite times derivatives of the faults for a descriptor system with input and measurement faults. Furthermore for a descriptor system with input and measurement faults and unknown disturbances (including modelling errors), a robust PMID observer is designed to simultaneously estimate system states, fault signals, the derivatives of the faults, and attenuate disturbances successfully. Fault-tolerant design is another important issue in this study. By using the obtained estimates of states and faults, and linear matrix inequality technique, a fault-tolerant control scheme is addressed, which ensures the closed-loop plant to be internally proper stable with prescribed H
infin
performance index even as unbounded faults occur. Finally, a numerical example is given to illustrate the design procedures, and simulations show satisfactory tracking and fault-tolerant control performance.
106 citations
TL;DR: This paper studies the quality of system identification models obtained using the standard quadratic prediction error criterion for a general linear model class and shows that although these variables often do not enter in asymptotic convergence results, they do play an important role when the data sample is finite.
Abstract: In this paper we study the quality of system identification models obtained using the standard quadratic prediction error criterion for a general linear model class. The main feature of our results is that they hold true for a finite data sample and they are not asymptotic. The main theorems bound the difference between the expected value of the identification criterion evaluated at the estimated parameters and at the optimal parameters. The bound depends naturally on the model and system order, the pole locations, and the noise variance, and it shows that although these variables often do not enter in asymptotic convergence results, they do play an important role when the data sample is finite.
105 citations
TL;DR: In this article, a mode I cohesive crack model is used for the identification of the material parameters, together with their uncertainties, in a discrete crack model, on the basis of experimental data generated by wedge-splitting tests on concrete specimens.
105 citations
TL;DR: This work investigates dynamic versions of fuzzy logic systems and, specifically, their non-Singleton generalizations (NSFLSs), and derives a dynamic learning algorithm to train the system parameters, and studies the performance of both dynamic and static FLSs in the predictive modeling of a NARMA process.
Abstract: We investigate dynamic versions of fuzzy logic systems (FLSs) and, specifically, their non-Singleton generalizations (NSFLSs), and derive a dynamic learning algorithm to train the system parameters. The history-sensitive output of the dynamic systems gives them a significant advantage over static systems in modeling processes of unknown order. This is illustrated through an example in nonlinear dynamic system identification. Since dynamic NSFLS's can be considered to belong to the family of general nonlinear autoregressive moving average (NARMA) models, they are capable of parsimoniously modeling NARMA processes. We study the performance of both dynamic and static FLSs in the predictive modeling of a NARMA process.
105 citations
TL;DR: In this paper, an aircraft trajectory controller, which uses the Incremental Nonlinear Dynamic Inversion, is proposed to achieve fault-tolerant trajectory control in the presence of model uncertainties and actuator faults.
105 citations