Results 101 to 110 of about 93,147 (298)

Subspace state space system identification for industrial processes

Journal of Process Control, 1998
Abstract We give a general overview of the state-of-the-art in subspace system identification methods. We have restricted ourselves to the most important ideas and developments since the methods appeared in the late eighties. First, the basics of linear subspace identification are summarized.
Wouter Favoreel, Bart De Moor, Peter Van Overschee   +2 more
openaire   +1 more source

Data-driven modelling of a commercial cold storage system using subspace system identification

e-Prime: Advances in Electrical Engineering, Electronics and Energy
This study presents subspace system identification of a cold storage system incorporating external temperature as input. The proposed model presents a holistic view of the whole system with each subsystem cohesively linked together.
Adesola Temitope Bankole, Muhammed Bashir Mu’azu, Habeeb Bello-Salau, Zaharuddeen Haruna   +3 more
doaj   +1 more source

A CUSUM test with sliding reference for ground resonance monitoring [PDF]

, 2011
Ground resonance is potentially destructive oscillations that may develop on helicopters rotors when the aircraft is on or near the ground. Therefore, this unstable phenomenon has to be detected before it occurs in order to be avoided by the pilot.
Jhinaoui, Ahmed, Mevel, Laurent, Morlier, Joseph   +2 more
core   +2 more sources

Maximum Entropy Vector Kernels for MIMO system identification

, 2016
Recent contributions have framed linear system identification as a nonparametric regularized inverse problem. Relying on $\ell_2$-type regularization which accounts for the stability and smoothness of the impulse response to be estimated, these ...
Chiuso, Alessandro, Pillonetto, Gianluigi, Prando, Giulia   +2 more
core   +1 more source

Enhanced Subspace Dynamic Mode Decomposition for Operational Modal Analysis of Aerospace Structures

Aerospace
To address the issue of low accuracy in the dynamic modal decomposition (DMD) method used for operational modal analysis (OMA) under noise conditions of aerospace structures, an enhanced identification approach is proposed in this paper, which integrates
Hao Zheng, Rui Zhu, Yanbin Li
doaj   +1 more source

LAPACK-Based Software for Subspace Identification [PDF]

, 1996
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Sima, V. (1), Varga, A., Verhaegen, M. (2) (1) Inst. for Informatics Bucharest   +2 more
core  

Elevator dynamic monitoring and early warning system based on machine learning algorithm

IET Networks, EarlyView., 2022
In order to monitor and warn the elevator dynamics, in this work, the machine learning algorithm is introduced, and the particle swarm algorithm is used to perfect the model. The model is optimised, and the experimental comparison shows that the optimisation of the model parameters can further improve the accuracy of the elevator load prediction. Then,
Shuai Zhang, Qiangguo Yin, Jinlong Wang
wiley   +1 more source

Extracting inter-area oscillation modes using local measurements and data-driven stochastic subspace technique

Journal of Modern Power Systems and Clean Energy, 2017
In this paper, a data-driven stochastic subspace identification (SSI-DATA) technique is proposed as an advanced stochastic system identification (SSI) to extract the inter-area oscillation modes of a power system from wide-area measurements. For accurate
Deyou YANG, Guowei CAI, Kevin CHAN
doaj   +1 more source

A compatibility criterion for optimal control and information aggregation in hierarchical network systems

Asian Journal of Control, EarlyView.
Abstract Large swarms often adopt a hierarchical network structure that incorporates information aggregation. Although this approach offers significant advantages in terms of communication efficiency and computational complexity, it can also lead to degradation due to information constraints.
Kento Fujita, Daisuke Tsubakino
wiley   +1 more source

Research on Model Identification of Permanent Magnet DC Brushless Motor Based on Auxiliary Variable Subspace Identification Algorithm

World Electric Vehicle Journal
This paper proposes a model identification method based on the auxiliary variable closed-loop subspace identification algorithm to address the problem of modeling difficulties caused by various complex factors affecting permanent magnet brushless DC ...
Jing Zhang, Yuhui Liu, Te Chen, Guowei Dou   +3 more
doaj   +1 more source