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International Journal of Modelling Identification and Control is a peer-reviewed journal published by Inderscience, covering Adaptive Control of Nonlinear Systems, Advanced Control Systems Optimization, Fault Detection and Control Systems.
| Publisher | Inderscience |
|---|---|
| Reference style | Author–year (Harvard/AGSM) Author–year — (Smith, 2023) in the text Smith, A., Jones, B. and Lee, C. (2023) 'A representative article title', International Journal of Modelling Identification and Control, 12(3), pp. 45–58.
Formats any DOI in International Journal of Modelling Identification and Control style. No sign-up. |
| Publishes research in | Adaptive Control of Nonlinear Systems Advanced Control Systems Optimization Fault Detection and Control Systems Control Systems and Identification Stability and Control of Uncertain Systems |
| ISSN | 1746-6172 |
| Citation impact (2-yr) | 0.28 |
| h-index | 33 |
| i10-index | 264 |
| Total citations | 10,654 |
| Top institutions publishing here | Hebei University of Science and Technology |
| Journal website | www.inderscience.com |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Citations each year’s papers have accumulated so far — the most recent years are still building up.
Non-linear state estimation and some related topics like parametric estimation, fault diagnosis and perturbation attenuation are tackled here via a new methodology in numerical differentiation. The corresponding basic system theoretic definitions and properties are presented within the framework of differential algebra, which permits to handle system variables and their derivatives of any order. Several academic…
Synchronisation of chaotic systems is an important research problem in chaos theory. In this research work, a novel sliding mode control method is proposed for the global chaos synchronisation of identical chaotic systems. The general result derived using novel sliding mode control method is established using Lyapunov stability theory. As an application of the general…
Multicollinearity occurs in a dataset due to correlation between the predictors. Models derived from such data without a check on multicollinearity may lead to erroneous system analysis. This problem can be eliminated by the selection of appropriate predictors from the dataset. Variable reduction methods like B2, B4, VIF, KIF and factor analysis (FA) can be…
The swarm intelligence literature frequently asserts that swarms exhibit high levels of robustness. That claim is, however, rather less frequently supported by empirical or theoretical analysis. But what do we mean by a 'robust' swarm? How would we measure the robustness or – to put it another way – fault-tolerance of a robotic swarm? These…
This research work describes the design and SPICE implementation of a 12-term novel hyperchaotic system with four quadratic nonlinearities. The Lyapunov exponents of the dissipative novel hyperchaotic system are obtained as L1 = 4.1043, L2 = 0.1571, L3 = 0 and L4 = −34.2529. The maximal Lyapunov exponent (MLE) of the novel hyperchaotic system is…
