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${\cal H}_{\infty}$ Step Tracking Control for Networked Discrete-Time Nonlinear Systems With Integral and Predictive Actions

Zhang, Hui, Shi, Yang, Liu, Mingxi·2013·IEEE Transactions on Industrial Informatics

Abstract

This paper investigates the step tracking control problem for discrete-time nonlinear systems in a networked environment with a limited capacity. The nonlinear system is represented by a Takagi-Sugeno (T-S) fuzzy system, and a network-induced delay is incorporated in the modeling of the connection link. In order to compensate for the network link effects and eliminate the tracking error, we employ some techniques mainly used in the predictive control and the integral control. Moreover, a quadratic cost function which includes terms related to the performance of the system and the actuating capacity is used. We assume that the lumped network-induced delay lies within a known set, and that the occurrence probability for each element in the set is known a priori. Then, the delay information will be incorporated into the delay-dependent tracking controllers. The parameters for the tracking controller are derived by solving an optimization problem. A networked inverted pendulum is used to illustrate the efficacy of the proposed design method.

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Metadata

Authors
Zhang, H., Shi, Y., & Liu, M.
Venue
IEEE Transactions on Industrial Informatics
Published
2013-02
Volume
9
Issue
1
Pages
337-345
ISSN
  • 1551-3203 (ISSN-L)
  • 1941-0050
OpenAlex
W1561568282
Cited by
181
References
0
FWCI
53.78
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: ${\cal H}_{\infty}$ Step Tracking Control for Networked Discrete-Time Nonlinear Systems With Integral and Predictive Actions. https://app.cochat.ai/papers/10.1109/tii.2012.2225434
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Zhang, H., Shi, Y., & Liu, M. (2013). ${\cal H}_{\infty}$ Step Tracking Control for Networked Discrete-Time Nonlinear Systems With Integral and Predictive Actions. IEEE Transactions on Industrial Informatics. https://doi.org/10.1109/tii.2012.2225434

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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.