Improving the performance of networked control systems with time delay and data dropouts based on fuzzy model predictive control

Sakr, Ahmad; El-Nagar, Ahmad M.; El-Bardini, Mohammad; Sharaf, M.M.

doi:10.1016/j.jfranklin.2018.07.012

Cited by 17 publications

(3 citation statements)

References 32 publications

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“…Thus, the sector nonlinearities are closer to the actual nonlinearities, and the less conservative stability results can be obtained in the controller design. The T-S fuzzy model offers nice theory framework to denote the system plant as average weighted sum of semi-linear subsystems (Sakr, Elnagar, Elbardini, & Sharaf, 2019;He, Liu, Wu, & Li, 2020). Thus, the T-S fuzzy model is employed in this paper.…”

Section:  mentioning

confidence: 99%

LMIs-based stability analysis and fuzzy-logic controller design for networked systems with sector nonlinearities: Application in tunnel diode circuit

Zheng¹,

Zhang²,

Lam³

et al. 2022

Expert Systems with Applications

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Section:  mentioning

confidence: 99%

LMIs-based stability analysis and fuzzy-logic controller design for networked systems with sector nonlinearities: Application in tunnel diode circuit

Zheng¹,

Zhang²,

Lam³

et al. 2022

Expert Systems with Applications

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“…17 Networked predictive control (NPC) to compensate network delay is discussed by Liu, 18 NPC scheme has been recorded as an effective method for time delay and packet loss. [19][20][21] The outputbased predictive control problem of networked control linear systems with time delay is studied in the study by Yang and Zheng, 22 and the cooperation of NPC, eventtriggered mechanism (ETM), and KF is considered. Inspirationally, the research on event-based predictive control of IT2 T-S fuzzy system under KF needs to be further developed, which is one of the motivations of this article.…”

Section: Introductionmentioning

confidence: 99%

Event-based predictive control for interval type-2 Takagi–Sugeno fuzzy systems under Kalman filter

Wang,

Rong,

2024

Proceedings of the Institution of Mechanical Engineers, Part I:

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In this article, the event-based predictive control problem for a class of interval type-2 Takagi–Sugeno fuzzy system is investigated. To reduce the influence of Gaussian noise, an improved Kalman filter is proposed, in which the system state is filtered or not depends on an event-triggered mechanism. Then, by designing the network predictive control scheme via interval type-2 fuzzy model, some sufficient conditions are derived, which guarantee the Schur stabilization of the concerned system subject to network delays. Finally, the correctness and effectiveness are verified by two simulation examples.

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“…An adaptive Smith predictor control problem was investigated in an NCS by incorporating an estimated time delay in the Smith predictor, thus achieving desired tracking performance [12]. A modified Smith predictor combined with a fuzzy model predictive control (FMPC) overcomes the stabilization problem in an NCS [13]. The Smith estimator controller finds it difficult to apply the Smith estimator to the unstable and disturbed networked control system, though it could compensate for constant delay and improve the control performance of an NCS.…”

Section: Introductionmentioning

confidence: 99%

An Improved Equivalent-Input-Disturbance Method for Uncertain Networked Control Systems with Packet Losses and Exogenous Disturbances

She

Liu

et al. 2021

Actuators

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In a networked control system (NCS), time delays, uncertainties, packet losses, and exogenous disturbances seriously affect the control performance. To solve these problems, a modified disturbance suppression configuration of NCS was built. In the configuration, a proportional–integral observer (PIO) reproduces the state of a plant and reduces the observation error; an equivalent input disturbance (EID) estimator estimates and compensates for the disturbance in the control input channel. The stability conditions of the NCS are given by using a linear matrix inequality, and the gains of the PIO and state feedback controller are obtained. Numerical simulation results and an application of a magnetic levitation ball system verifies the effectiveness of the presented method. Comparison with the conventional PIO and EID methods shows that the presented method reduced the tracking error to about one-fifth and two-thirds of their original values, respectively. This demonstrates the validity and superiority of the presented method.

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Improving the performance of networked control systems with time delay and data dropouts based on fuzzy model predictive control

Cited by 17 publications

References 32 publications

LMIs-based stability analysis and fuzzy-logic controller design for networked systems with sector nonlinearities: Application in tunnel diode circuit

LMIs-based stability analysis and fuzzy-logic controller design for networked systems with sector nonlinearities: Application in tunnel diode circuit

Event-based predictive control for interval type-2 Takagi–Sugeno fuzzy systems under Kalman filter

An Improved Equivalent-Input-Disturbance Method for Uncertain Networked Control Systems with Packet Losses and Exogenous Disturbances

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