Enhanced  adaptive control for a benchmark piezoelectric‐actuated system via fuzzy approximation

Yousef, Hassan; Hamdy, Mohamed; Saleem, Ashraf; Nashed, Kyrillos; Mesbah, Mustafa; Shafiq, Muhammad

doi:10.1002/acs.3033

Cited by 36 publications

(17 citation statements)

References 47 publications

(72 reference statements)

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“…However, some of the studies have indirect comparability to the presented study though they show high affluence on fuzzy control system design [17, 18, 24–29]. Also, more literature can be seen in [36–44]. Despite the above‐proposed control methods, yet the problem of disturbance rejection for DP control has been a big challenge.…”

Section: Introductionmentioning

confidence: 70%

Dynamic positioning of ships based on robust fuzzy observer

Ngongi

Massami

et al. 2020

J. eng.

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Section: Introductionmentioning

confidence: 70%

Dynamic positioning of ships based on robust fuzzy observer

Ngongi

Massami

et al. 2020

J. eng.

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“…For observer (15), the definitions of estimation error of the weights p+1 to n and its dynamics using the EKF algorithm (5) for observer (15) is (26). The output error (9) can be rewritten as (27) withx as (28).…”

Section: Rhonn Observermentioning

confidence: 99%

Real‐time neural observer‐based controller for unknown nonlinear discrete delayed systems

Rios

Alanis

Arana‐Daniel

et al. 2020

Intl J Robust & Nonlinear

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This work presents a neural observer-based controller for uncertain nonlinear discrete-time systems with unknown time-delays. The proposed neural observer does not need previous knowledge of the model about the system under consideration, neither the value of its parameters, delays, nor their explicit estimations. The proposed neural observer is based on a neural network composed of two recurrent high order neural networks (RHONNs) for nonmeasurable state variables, one in a parallel configuration, and for measurable state variables one in a series-parallel configuration. The neural network is trained on-line with an extended Kalman filter algorithm. The proposed RHONN observer provides a mathematical model for the system. Based on such a resulting mathematical model, a control law is designed using discrete-time sliding mode block control. Applicability is presented using real-time results that show the performance of the proposal using a linear induction motor prototype as the selected system; this prototype is under the presence of varying time-delays. A Lyapunov analysis is included to prove the semi-globally uniformly ultimately boundedness (SGUUB) of the proposed RHONN observer-controller scheme for uncertain nonlinear discrete-time systems with unknown delays. K E Y W O R D S discrete-time sliding modes, Lyapunov stability, neural block control, neural state estimation, real-time, time-delay systems 8402

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“…On the other hand, the nonlinearities have been appeared in most of the physical plant and practical applications such as robots, power systems and in other more systems. [15][16][17][18][19][20][21] Hence, many control approaches have been presented to deal with nonlinear systems. One of these approaches is Takagi-Sugeno (T-S) fuzzy model, which has the ability to describe the nonlinear systems.…”

Section: Introductionmentioning

confidence: 99%

Design of equivalent‐input‐disturbance estimator based modified repetitive control with adaptive periodic event‐triggered for time‐varying delay nonlinear systems

Abd‐Elhaleem

Soliman

Hamdy

2022

Intl J Robust & Nonlinear

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This article addresses the problems of the disturbance rejection and the periodic signal tracking for a class of time-varying delay nonlinear systems subjected to unknown exogenous disturbances. To approximate the nonlinearity of the system, a Takagi-Sugeno (T-S) fuzzy model has been used. The proposed modified repetitive controller (MRC) scheme based on the equivalent-input-disturbance (EID) estimator improves the performance of periodic and aperiodic unknown disturbances rejection effectively and achieves good tracking performance for periodic references. Furthermore, an adaptive periodic event triggered mechanism based fuzzy state observer (APETM-FSO) has been utilized to reduce data transmission, energy consumption, and computational burden, save the resources of communication. With the help of a designed adaptive event triggering condition, the APETM can detect the event occurrence, which is described by exceeding the error signal to a predetermined threshold. Only when the event occurs, the current data are transmitted otherwise, data can be kept unchanged using a zero-order hold. Hence, The MRC, EID, and APETM-FSO based on a time-varying delay T-S fuzzy model construct the overall system. Then, to achieve the asymptotic stability of the overall system subjected to unknown disturbances, sufficient conditions based on the Lyapunov-Krasovskii functional stability theory and linear matrix inequalities (LMIs) are derived. In addition, the FSO and fuzzy state feedback controller gains are designed using the matrix decomposition and LMI approaches. Simulation results with comparative study are presented to demonstrate the effectiveness and feasibility of the proposed scheme.

show abstract

Enhanced adaptive control for a benchmark piezoelectric‐actuated system via fuzzy approximation

Cited by 36 publications

References 47 publications

Dynamic positioning of ships based on robust fuzzy observer

Dynamic positioning of ships based on robust fuzzy observer

Real‐time neural observer‐based controller for unknown nonlinear discrete delayed systems

Design of equivalent‐input‐disturbance estimator based modified repetitive control with adaptive periodic event‐triggered for time‐varying delay nonlinear systems

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