Event-triggered adaptive control of a class of nonlinear systems with non-parametric uncertainty in the presence of actuator failures

Ghazisaeedi, Hamid Reza; Tavazoei, Mohammad Saleh

doi:10.1177/01423312211002586

Cited by 5 publications

(6 citation statements)

References 30 publications

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“…Therefore, how to construct an adaptive finite-time tracking controller is a nontrivial task for the given nonlinear system (equation (1)). Third, too many adaptive parameters in the design procedure make the control methods (Cheng et al, 2020; Ghazisaeedi and Tavazoei. 2021; Wang et al, 2020a) impractical.…”

Section: Adaptive Finite-time Tracking Controller Designmentioning

confidence: 99%

“…Thanks to the approximation capabilities of neural networks (NNs), the adaptive tracking control scheme was proposed for uncertain nonlinear single-input and single-output (Wang et al, 2020a) and multi-input and multi-output systems (Cheng et al, 2020), respectively. By using NNs in the backstepping procedure, an adaptive control method was designed for a class of uncertain nonlinear strict-feedback systems (Ghazisaeedi and Tavazoei, 2021). On one hand, lots of parameters need to be adjusted online in the above works.…”

Section: Introductionmentioning

confidence: 99%

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Adaptive finite-time tracking control for full state constrained nonlinear systems with time-varying delays and input saturation

Fang

et al. 2021

Transactions of the Institute of Measurement and Control

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This paper investigates the adaptive finite-time tracking control problem for a class of nonlinear full state constrained systems with time-varying delays and input saturation. Compared with the previously published work, the considered system involves unknown time-varying delays, asymmetric input saturation, and time-varying asymmetric full state constraints. To ensure the state constraint satisfaction, the appropriate time-varying asymmetric Barrier Lyapunov Functions and the backstepping technique are utilized. Meanwhile, the finite covering lemma and the radial basis function neural networks are employed to solve the unknown time-varying delays. The assumption that the time derivative of time-varying delay functions is required to be less than one in traditional Lyapunov–Krasovskii functionals is removed by the proposed method. Moreover, the asymmetric input saturation is handled by an auxiliary design system. Taking the norm of the neural network weight vector as an adaptive parameter, a novel adaptive finite-time tracking controller with minimal learning parameters is constructed. It is proved that the proposed controller can guarantee that all signals in the closed-loop system are bounded, all states are constrained within the predefined sets, and the tracking error converges to a small neighborhood of the origin in a finite time. Finally, a comparison study simulation is given to demonstrate the effectiveness of our proposed strategy. The simulation results show that our proposed strategy has good advantages of high tracking precision and disturbance rejection.

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Section: Adaptive Finite-time Tracking Controller Designmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Adaptive finite-time tracking control for full state constrained nonlinear systems with time-varying delays and input saturation

Fang

et al. 2021

Transactions of the Institute of Measurement and Control

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“…A class of unknown nonlinear dynamical systems were examined by Liu and Tong (2015) using adaptive fuzzy control. Dwell time and average dwell time switching approach for adaptive neural control for switched nonlinear systems was investigated by Han et al (2009b), Ghazisaeedi and Tavazoei (2021), and Yin et al (2018).…”

Section: Introductionmentioning

confidence: 99%

Hybrid neural network control design for uncertain switched nonlinear systems with external disturbances: Application to ship maneuvering system

Bali

Singh

Kumar

2023

Transactions of the Institute of Measurement and Control

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In this work, the problem of hybrid neural network control for a class of switched uncertain nonlinear systems in strict-feedback form is considered. To approximate unknown nonlinear functions, an improved whale optimization algorithm (IWOA)-based hybrid neural network controller is introduced. Based on hybrid neural network approximation ability, a new hybrid neural network controller is constructed via the backstepping technique and the common Lyapunov function (CLF) is used for the stability analysis of the proposed model. The suggested method ensures that all signals in the closed-loop system are semi-global uniform ultimate bounded (SGUUB), and the tracking error converges to a small neighborhood of zero. Finally, the proposed scheme is applied to a ship maneuvering system and a numerical example to verify its effectiveness.

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“…To address these issues, researchers are currently working in the development of a variety of low-voltage DC-DC converters that can provide the necessary power to high-current DC applications. [1][2][3][4][5][6][7] In the subsequent section, a variety of buck converters that have been proposed and analyzed by researchers will be examined and discussed. Tapped inductor (TI) converters are a type of electronic converters that include a distinct branch in the winding path of the coupled inductor.…”

Section: Introductionmentioning

confidence: 99%

“…Nevertheless, buck converters encounter a number of obstacles, including conduction and switching losses, increased voltage stress on semiconductor devices, significant current fluctuations, and decreased efficiency relative to their typical operation. To address these issues, researchers are currently working in the development of a variety of low‐voltage DC‐DC converters that can provide the necessary power to high‐current DC applications 1–7 …”

Section: Introductionmentioning

confidence: 99%

Research and implementation of an innovative modular non‐isolated step‐down DC‐DC structure with continuous input current based on the Ćuk converter

Ghabeli Sani,

Banaei,

Hosseini

2023

Circuit Theory & Apps

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SummaryThis study proposes a new design for a non‐isolated buck converter with continuous input current. As required, the integration of additional modules into the existing structure permits a significant decrease in the converter's gain to attain significantly lower values. In order to create the proposed converter, the input voltage connections to the Ćuk converter were changed. In this configuration, the operational state of the Ćuk converter has been changed from buck‐boost to step‐down by connecting the input power source's negative polarity to the inductor's terminal. In addition, the proposed converter benefits from a common ground between the input source and output port. Moreover, it can achieve a significant reduction in gain by increasing the number of series modules. Finally, the compact converter was smoothly incorporated onto a printed circuit board (PCB) and afterward validated by an output power of 80 watts.

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Event-triggered adaptive control of a class of nonlinear systems with non-parametric uncertainty in the presence of actuator failures

Cited by 5 publications

References 30 publications

Adaptive finite-time tracking control for full state constrained nonlinear systems with time-varying delays and input saturation

Adaptive finite-time tracking control for full state constrained nonlinear systems with time-varying delays and input saturation

Hybrid neural network control design for uncertain switched nonlinear systems with external disturbances: Application to ship maneuvering system

Research and implementation of an innovative modular non‐isolated step‐down DC‐DC structure with continuous input current based on the Ćuk converter

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