Dynamic event‐triggered control for singularly perturbed systems

Tong, Hua; Xiao, Jiang‐Wen; Lei, Yan; Yang, Wu

doi:10.1002/rnc.5622

Cited by 16 publications

(11 citation statements)

References 31 publications

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“…Suppose 𝛿 = 0.15. Then, by solving the LMI (20) in Theorem 1, we have Moreover, the feasible solutions of the LMIs ( 28)-( 29) in Theorem 2 are as follows:…”

Section: Comparison Of the Pwl Model And The Augment Model Methodsmentioning

confidence: 99%

“…This advantage will be proved in the example section. On the other hand, compared with the PWL model method, less free variables are involved by using the augmented model method, see LMI (20). Thus, the computation is reduced.…”

Section: Piecewise Linear Modelmentioning

confidence: 99%

“…Event-triggered schemes (ETSs) reduce the transmission rate while achieving the control performance. [17][18][19][20][21] The measurements are transmitted when the conditions of ETSs are satisfied. Lately, event-triggered predictive control begins to gain attention.…”

Section: Introductionmentioning

confidence: 99%

“…Event‐triggered schemes (ETSs) reduce the transmission rate while achieving the control performance 17‐21 . The measurements are transmitted when the conditions of ETSs are satisfied.…”

Section: Introductionmentioning

confidence: 99%

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Dynamic event‐triggered networked predictive control for discrete‐time NCSs under deception attacks

Wang

et al. 2022

Intl J Robust & Nonlinear

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This paper investigates the dynamic event-triggered predictive control problem for discrete-time networked control systems under deception attacks. A new dynamic event-triggered scheme is proposed for discrete-time networked predictive control systems to reduce the data transmission. The feature of the dynamic event-triggered scheme is that the triggering threshold is adjusted dynamically.The Luenberger observer is provided to estimate the output measurements. The networked predictive control method is used to compensate for the time delay. Next, by using the piecewise linear model and the augmented model methods, sufficient conditions are established to guarantee the mean square asymptotic stability of the closed-loop systems, respectively. Finally, the effectiveness of the proposed approach is validated via a buck DC-DC converter system.

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“…Suppose 𝛿 = 0.15. Then, by solving the LMI (20) in Theorem 1, we have Moreover, the feasible solutions of the LMIs ( 28)-( 29) in Theorem 2 are as follows:…”

Section: Comparison Of the Pwl Model And The Augment Model Methodsmentioning

confidence: 99%

Section: Piecewise Linear Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…Event‐triggered schemes (ETSs) reduce the transmission rate while achieving the control performance 17‐21 . The measurements are transmitted when the conditions of ETSs are satisfied.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Dynamic event‐triggered networked predictive control for discrete‐time NCSs under deception attacks

Wang

et al. 2022

Intl J Robust & Nonlinear

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show abstract

“…In order to solve the finite time tracking control problem, an adjustable time performance function was introduced in [18], and the controller design can smoothly switch between fixed and relative threshold strategies. In [10] , a dynamic event-triggered control scheme was designed for singularly perturbed systems.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy observer-based command filtered tracking control for uncertain strict-feedback nonlinear systems with sensor faults and event-triggered technology

Sun

Gao²,

Wu³

et al. 2023

Nonlinear Dyn

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For the trajectory tracking problem of nthorder uncertain nonlinear systems with strict feedback, a fuzzy controller based on command filtered and eventtriggered technology is designed to improve the tracking error of the system. Concurrently, a fault-tolerant control scheme is introduced to effectively solve the problem of sudden output sensor failure. Additionally, the proposed controller can also greatly avoid the "differential explosion" problem of derivations of virtual control laws, which makes the design of the controller simpler. Furthermore, an effective observer is designed to solve the problem of system state immeasurability. The control law designed by this method does not need to include the known function of the system state equation. Therefore, the proposed control scheme makes the design of the controller more convenient and flexible. According to Lyapunov stability theory, it is proved that all the signals in the closed-loop system are uniformly and ultimately bounded. Finally, two simulation examples of second-order nonlinear system and single link robot show the effectiveness of the proposed scheme.

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Hybrid‐driven‐based resilient control for networked T‐S fuzzy systems with time‐delay and cyber‐attacks

Saravanakumar

Lee

2023

Intl J Robust & Nonlinear

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This work investigates design problem of the hybrid-triggered-based resilient controller for a class of Takagi-Sugeno (T-S) fuzzy systems subject to nondeterministic cyber-attacks, probabilistic time-delay, controller gain variations and actuator failures in which nondeterministic cyber-attacks and hybrid-triggered mechanism are implemented by probabilistic variables gratifying the Bernoulli distributions. To save the network resources, a new kind of hybrid-triggered-based resilient controller design is introduced. By employing Lyapunov technique together with improved Wirtinger's integral inequalities and event-generator function, new delay-dependent sufficient conditions are constructed which assures that the resulting closed-loop system is mean square asymptotically stable and satisfies a prescribed performance. At last, two numerical examples are provided to display the effectiveness and advantage of the constructed method.

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Dynamic event‐triggered control for singularly perturbed systems

Cited by 16 publications

References 31 publications

Dynamic event‐triggered networked predictive control for discrete‐time NCSs under deception attacks

Dynamic event‐triggered networked predictive control for discrete‐time NCSs under deception attacks

Fuzzy observer-based command filtered tracking control for uncertain strict-feedback nonlinear systems with sensor faults and event-triggered technology

Hybrid‐driven‐based resilient control for networked T‐S fuzzy systems with time‐delay and cyber‐attacks

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