Adaptive event-triggered SMC for stochastic switching systems with semi-Markov process and application to boost converter circuit model
In this article, the sliding mode control (SMC) design is studied for a class of stochastic
switching systems subject to semi-Markov process via an adaptive event-triggered …
switching systems subject to semi-Markov process via an adaptive event-triggered …
Event-triggered adaptive fuzzy fixed-time tracking control for a class of nonstrict-feedback nonlinear systems
H Wang, K Xu, J Qiu - … Transactions on Circuits and Systems I …, 2021 - ieeexplore.ieee.org
The problem of fuzzy-based adaptive event-triggered tracking control is investigated for a
class of non-strict-feedback nonlinear systems within fixed-time interval in this paper. Fuzzy …
class of non-strict-feedback nonlinear systems within fixed-time interval in this paper. Fuzzy …
Novel neural network fractional-order sliding-mode control with application to active power filter
J Fei, H Wang, Y Fang - IEEE transactions on systems, man …, 2021 - ieeexplore.ieee.org
In this article, a fractional-order sliding-mode control scheme based on a two-hidden-layer
recurrent neural network (THLRNN) is proposed for a single-phase shunt active power filter …
recurrent neural network (THLRNN) is proposed for a single-phase shunt active power filter …
Neural‐network‐based control for discrete‐time nonlinear systems with denial‐of‐service attack: The adaptive event‐triggered case
This article investigates a neural network (NN)‐based control problem for unknown discrete‐
time nonlinear systems with a denial‐of‐service (DoS) attack and an adaptive event …
time nonlinear systems with a denial‐of‐service (DoS) attack and an adaptive event …
Observer-based event-triggered containment control for MASs under DoS attacks
This article studies the observer-based event-triggered containment control problem for
linear multiagent systems (MASs) under denial-of-service (DoS) attacks. In order to deal with …
linear multiagent systems (MASs) under denial-of-service (DoS) attacks. In order to deal with …
Dynamic event-triggered output feedback control for load frequency control in power systems with multiple cyber attacks
This article presents a novel dynamic event-triggered scheme for the load frequency
regulation with periodic denial-of-service (DoS) attacks and deception attacks via …
regulation with periodic denial-of-service (DoS) attacks and deception attacks via …
A backstep** global fast terminal sliding mode control for trajectory tracking control of industrial robotic manipulators
We propose a backstep** global fast terminal sliding mode control for trajectory tracking
control of industrial robotic manipulators in this article. An integral of the global fast terminal …
control of industrial robotic manipulators in this article. An integral of the global fast terminal …
Bumpless Transfer H∞ Anti-Disturbance Control of Switching Markovian LPV Systems Under the Hybrid Switching
This article focuses on the bumpless transfer anti-disturbance control problem for switching
Markovian LPV systems under a hybrid switching law. A parameter-dependent multiple …
Markovian LPV systems under a hybrid switching law. A parameter-dependent multiple …
Novel LKF Method on H∞ Synchronization of Switched Time-Delay Systems
Q Qi, X Yang, Z Xu, M Zhang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
This article investigates global asymptotic synchronization (GAS) of switched nonlinear
systems with delay. By introducing mode-dependent double event-triggering mechanisms …
systems with delay. By introducing mode-dependent double event-triggering mechanisms …
Neural adaptive self-triggered control for uncertain nonlinear systems with input hysteresis
J Wang, H Zhang, K Ma, Z Liu… - IEEE transactions on …, 2021 - ieeexplore.ieee.org
The issue of neural adaptive self-triggered tracking control for uncertain nonlinear systems
with input hysteresis is considered. Combining radial basis function neural networks …
with input hysteresis is considered. Combining radial basis function neural networks …