In this work, we address hybrid-driven-based robust synchronization problem for multi-weighted complex dynamical networks with actuator saturation and deception attacks. The hybrid-triggered mechanism, which combines a switch between the event-triggered scheme and the time-triggered scheme, is often used to reduce the data transmission and the alleviate network burden. Further, the equivalent-input-disturbance technique is applied to eliminate the unknown disturbance effect of the addressed system. Moreover, a memory controller is designed under actuator saturation to ensure that the resultant augmented system is asymptotically synchronized even in the presence of deception attacks. Finally, three numerical examples are given to show the validity of the obtained theoretical results.
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http://dx.doi.org/10.1016/j.neunet.2023.02.031 | DOI Listing |
Neural Netw
November 2024
School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, PR China.
This paper studies the asynchronous output feedback control and H synchronization problems for a class of continuous-time stochastic hidden semi-Markov jump neural networks (SMJNNs) affected by actuator saturation. Initially, a novel neural networks (NNs) model is constructed, incorporating semi-Markov process (SMP), hidden information, and Brownian motion to accurately simulate the complexity and uncertainty of real-world environments. Secondly, acknowledging system mode mismatches and the need for robust anti-interference capabilities, a non-fragile controller based on hidden information is proposed.
View Article and Find Full Text PDFNeural Netw
November 2024
School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing 210023, China. Electronic address:
This article investigates the problem of adaptive fixed-time optimal consensus tracking control for nonlinear multiagent systems (MASs) affected by actuator faults and input saturation. To achieve optimal control, reinforcement learning (RL) algorithm which is implemented based on neural network (NN) is employed. Under the actor-critic structure, an innovative simple positive definite function is constructed to obtain the upper bound of the estimation error of the actor-critic NN updating law, which is crucial for analyzing fixed-time stabilization.
View Article and Find Full Text PDFISA Trans
November 2024
School of Electrical Engineering, Guangxi University, Nanning, 530000, PR China. Electronic address:
This paper investigates the unified tracking control problem for a class of high-order nonlinear systems with 7 kinds of irregular state constraints and input saturation based on the dynamic event-triggered mechanism. The irregular state constraints exist in practical systems, including time-varying constraints, alternation between positive and negative bounds, adding/removing constraints during system operation, and the state of the system being constrained only by the upper/lower boundaries. Auxiliary constraint boundaries are introduced to deal with these irregular state constraints.
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November 2024
State Key Laboratory of Robotics and Systems, Harbin Institute of Technology, Harbin 150000, China. Electronic address:
Due to the energy storage and release capability introduced by stiffness adjustment, a variable stiffness actuator is essential to achieve human-like energy efficiency for robots. However, it is not trivial to control the strongly coupled and nonlinear system, especially with highly dynamic stiffness variation. In this work, decoupled and robust command filtered backstepping tracking controllers for position and stiffness are proposed.
View Article and Find Full Text PDFACS Nano
October 2024
Shanghai Key Laboratory of Anesthesiology and Brain Functional Modulation, Clinical Research Center for Anesthesiology and Perioperative Medicine, Translational Research Institute of Brain and Brain-Like Intelligence, Shanghai Fourth People's Hospital, School of Medicine, Tongji University, Shanghai 200434, China.
Magnetic nanorobots are emerging players in thrombolytic therapy due to their noninvasive remote actuation and drug loading capabilities. Although the nanorobots with a size under 100 nm are ideal to apply in microvascular systems, the propulsion performance of nanorobots is inevitably compromised due to the limited response to magnetic fields. Here, we demonstrate a nattokinase-loaded magnetic vortex nanorobot (NK-MNR) with an average size around 70 nm and high saturation magnetization for mechanical propelling and thermal responsive thrombolysis under a magnetic field with dual frequencies.
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