Recent Articles

Open access

ISSN: 2949-8554
CN: 50-1232/TP
p-ISSN: 2097-504X

Coding-based distributed filtering for cyber–physical systems under denial of service attacks

This article investigates the distributed recursive filtering problem for discrete-time stochastic cyber–physical systems. A particular feature of our work is that we consider systems in which the state...

Adaptive event-triggered coding and decoding scheme based on fuzzy logic

In this paper, we propose a fuzzy logic-based coded event-triggered control with self-adjustable prescribed performance (FL-CEC-SPP) to address the trade-off between control performance and communication...

Agentic AI: The age of reasoning—A review

Artificial intelligence has experienced a significant boom with the emergence of agentic AI, where autonomous agents are increasingly replacing human intervention, enabling systems to perceive, reason,...

Output feedback prescribed performance state synchronization for leader-following high-order uncertain nonlinear multi-agent systems

This paper addresses the synchronization of follower agents’ state vectors with that of a leader in high-order nonlinear multi-agent systems. The proposed low-complexity control scheme employs high-gain...

Adaptive optimal tracking control for underactuated surface vessels using extended state observer and reinforcement learning

This paper investigates the adaptive optimal tracking control (AOTC) for underactuated surface vessels (USVs). Compared to the majority of existing studies, the control strategy in this paper innovatively...

Essay on robust prescribed-time stabilization

As well-known, prescribed-time stabilizing design faces the need of using time-varying high gains which escape to infinity as time approaches the desired instant. In the presence of measurement noise,...

GRA: Graph-based reward aggregation for cooperative multi-agent reinforcement learning

Multi-agent reinforcement learning (MARL) has proven its effectiveness in cooperative multi-agent systems (MASs) but still faces issues on the curse of dimensionality and learning efficiency. The main...

Dual-channel event-triggered data-driven control for energy storage system with input saturation and packet loss

This paper proposes a dual-channel dynamic event-triggered (DET) constrained control strategy with packet loss compensation to regulate power in battery energy storage systems (BESSs) under packet loss...

Data-driven dual-channel event-triggered attitude control for helicopter with quantized information

In this paper, a dual-channel event-triggered quantized model-free adaptive control method for a three-degree-of-freedom helicopter attitude control system with limited communication resources is presented....

Quadrotor-based trajectory tracking control of wind turbine blades: A dual-closed-loop ADRC approach

This paper is concerned with the tracking control problem of a quadrotor for the motion trajectory of wind turbine blades subject to external disturbances. Due to the unpredictability and complexity...

Finite-time data-driven sliding-mode control for bridge cranes under sensor saturation and quantized information

This paper addresses sliding-mode control for bridge crane systems within a finite time horizon, accounting for uncertain dynamics and sensor saturation constraints. Firstly, partial feedback linearization...

Asymptotic attitude tracking control for uncertain quadrotors based on enhanced controllability condition

In this work, we delve into the asymptotic attitude tracking control problem of a class of uncertain quadrotors, considering multiple kinds of uncertainties including unknown system parameters, unmodeled...

Accurate pulmonary nodule detection via progressive multi-scale networks and geometric constraint refinement

Pulmonary nodule detection in CT images plays a crucial role in the early diagnosis of lung cancer. However, the development of efficient detection systems, especially in reliable detection of small...

Supervisory control of Petri nets with uncontrollable and unobservable transitions under replacement attacks

In this paper, we study the robust control of discrete event systems modeled by Petri nets with uncontrollable and unobservable transitions under replacement attacks. The existing supervisory control...

A dynamic weighted deep-broad learning architecture for wind power interval prediction

Predicting wind power is essential for the stable and economical operation of power grids. Traditional point forecasts often struggle to capture volatility, while wind power interval prediction (WPIP)...

Adaptive neural network fixed-time formation control of unmanned ground vehicles

This paper is concerned with the fixed-time formation control problem of unmanned ground vehicles. The essential work of this paper is the development of a practical fixed-time formation control strategy...

DistFormer+: A robotic arm collision distance estimator for multi-obstacle environments

Learning-based collision detectors have been widely applied in path planning due to their faster detection speed compared to traditional computational geometry-based collision detectors. Existing learning-based...

Tire wear aware trajectory tracking control for Multi-axle Swerve-drive Autonomous Mobile Robots

Multi-axle Swerve-drive Autonomous Mobile Robots (MS-AMRs) equipped with independently steerable wheels are commonly used for high-payload transportation. In this work, we present a novel Model Predictive...

Review on the developments of sliding function and adaptive gain in sliding mode control

Sliding mode control (SMC) is a well-known robust nonlinear control method with strong robustness and fast response which has been widely used in many applications. This paper introduces the major results...

Novel multi-agent action masked deep reinforcement learning for general industrial assembly lines balancing problems

Efficient planning of activities is essential for modern industrial assembly lines to uphold manufacturing standards, prevent project constraint violations, and achieve cost-effective operations. While...

Fuzzy adaptive finite-time inverse optimal control for active suspension systems

This paper investigates the problem of fuzzy adaptive finite-time inverse optimal control for active suspension systems (ASSs). The fuzzy logic systems (FLSs) are utilized to learn the unknown non-linear...

Privacy-preserving distributed consensus over directed networks with limited communication

The issue of privacy leakage in distributed consensus has garnered significant attention over the years, but existing studies often overlook the challenges posed by limited communication in algorithm...

CLAD: Criterion learner and attention distillation for automated CNN prunning

Filter pruning effectively compresses the neural network by reducing both its parameters and computational cost. Existing pruning methods typically rely on pre-designed pruning criteria to measure filter...

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