Abstract: In this paper, an improved ant colony optimization (ICMPACO) algorithm based on the multi-population strategy, co-evolution mechanism, pheromone updating strategy, and pheromone diffusion ...

Abstract: The finite/fixed-time stabilization and tracking control is currently a hot field in various systems since the faster convergence can be obtained. By contrast to the asymptotic stability, ...

Abstract: This article concerns optimal prescribed-time formation control for a class of nonlinear multiagent systems (MASs). Optimal control depends on the solution of the Hamilton–Jacobi–Bellman ...

Abstract: This technical note presents a continuous-time multi-agent system for distributed optimization with an additive objective function composed of individual objective functions subject to bound ...

Abstract: Magnetic miniature robots are promising tools for minimally invasive and noninvasive therapy. Constructing systems with actuation–perception loops is an essential step to progress from ...

Abstract: Recently, the advancement of deep learning (DL) in discriminative feature learning from 3-D LiDAR data has led to rapid development in the field of autonomous driving. However, automated ...

Abstract: Human gaze provides valuable information on human focus and intentions, making it a crucial area of research. Recently, deep learning has revolutionized appearance-based gaze estimation.

Abstract: The coupling between the active and the reactive power of the droop-controlled inverter is critical in the low-voltage microgrid. The conventional virtual power-based control strategy can ...

Abstract: Over the last several years, the field of natural language processing has been propelled forward by an explosion in the use of deep learning models. This article provides a brief ...

Abstract: The lithium-ion batteries used in electric vehicles have a shorter lifespan than other vehicle components, and the degradation mechanism inside these batteries reduces their life even more.

Abstract: The traditional deep learning-based bearing fault diagnosis approaches assume that the training and test data follow the same distribution. This assumption, however, is not always true for ...

Abstract: This article proposes a novel framework to manage subgroups' noncooperative behavior by weight penalty in large-scale group decision making. To do that, a trust-consensus index (TCI) is ...