Adaptive aquila optimizer for centralized mapping and exploration DOI
Faiza Gul, Imran Mir, Laith Abualigah

et al.

Pattern Analysis and Applications, Journal Year: 2024, Volume and Issue: 27(4)

Published: Sept. 25, 2024

Language: Английский

Leader-Following Consensus of Discrete-Time Nonlinear Multi-Agent Systems with Asymmetric Saturation Impulsive Control DOI Creative Commons

Yuan Qiao,

Guorong Chen, Yuan Tian

et al.

Mathematics, Journal Year: 2024, Volume and Issue: 12(3), P. 469 - 469

Published: Feb. 1, 2024

Impulsive control is an effective approach for coordinating multi-agent systems in practical environments due to its high robustness and low cost. However, impulsive exhibits characteristics such as amplitude rapid variation, potentially presenting threats the equipment. Additionally, are constrained by input saturation limitations physical controller structures information-processing capabilities. These constraints may be asymmetrical. Therefore, it necessary consider constraint when implementing control, can also mitigate posed impulse agents. This paper investigates leader-following consensus a class of discrete-time nonlinear systems, proposing asymmetric protocol reduce energy consumption damage Regarding handle saturation, proposed that eliminates need transformation from case symmetric case, which retains function directly introduces sector condition deal with nonlinearity. Furthermore, based on Lyapunov stability theory matrix theory, sufficient conditions under established, admissible region system estimated. Finally, numerical simulations provided verify validity theoretical results.

Language: Английский

Citations

3

Multi-User Detection Based on Improved Cheetah Optimization Algorithm DOI Open Access
Shuang Chen,

Yuanfa Ji,

Xiyan Sun

et al.

Electronics, Journal Year: 2024, Volume and Issue: 13(10), P. 1842 - 1842

Published: May 9, 2024

Targeting the issues of slow speed and inadequate precision optimal solution calculation for multi-user detection in complex noise environments, this paper proposes a algorithm based on Hybrid Cheetah Optimizer (HCO). The first optimizes control parameters individual update mechanism (CO) using nonlinear strategy to improve uniformity discretization search range, then dynamically introduces differential evolutionary into improved selection CO algorithm, which is utilized fine-tune space maintain local diversity during fast process. Simulation results demonstrate that not only realizes convergence with very low bit error rate (BER) at eight iterations but also has obvious advantages terms immunity, resistance far near effects, communication capacity, etc., greatly improves accuracy position solving can achieve purpose accurate environments.

Language: Английский

Citations

1

Adaptive aquila optimizer for centralized mapping and exploration DOI
Faiza Gul, Imran Mir, Laith Abualigah

et al.

Pattern Analysis and Applications, Journal Year: 2024, Volume and Issue: 27(4)

Published: Sept. 25, 2024

Language: Английский

Citations

0