Intelligent Optimization Algorithms for Vibration Control of Mechanical Systems

DOI

10.2991/978-94-6463-823-3_37How to use a DOI?

Keywords

Vibration Control; Genetic Algorithm; Firefly Algorithm; Multi-objective Optimization; Nonlinear Systems

Abstract

Vibration control occupies an important position in mechanical systems, but traditional experience-based, or single-objective, control methods are often difficult to cope with the challenges posed by complex structures, high precision, and multi-objective requirements. For this reason, various intelligent optimization algorithms have been introduced to improve the efficiency and robustness of system vibration reduction. This thesis systematically analyzes the application of various algorithms such as Genetic Algorithm (GA), Firefly Algorithm (AFA), and Multi-objective Optimization Algorithm. In addition, Hybrid Genetic Algorithm (HTGA) incorporating Orthogonal Function Approach (OFA) and Particle Swarm Algorithm (PSO) incorporating fuzzy control has also attracted much attention in the field of vibration control. It is shown that these algorithms have made significant progress in sensor-actuator layout, nonlinear system parameter tuning, and optimal design under multi-objective constraints: They can effectively reduce vibration amplitude. Moreover, they achieve a balance between vibration reduction efficiency, energy consumption, and system stability. The above research results provide a more forward-looking technical path and theoretical support for vibration control under complex working conditions and uncertainties, and lay an important foundation for high-precision and high-reliability mechanical system design.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

TY  - CONF
AU  - Yinxue Mu
PY  - 2025
DA  - 2025/08/31
TI  - Intelligent Optimization Algorithms for Vibration Control of Mechanical Systems
BT  - Proceedings of the 2025 3rd International Conference on Image, Algorithms, and Artificial Intelligence (ICIAAI 2025)
PB  - Atlantis Press
SP  - 376
EP  - 386
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-823-3_37
DO  - 10.2991/978-94-6463-823-3_37
ID  - Mu2025
ER  -