Active Vibration Control of a Smart Structure Using Neural Network
Vibration is a major problem that can cause structures to wear out prematurely and even fail. Smart structures are a promising solution to this problem because they can be equipped with actuators, sensors, and controllers to reduce or eliminate vibration. This work will study a complete analytical model of a cantilever beam equipped with a pair of piezoelectric actuators and a single piezoelectric sensor. First, we will use a couple of collocated piezoelectric actuators and a sensor to measure and control vibration levels based on a PID controller. Next, we are going to design an artificial neural network (ANN) to enhance the ability of the classical PID controller to self-tune its parameters. For training the artificial neural network, we will use one of the evolutionary algorithms to generate a dataset of the system for the training. Finally, we will compare the effect of the PID self-tuned by ANN and the classical PID controller on the system’s stability and performance. Thus, this work will thoroughly understand the potential vibration control of the cantilever beam.
Authors
- Ahmed Abdulrahman Mohammed
- Sami El Ferik (ORCID: https://orcid.org/0000-0001-5648-4786)
- Abdul‐Wahid A. Saif (ORCID: https://orcid.org/0000-0003-2969-1581)
- Fouad M. AL‐Sunni
Institutions
- King Fahd University of Petroleum and Minerals (SA)
Publication Details
- Published
- 2024-11-06
- DOI
- https://doi.org/10.1109/dese63988.2024.10912042
- Primary Topic
- Structural Health Monitoring Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- King Fahd University of Petroleum and Minerals