Simulation and experimental investigation of structural dynamic frequency characteristics control.

Area of Science:

• Mechanical Engineering
• Control Systems
• Vibration Analysis

Background:

• Mechanical equipment typically operates with fixed frequency characteristics.
• Improving dynamic performance or adapting to changing conditions requires control over these characteristics.
• Existing active control methods primarily focus on reducing vibration amplitudes.

Purpose of the Study:

• To present a novel Dynamic Frequency Characteristics Active Control (DFCAC) method.
• To enable arbitrary changes in equipment dynamic characteristics beyond simple vibration reduction.
• To apply and validate the DFCAC method for a flat plate structure.

Main Methods:

• Development of a DFCAC algorithm utilizing a neural network.
• The algorithm comprises two key components: an identification module and a controller.
• Implementation and testing on a flat plate model.

Main Results:

• The DFCAC method successfully controlled vibrations.
• The method demonstrated the ability to arbitrarily alter the dynamic frequency characteristics.
• Simulations and experiments confirmed the effectiveness of the proposed approach.

Conclusions:

• The DFCAC method offers a significant advancement over traditional vibration control.
• This technique allows for adaptable dynamic performance in mechanical systems.
• The neural network-based DFCAC is a viable and effective solution for enhancing equipment dynamics.