Bio-inspired sensing and actuating architectures for feedback control of civil structures

Area of Science:

• Structural Engineering
• Control Systems
• Bio-inspired Engineering

Background:

• Civil structures face failure risks from environmental loads like earthquakes and wind.
• Active feedback control systems offer solutions but face adoption challenges.
• Biological systems provide advanced signal processing and actuation techniques.

Purpose of the Study:

• To develop a bio-inspired control algorithm for civil structures.
• To simplify control computations by mimicking biological sensory systems, specifically the mammalian auditory system.
• To explore methods for determining optimal weighting matrices for the control law.

Main Methods:

• Developed a bio-inspired control algorithm using signal processing from the mammalian auditory system.
• Investigated particle swarm optimization, artificial neural networks, and optimal control theory for deriving the weighting matrix (W).
• Simulated the algorithm on a five-story benchmark structure and compared it to a linear quadratic regulator (LQR).

Main Results:

• The bio-inspired control law is a weighted combination of structural response (F=WN).
• Particle swarm optimization (PSO) demonstrated the most effective control among the tested methods.
• The PSO-based bio-inspired control performance was comparable to the traditional LQR method.

Conclusions:

• Bio-inspired control algorithms, particularly those using PSO for weighting matrix optimization, show significant promise for civil structure protection.
• Mimicking biological systems offers a viable approach to overcome challenges in active feedback control for structures.
• The developed algorithm provides an effective and comparable alternative to traditional control strategies.