Optimization and vibration suppression of adaptive composite panels using genetic algorithm and disturbance observer technique

Su Yan; Mehrdad N. Ghasemi-Nejhad

doi:10.1117/12.482732

1 August 2003 Optimization and vibration suppression of adaptive composite panels using genetic algorithm and disturbance observer technique

Su Yan, Mehrdad N. Ghasemi-Nejhad

Author Affiliations +

Proceedings Volume 5049, Smart Structures and Materials 2003: Modeling, Signal Processing, and Control; (2003) https://doi.org/10.1117/12.482732
Event: Smart Structures and Materials, 2003, San Diego, California, United States

Abstract

In this paper, a model of the adaptive composite panel surfaces with piezoelectric patches is built using the Rayleigh-Ritz method based on the laminate theory. The interia and stiffness of the actuators are considered in the developed model. An optimal actuator location has been proved to be desirable since the piezoelectric actuators often have limitations of delivering large power oiutputs. Due to its effectiveness in seraching optimal design parameters and obtaining globally optimal solutions, the genetic algorithm has been applied to find optimal locations of piezoelectric actuators for the vibration control of a smart composite beam. In addition, the effects of population size, the crossover probability, and the mutation probability on the convergence of the genetic algorithm are investigated. Meanwhile, linear quadric regulator (LQR) and disturbance observer (DOB) are employed for the vibration suppression of the optimized adaptive composite beam (ACB). The experimental results show the robustness of the DOB, which can successfully suppress the vibrations of the cantilevered ACB according to the optimization results in an uncertain system.

Citation Download Citation

Su Yan and Mehrdad N. Ghasemi-Nejhad "Optimization and vibration suppression of adaptive composite panels using genetic algorithm and disturbance observer technique", Proc. SPIE 5049, Smart Structures and Materials 2003: Modeling, Signal Processing, and Control, (1 August 2003); https://doi.org/10.1117/12.482732

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