A float-encoded genetic algorithm technique for integrated optimization of piezoelectric actuator and sensor placement and feedback gains

Abstract

This paper presents a novel float-encoded genetic algorithm and applies it to the
\noptimal control of flexible smart structures bonded with piezoelectric actuators and sensors.
\nA performance function is initially developed, based on the maximization of dissipation
\nenergy due to a control action. Then, according to this characteristic, a float-encoded genetic
\nalgorithm is presented which is capable of solving this optimization problem reliably and
\nefficiently. The optimization algorithm that is developed for the control of flexible systems
\nallows an integrated determination of actuator and sensor locations and feedback gains. The
\npaper demonstrates the suitability of the proposed technique through its application to three
\nstandard benchmark test functions and a collocated cantilever beam.