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

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