Substructural neural network controller

A substructure-based neural network is proposed for the active control of flexible structures. A flexible structure is divided into substructures. Subsequently, subcontrollers are designed for these substructures using the linear quadratic regulator (LQR) control method. These subcontrollers are assembled to obtain the central feedback controller for the whole structure. A radial basis function neural network is trained to emulate the behavior of this central controller designed from substructure levels. The training is based only on the outputs of sensors collocated with the actuators. Therefore, two distinct advantages of the proposed neural network controller are noted as its training being based on substructural LQR controller and collocated sensor data. The performance of the neural network controller is compared favorably with the complete structural LQR controller for various input forces acting on a large flexible structure.