A distributive neural control system is advocated for flexible multibody structures. The proposed neural controller is designed to achieve trajectory slewing of a structural member as well as vibration suppression for precision pointing capability. The motivation to support such an innovation is to pursue a real-time implementation of a robust and fault tolerant structural controller. The proposed control architecture which takes advantage of the geometric distribution of piezoceramic sensors and actuators has provided a tremendous freedom from computational complexity. In the spirit of model reference adaptive control, we utilize adaptive time-delay radial basis function networks as a building block to allow the neural network to function as an indirect closed-loop controller. The horizon-of-one predictive controllers cooperatively regulates the dynamics of the nonlinear structure to follow the prespecified reference models asymptotically. The proposed control strategy is validated in the experimental facility, called the Planar Articulating Controls Experiment which consists of a two-link flexible planar structure constrained to move over a granite table. This paper addresses the theoretical foundation of the architecture and demonstrates its applicability via a realistic structural test bed.
Gary G. Yen,
"Distributive vibration control in flexible multibody dynamics", Proc. SPIE 2492, Applications and Science of Artificial Neural Networks, (6 April 1995); doi: 10.1117/12.205152; https://doi.org/10.1117/12.205152