Decentralized neural controller design for space structural platforms

A decentralized neural control system is advocated for flexible multibody structures. The proposed neural controller is designed to achieve trajectory maneuvering of 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 robust and fault tolerant structural controller. The proposed decentralized control architecture which takes advantage of the geometric distribution of PZT sensors and actuators has provided a tremendous freedom from computational complexity. 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 controller regulates the dynamics of the nonlinear structure to follow a prespecified reference model 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.<
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