Optimal tracking control in flexible pointing structures

A hybrid neural control system incorporated with feedforward and feedback dynamics is advocated for flexible multibody structures. The proposed neural controller is designed to achieve trajectory slewing of structural member as well as vibration suppression for precision pointing capability. The feedforward path corresponds to the steady-state output of the dynamics while the feedback path stabilizes the transient-state of the motion. 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 signals 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