Use of MRAN Adaptive Neural Network for Control of a Flexible System

摘要

Flexible systems are used in many industrial designs to reduce weight and power consumption. Undesirable frequencies are common and may interfere with control systems. In many aerospace flexible dynamic systems the interfering frequency shifts due to the nonlinearities and coupling within the system. The conventional approach in aerospace is to generate a large number of individual notch filters to protect the control systems. This requires a significant verification and validation activity, as well as a large storage capacity for the filter coefficients. In this paper an MRAN neural network system is used to control a multivariable linearized space structure. Growth and pruning ideas are reviewed and applied to the space structure model. Proportional integral (PI) and lead-lag update rules are compared to a typical update rule.