Practical aspects of precision membrane antenna shape control

A theoretical elasticity model of an inflatable membrane reflector is being developed, which predicts how the structure responds to perturbations at its boundary. The objective in the process of model development is to use interconnected cells to spatially discretize the membrane structure. Each cell would consist of three basic components-a spring, mass, and damper-while forming a symmetric cell configuration. Such cells will allow a multi-input, multi-output (MIMO) linear model formation where either displacements and/or forces would be considered as inputs and/or disturbances. Feedback error learning method is used for local state estimation and local parameter identification of the membrane. In this method a learning algorithm is proposed that uses the output of a feedback controller as the error for training an adaptive feedforward neural network model. In other words, feedback error learning is control strategy, which incorporates a neural network in a feedforward path, and allows this artificial system to learn the inverse dynamics of the controlled plant in real-time. A scanning laser velocimeter is used for measuring the local displacements and local transfer functions (LTF) of the membrane. The feedback on the membrane shape is coupled with a mathematical model of boundary perturbation effects for control efforts