Performance optimization of a magnetohydrodynamic generator at the scramjet inlet

The performance optimization problem of a magnetohydrodynamic (MHD) generator-at the inlet of a scramjet engine is studied. The generator performance is characterized in terms of both the net energy extracted from the flow and the flow characteristics through the channel before it enters the combustion chamber of the scramjet engine. The analysis assumes a steady-state one-dimensional flow in which the position along the channel is treated as an independent coordinate. The performance optimization problem can then be handled by optimal control theory, in which position now plays the role of time as in a standard control problem. In this work, an optimal neural-networks-based controller design technique developed in our previous work is used. The technique is well suited for this application, because the MHD system is highly nonlinear. Furthermore, the technique is data-based, in that experimental data obtained from the system can be used to design the optimal controller without requiring an explicit model of the system.