Simple Learning-Based Robust Nonlinear Control of an Electric Pump for Liquid-Propellant Rocket Engines

Abstract

This paper presents a robust nonlinear control strategy for an electric pump for liquid-propellant rocket engines. In order to compensate for model uncertainties and disturbances, a gradient-descent-based simple learning control strategy is employed that minimizes the cost function defined on the error dynamics of the nonlinear system. Detailed stability analysis for the nonlinear system is provided. Computer simulation results are included to demonstrate the effectiveness of the nonlinear control method using an electric pump model consisting of a brushless permanent-magnet direct current (DC) motor and a centrifugal pump. In particular, it is shown that by employing the developed nonlinear controller, the mass flow rate can be successfully kept at a certain level, can be changed instantly from one level to another (immediate decrease or increase), or can be changed linearly/nonlinearly, gradually, and continually for a certain period.