Adaptive Control of a Seeker-Guided 2D Missile with Unmodeled Aerodynamics

In this paper we apply extensions of retrospective cost adaptive control (RCAC) to a 2D missile model considered in prior papers as a benchmark test of adaptive control methods. The dynamics of the missile are highly nonlinear, and instantaneous linearizations are nonminimum phase due to nose sensing and tail actuation. The results that we present in this paper show that the RCAC controller provides results that are comparable to a highly tuned autopilot based on aerodynamic modeling, whereas the RCAC controller uses no knowledge of the missile’s aerodynamics. These results significantly improve the results obtained on the same problem using an earlier version of RCAC, presented at the 2010 GNC.