Adaptive Nonlinear Controller Synthesis and Flight Test Evaluation On an Unmanned Helicopter

Numerous simulation studies have recently revealed the potential benefits of a neural network-based approach to direct adaptive control in the design of flight control systems. Foremost among the potential benefits is greatly reduced dependence on high-fidelity modeling of system dynamics. However, the methodology has only recently been proven practical by demonstration in an actual flight system. This paper begins with an overview of the design of a nonlinear adaptive control system for flight test on an unmanned helicopter test bed. Next, the design of an outer loop trajectory tracking controller as well as simulation results are presented. The paper concludes with the presentation of preliminary flight test results of the rate command system that document the actual performance of the control system in flight.