Implementation of adaptive nonlinear control for flight test on an unmanned helicopter

Abstract

Numerous simulation studies have 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 modeling of system dynamics. However, the methodology has yet to be proven practical by demonstration in an actual flight system. The paper presents an overview of the design of a practical control system for flight test on an unmanned helicopter testbed. Included is a description of the control system hardware and software, as well as the real-time, hardware-in-the-loop simulation facility assembled to prepare for flight testing. Hardware-in-the-loop test results are presented, and flight test plans for the forth quarter of 1998 are discussed.