NASA 1996 SBIR Phase I

PROJECT TITLE : Advanced High Performance Intelligent Aircraft Control Techniques

TECHNICAL ABSTRACT (LIMIT 200 WORDS)

This project proposes intelligent control for advanced flight control system design. Specifically, an integrated design framework utilizing neural networks, fuzzy logic, and nonlinear control will be developed to address specific issues, such as complexity, nonlinearity and uncertainty, arising in advanced aircraft control. The goal is to improve stability robustness and performance robustness for all flight conditions. In this project, the complexity and uncertainty issues are addressed via the distributed parallel processing, learning, and online reoptimization properties of neural networks. The nonlinear dynamics due to severe kinematic and inertial coupling as well as aerodynamics is naturally incorporated into the design framework. The knowledge base and decision making logic furnished by a fuzzy system leads to a human intelligence enhanced adaptive control scheme. At the end of Phase I, the effectiveness of the integrated intelligent control approach will be demonstrated on a fully integrated prototype module. It is anticipated that this project together with our on-going research on intelligent guidance laws will greatly enhance the status of current aircraft guidance and control system design.

The resulting design software toolkit in this project can find applications to a whole spectrum of flight control systems, including missile autopilot, aircraft flight control, spacecraft flight control, and unmanned aerial vehicle control.

Dr. Ching-Fang Lin
American GNC Corporation
9131 Mason Avenue
Chatsworth, CA 91311

American GNC Corporation
9131 Mason Avenue
Chatsworth, CA 91311