Nonlinear adaptive flight control with genetic algorithm design optimization

This paper examines the use of a nonlinear adaptive control law for multi-a xis control of a high-performance aircraft with stabilator, aileron and rud der failures. The control law is based on a backstepping design approach wi th fixed parameter optimization done using a stochastic genetic algorithm. The control law is demonstrated on a six-degree-of-freedom simulation with nonlinear aerodynamic and engine models, actuator models with saturation, a nd turbulence. There are substantial differences between the control law de sign and simulation models, which are used to demonstrate some robustness a spects of this control law. To deal with actuator saturation, the Lyapunov function is modified so that the growth of integrated error and the rate of change of parameter growth are both reduced when the surface commands are growing at a rate that will likely saturate the actuators. Published in 199 9 by John Wiley & Sons, Ltd. This article is a US Government work and is in the public domain in the United States.