Development and Application of a Nonlinear Fin Mixer

This paper describes the development and application of a nonlinear fin mixer to control aerodynamic vehicles during demanding flight maneuvers. Maneuvers that may be experienced by a bank-to-turn homing missile utilizing a proportional navigation guidance scheme often drive fin actuators into acceleration, rate and/or position limitations For vehicles where each fin is used to control multiple degrees-of-freedom, these saturations can lead to vehicle instability. This paper explores these regions of instability and develops a nonlinear fin mixer which utilizes information on the actuator limitations to eliminate these instabilities in an optimal manner. The paper presents an implementation of the nonlinear fin mixer in terms of a set of parallel dynamic systems and relates this implementation to that of an Artificial Neural Network. The improvements due to the implementation of the nonlinear mixer are demonstrated using a nonlinear Monte Carlo simulation of a bank-to-turn homing missile pursuing a maneuvering ground target.