Abstract

K. J. Austin and P. A. Jacobs

Provided the supersonic combustion ramjet (scramjet) engine can be developed into a practical propulsion system, ultimate success of sustained hypersonic flight will depend on configuring a robust and stable airframe-propulsion-control combination. Hypersonic air-breathing vehicles feature a high degree of engine integration with the airframe and are typically unstable. Maintenance of the vehicle attitude is therefore not just for vehicle stability but also for propulsive effectiveness. In turn, engine operation exhibits strong dependancies on flight conditions and vehicle attitude, thus there is limited scope for departure from optimum operating conditions. To design the flight controller for this inherently unstable vehicle we have applied a genetic algorithm, hence the trained monkeys metaphor in the title. Being a nondeterministic search method, there is no guarantee of generating a useful solution, yet given a little direction through evolutionary operators and a measure of fitness, plus enough time, it is able to solve hard problems. The controllers goal is to achieve stable longitudinal flight along a predefined trajectory. Towards this aim an arrangement of fuzzy logic rule bases are directed at manipulating the vehicle's angle of attack through the acutation of symmetric elevators. A preset structure for the rules is used whereby the design task is to configure the control surface through selection of the rule consequents. To direct the search for a controller design, the genetic algorithm uses simulated flight responses to a range of initial conditions, without linearization of the vehicle model and dynamics. This paper presents some results of this application.

Full Paper (Size: 415 KB)