Title :
Integrated flight/propulsion control system design via neural network
Author_Institution :
Dept. of Mech. Eng., Texas Univ., Arlington, TX, USA
Abstract :
Neural network design methodology is utilized to design an integrated airframe/engine control system for a modern, statically unstable, fighter aircraft in landing. The resulting neural controller structure consists of a feedback compensator and a feedforward filter formulated in the form of a three-layer feedforward network whose parameters are trained by a static backpropagation method. The number of parameters is chosen by an ad hoc procedure. The feedback compensator satisfies closed-loop stability, while the feedforward filter provides command shaping. Once training has been completed, and the parameters are fixed, overall system performance evaluation results are then presented
Keywords :
aerospace propulsion; aircraft; aircraft landing guidance; backpropagation; closed loop systems; compensation; control system synthesis; feedback; feedforward neural nets; filtering theory; stability; aircraft propulsion control; closed-loop stability; command shaping; feedback compensator; feedforward filter; fighter aircraft; flight control; landing control; neural controller structure; neural network; static backpropagation; system performance evaluation; three-layer feedforward network; Aerospace control; Aircraft propulsion; Backpropagation; Control systems; Design methodology; Engines; Filters; Military aircraft; Neural networks; Neurofeedback;
Conference_Titel :
Intelligent Control, 1993., Proceedings of the 1993 IEEE International Symposium on
Conference_Location :
Chicago, IL
Print_ISBN :
0-7803-1206-6
DOI :
10.1109/ISIC.1993.397647