Title :
Suboptimal intelligent control: agile aircraft application
Author :
Mohler, Ronald R. ; Zakrzewski, Radoslaw R.
Author_Institution :
Dept. of Electr. & Comput. Eng., Oregon State Univ., Corvallis, OR, USA
fDate :
7/1/1996 12:00:00 AM
Abstract :
Near-optimal control of an aircraft using artificial neural networks is discussed with the optimal control problem solved off-line for numerous initial and final conditions using standard techniques. The obtained trajectories are then used to train a neural network controller. The concept is applied to minimum-time control and quadratic-performance optimal control of the longitudinal motion of a super-agile aircraft. Full nonlinear dynamics with control (magnitude and rate) constraints as well as state constraints are considered. Suboptimal feedback synthesized by a neural network is tested on a simulated rapid manoeuvre with extremely large changes in pitch angle and angle of attack
Keywords :
aircraft control; feedback; intelligent control; learning (artificial intelligence); motion control; neurocontrollers; suboptimal control; artificial neural networks; full nonlinear dynamics; longitudinal motion; minimum-time control; near-optimal control; neural network controller; quadratic-performance optimal control; simulated rapid manoeuvre; state constraints; suboptimal feedback; suboptimal intelligent control; super-agile aircraft; Aerospace control; Aircraft; Artificial neural networks; Intelligent control; Motion control; Network synthesis; Neural networks; Neurofeedback; Optimal control; Testing;
Journal_Title :
Control Systems Technology, IEEE Transactions on