Title :
Use of Hopfield neural networks in optimal guidance
Author :
Steck, James E. ; Balakrishnan, Sivasubramanya N.
Author_Institution :
Dept. of Mech. Eng., Wichita State Univ., KS
fDate :
1/1/1994 12:00:00 AM
Abstract :
A Hopfield neural network architecture is developed to solve the optimal control problem for homing missile guidance. A linear quadratic optimal control problem is formulated in the form of an efficient parallel computing device known as a Hopfield neural network. Convergence of the Hopfield network is analyzed from a theoretical perspective, showing that the network, as a dynamical system approaches a unique fixed point which is the solution to the optimal control problem at any instant during the missile pursuit. Several target-intercept scenarios are provided to demonstrate the use of the recurrent feedback neural net formulation
Keywords :
Hopfield neural nets; aerospace control; missiles; optimal control; Hopfield neural networks; architecture; dynamical system; homing missile guidance; linear quadratic optimal control; optimal guidance; parallel computing; recurrent feedback neural net; target-intercept scenarios; Acceleration; Accelerometers; Artificial neural networks; Biological neural networks; Computer architecture; Hopfield neural networks; Missiles; Modems; Navigation; Neurofeedback; Optimal control; Parallel processing;
Journal_Title :
Aerospace and Electronic Systems, IEEE Transactions on