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.<>
Use of Hopfield neural networks in optimal guidance
IEEE Transactions on Aerospace and Electronic Systems ; 30 , 1 ; 287-293
1994-01-01
710668 byte
Article (Journal)
Electronic Resource
English
Use of Hopfield Neural Networks in Optimal Guidance
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