Linear quadratic optimal control with a modified difference Hopfield neural network
用改进的差分式Hopfield网络实现线性二次型最优控制

A linear difference Hopfield neural network which has the function of iterative learning is proposed to overcome the local minimum problem of its energy function.Theoretical analysis shows that the linear Hopfield neural network is stable,and the stable state makes its energy function reach its unique minimum.On the basis of the relation between the stability of the linear difference Hopfield network and its energy function's convergence,the linear Hopfield network is applied to solve linear quadratic optimization control problems for multivariable time-varying systems.The theoretical design method of linear Hopfield neural network shows that its stable outputs are the desired optimal control inputs.The simulation results are in accord with theoretical analysis.