A optimal control method with Hopfield neural networks

An optimal control method based on continuous-time, continuous-state Hopfield neural network (CTCSHNN) is proposed for multivariable time-varying systems. The equivalence is built theoretically between moving-horizon linear quadratic (LQ) performance index and energy function of CTCSHNN, and the CTCSHNN is constructed to solve the above LQ optimization control problems. Moreover, the rolling optimization strategy is adopted to form closed-loop control structure that includes CTCSHNN. So, the dynamic optimization control for multivariable time-varying systems is realized in infinite-horizon. As an example, a second order time-varying system is simulated. Simulation results show the effectiveness of proposed method.