Infinite-horizon optimal control based on continuous-time continuous-state Hopfield neural networks
An optimal control method based on continuous-time continuous-state Hopfield neural network (CTCSHNN) is proposed for time-varying multivariable systems. The equivalence is built theoretically between receding-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 infinite-horizon optimization control is realized for multivariable time-varying systems. As an example, a second order time-varying system is simulated. Simulation results show the effectiveness and feasibility of the proposed method.
infinite-horizon optimization control hopfield neural network time-varying system