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.