An　optimal　control　method　based　on　continuous　Hopfield　neural　network　(CHNN)　is　proposed　for　multivariable　time-varying　systems.　The　equivalence　between　linear　quadratic　(LQ)　performance　index　in　moving-time　horizon　and　energy　function　of　CHNN　is　built　theoretically,　and　the　CHNN　is　constructed　to　solve　LQ　optimization　control　problems.　Moreover,　the　receding　optimization　strategy　is　adopted　to　form　closed-loop　control　structure　that　includes　CHNN.　Therefore,　the　dynamic　optimization　control　for　multivariable　time-varying　systems　is　realized　in　infinite-time　horizon.　Simulation　results　show　the　effectiveness　of　proposed　method.