Artificial　intelligence　methods　are　widely　applied　in　advanced　control　practices　such　as　fuzzy　calculation-based　intelligent　control　method,　neural　network-based　predictive　control　method,　etc.　Control　performances　are　expected　to　be　improved　such　as:　faster　control　speed,　smaller　steady-state　error,　and　less　repeated　manual　tuning　workloads　in　harmful　environments　for　engineers.　Main　works　are　as　follows:　Firstly,　change　ratio-based　fuzzy　adjusted　PID　(FA-PID)　method　is　improved.　The　adjusted　parameters　of　FA-PID　are　the　multiplication　result　of　the　change　ratio　at　the　current　control　cycle　and　the　control　parameters　at　the　time　of　previous　adjustment　cycle.　Secondly,　prediction　of　back　propagation　neural　networks-based　fuzzy-PID　(BPNN-F-PID)　and　prediction　of　back　propagation　neural　networks-based　FA-PID　(BPNN-FA-PID)　are　improved,　in　which　the　adjusted　control　parameters　are　calculated　according　to　the　predicted　output　of　control　system.　Thirdly,　comparative　simulations　of　all　the　above　methods　are　implemented,　a　series　of　better　effects　are　found.　Effects　are　as　follows:　The　improved　controllers　have　better　performance　such　as　faster　control　speed,　better　ability　of　anti-interference,　restrained　overshoot　and　smaller　steady-state　error.