Historically,　underwater　vehicles　and　unmanned　surface　vehicles　were　often　considered　as　independent　entities　in　terms　of　movement,　limiting　the　potential　for　utilizing　the　diverse　environments　to　acquire　multidimensional　information,　monitor　targets　comprehensively,　provide　assistance　in　rescue　and　disaster　relief,　and　manage　resources　effectively.　Therefore,　this　paper　introduces　an　approach　for　collaborative　control　of　surface　underwater　unmanned　vehicles　and　formulates　a　fuzzy　PID　controller　to　effectively　solve　the　difficulties　in　controlling　them.　Developing　the　fuzzy　control　rule　base　and　membership　function　requires　significant　experience　and　knowledge,　resulting　in　considerable　human　interference.　Therefore,　in　this　study,　the　fuzzy　PID　controller＇s　parameters　are　fine-tuned　through　the　particle　swarm　optimization　algorithm,　aiming　to　minimize　the　influence　of　human　factors　in　the　design　of　fuzzy　control.　Simulation　outcomes　illustrate　that　the　overshoot　of　a　fuzzy　PID　controller　optimized　through　PSO　algorithm　is　decreased　by　39.56%.　Moreover,　the　response　time　is　slightly　enhanced　even　in　the　presence　of　noise　interference　within　the　system.　©　2023　IEEE.