In　order　to　avoid　the　complex　adjustment　of　scaling　factor　and　quantization　factor　in　the　design　of　fuzzy　controller　and　the　shortcomings　that　the　fuzzy　control　rules　can　not　be　changed　once　identified,　a　fuzzy　controller　with　self-optimizing　rules　is　adopted.　Particle　swarm　optimization　(PSO)　algorithm　is　used　to　optimize　the　parameters　of　fuzzy　controller.　A　new　evaluation　function　including　the　system　adjusting　time,　rise　time,　over-shoot,　and　steady-state　error　is　defined.　A　group　of　parameters　of　the　fuzzy　controller　that　minimize　the　evaluation　function　is　calculated　rapidly　by　searching　in　the　given　controller　parameters　area.　Numerical　simulations　show　that　the　controller　can　easily　be　applied　to　the　first-order　and　second-order　system　with　time　delay,　no　overshoot,　and　its　performance　is　also　better　than　the　classic　PID　optimized　by　PSO.　©　2010　IEEE.