The structure and the characters of wind velocity control system of D-4 low velocity wind tunnel at home having been built in Beijing University of Aeronautics and Astronautics was introduced. Due to the difficulties of establishing mathematical model, the complicated nonlinear characters and the change of parameters, the wind velocity systems is not easy to control in classical PID algorithm. This problem can be solved on the basis of parameters self-tuning fuzzy-PID control algorithm combined with expert decision. The experiment proved, compared with classical PID control, the parameters self-tuning fuzzy-PID control method can decrease the overshoot, enhance the capacity of anti-dynamic disturbance, have certain robustness, resolve the contradictory between rapidity and small overshoot, and is suitable for application in low velocity wind control system.
Li Ke, Liu Wangkai, Wang Jun.Parameters self-tuning fuzzy-PID combined with expert control on wind velocity control system of wind tunnels at home[J] JOURNAL OF BEIJING UNIVERSITY OF AERONAUTICS AND A, 2007,V33(12): 1387-1390
������,��ϼ,������. �綴����ѹģ������ϵͳ[J]. ������ѧʵ�������, 1998,12(2):94- 96 Yin Diyi, Zhu Zhaoxia, Hui Zenghong. The pressure-speed fuzzy control system of wind tunnel at home[J] . Journal of Experiments in Fluid Mechnics, 1998, 12(2):94-96(in Chinese)
Zhao Zhenyu. Fuzzy gain sheduling of PID controllers[J].IEEE Transactions on Systems Man and Cybernetics.1993, 23(5):1392-1398
������. �Ƚ�PID����MATLAB����[M]. ����:���ӹ�ҵ������,2005: 94-98 Liu Jinkun. Advanced PID control and MATLAB simulation [M].Beijing: Electronics Industry Press,2005:94-98(in Chinese)
������. ģ��ϵͳ��ģ������[M]. ����:�廪��ѧ������.[J].2006: 206- 210 Wang Lixin. Course in fuzzy systems & control[M].Beijing: Tsinghua University Press.2006,:-
Silva C W. Fuzzy adapation and control of a class of dynamic systems[J].IEEE Inteligent Control, 1990, 1(5):304-309