摘要
模糊控制对于解决模型不确定性问题具有较好的优势。对于航空发动机这样复杂的系统,其数学模型具有较大的不确定性,经典的PID算法难以对其实现良好控制。因此,运用模糊控制理论就具有较好的实践意义。该文将模糊控制与自适应控制理论相结合,运用模糊推理方法,实现了对PID参数的在线最佳调整。最后,通过数字仿真,对比了经典PID控制和运用模糊自适应控制的PID,证明了其在航空发动机控制中应用的可能性。
Due to its simplicity, utility and easy application, PID controller is used largely in classical automation systems. However, the performance of the controller can not satisfy complicated nonlinear systems such as aircraft engines. This problem can be solved on the basis of the fuzzy self - learning control theory. The integrated flight/propulsion control system of a new fighter and its new trubofan engine are studied in this paper. Fuzzy control theory has a lot of predominance in some questions which can not figure out there models exactly. Two control methods of fuzzy control and self - learning control were combined in this paper which were used to revise the parameter of PID. Finally, the method was tested by the simulation. The simulation results indicate that the designed integrated controller has good performances.
出处
《计算机仿真》
CSCD
2006年第3期54-57,共4页
Computer Simulation
关键词
模糊自适应
航空发动机
模型
Fuzzy self - learning
Aero - engine
Model
