To solve the problem of Linear Quadratic Regulator (LQR) in aeroengine multivariable control

a modified LQR method based on a kind of fuzzy-neural networks was presented.First

we chose some representative operation points in the engine flight envelope

and designed the LQR controller for each operating point separately.Then

Adaptive-Network-based Fuzzy Inference System (ANFIS) was utilized to synthesize each linear controller to make a nonlinear controller.The inputs of ANFIS are flight altitude and Mach number

and the output is a feedback matrix

which represents the design results.The design of other operation points in the engine flight envelope can be conveniently deduced by the inference system.The ANFIS was trained offline

so we concluded that the method could compensate the short comings of the LQR control.Simulation results were given for a specific turbofan.The design process was analyzed

and the results prove the validity of the method.