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Nonlinear control of aircraft engines using a generalized minimum variance based approach

Model based design has become one of the enabling technologies for aircraft engine control systems. One of the mostly received model based design methods is nonlinear control. In the field of nonlinear control of aircraft engines, three well-known approaches are linear parameter varying control, nonlinear model predictive control and optimization methods. These approaches require an analytical mathematical model with a high level of accuracy. For aircraft engines, however, it is extremely difficult, if not possible, to obtain a high accuracy analytical model over the flight envelope. Therefore, these design approaches still need further investigation to address these issues. In this paper, a generalized minimum variance based approach is proposed. One of the features of the proposed method is that it does not require an analytical mathematical model for design; another advantage is that the inverse operation of nonlinear functions is not needed for the computation of optimal signals, hence suitable for real time control. This is attracting as the aircraft engine EEC only has very limited computing resource. Simulation results support the statements and validate the effectiveness of the proposed method.