Adaptive Control Of Aero-engine Systems With Input Saturation

Aero-engines system is complicated system with strongly nonlinear, time-varying and uncertain. With the development of aero-engines, aero-engine's control systems also get a constantly and fast evolving in recent year. And its requirements also become more and more accuracy. The paper focuses on the nonlinear saturation and multi-modal of aero-engines made the following series of meaningful attempt and research.First, in order to avoid use the differential of output, the model reference adaptive control (MAFC) base on input-output was adopted to design aero-engines controller, and then applied it to multivariable control systems of aero-engines control system. It clearly demonstrated that the controller could effectively avoid the each order derivative of output and gain a better control performance from the matlab simulation.Second, so as to solve the problem of aero-engines actuator's nonlinear saturation, a saturation compensator was proposed based on the controller in last chatter. The simulation results show that this measure can reduce the impact of the actuator's non-linear saturation, and can get an effective anti-saturation control performance.At last, the paper try to applied network model reference adaptive neural PSD control to aero-engines control system. And give a detailed analysis of the neural network PSD control theory, and design methods, and structure and function. The simulation results show that the neural network model reference PSD control could effective solve nonlinear saturation with a good adaptive performance. The paper could provide a theoretical research on the neural network intelligent control in aviation engine control system.