Aero-engine online optimization and multivariable control design method based on model predictive control

Abstract

An aero-engine online optimization and multivariable control design method based on model predictive control achieves the control and online optimization of multiple variables of an aero-engine undera constraint and according to requirements of thrust and speed. A control system consists of two parts. The first part is a prediction model acquisition layer. Based on the actual working state of each control cycle and the external environmental parameters of the aero-engine, an engine small deviation linear model near different steady-state points is continuously established, and model parameters are provided for a model predictive controller. The second part is a control law decision layer. A closed-loop structure is formed by the model predictive controller and an external output feedback.The model predictive controller, based on an engine model in the current state, a control command and relevant constraint limits, determines the output of the controller at the next moment by solvinga linear optimization problem. The external output feedback introduces the aero-engine actual output into the decision on future controlled quantity of the controller to compensate for the influenceof model mismatch and external disturbances.

Description

technical field [0001] The invention provides an aeroengine online optimization and multivariable control design method based on model prediction, which belongs to the technical field of aerospace propulsion system control and simulation. Background technique [0002] With the continuous advancement of aero-engine technology, the structure of modern aero-engines has become increasingly complex, and the scope of work has also continued to expand. The requirements for aero-engine control systems have also become higher and higher. The traditional single-input / single-output control system has been difficult to meet the control requirements. . Therefore, selecting more control variables to realize the multi-variable control system that controls multiple parameters of the engine has become an important means to improve the performance of the engine control system. As a model-based multi-variable control algorithm, model predictive control can not only realize the effective contr...

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Problems solved by technology

Although model predictive control has many excellent characteristics, it also has the disadvantage that it is difficult to balance the performance of the controller with the real-time performance of the control system.

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