Nonlinear model predictive control method for high-speed helicopter power system based on integrated onboard model

Abstract

To mitigate severe fluctuations in engine power turbine speed caused by changes in coaxial rotors, propellers, and aero-surfaces during the mode transition in coaxial high-speed helicopter (CHH), this paper presents a nonlinear model predictive control (NMPC) method for the CHH power system based on an integrated onboard model. Firstly, a digital simulation framework is deployed, incorporating a CHH onboard model based on a T-S fuzzy model and an onboard composite model of variable speed turboshaft engine based on a stacked Long Short-Term Memory-State Variable Model (LSTM-SVM). Subsequently, a nonlinear model predictive control method is devised for the CHH power system. By integrating flight prediction data from the integrated onboard model, an optimized objective function is formulated, taking into account both speed control objectives and the dynamic response characteristics of the turboshaft engine's output shaft. Through rolling optimization and feedback correction methods, real-time optimized control parameters for the turboshaft engine are obtained, ensuring rapid responsiveness in the engine control system. Simulation results demonstrate that the developed integrated onboard model accurately represents the variations in performance parameters during high-speed helicopter flight. Additionally, the nonlinear model predictive control law effectively tracks the variable speed reference commands of the power turbine, maintaining a maximum power turbine speed fluctuation of under 0.46%, thereby significantly enhancing both the engine's response and control quality while preserving computational real-time performance.