Research On Integrated Modeling, Control And Optimization Of Turboshaft Engine/Rotor

With the performance improvement of new generation of helicopters, the demands of helicopter's fire control system, maneuver quality, survivability, agility and maneuverability become higher and higher, and the complexity and the coupling dynamic effects of helicopter's subsystems also increase. The traditional design methods of individual subsystems have been unable to meet the demand, and the only solution is the integrated design and control methods. The rotor is driven by a shaft projecting from main gear box which connects to the turboshaft engine's power turbine, and the rotor is not only the load of the turboshaft engine, but also the important component of generating the lift of the helicopter and controlling the flight velocity and attitude, so the turboshaft engine/rotor system has the important influence on the whole helicopter performance. In this dissertation, the integrated helicopter/engine simulation platform is built, and the control and optimization of the turboshaft engine/rotor are researched based on the platform.In the first Chapter, a general introduction of the helicopter integrated flight/engine control, the model predictive control and the optimization program is presented with a brief description. The helicopter/engine integrated simulation platform is built based on the Black-Hawk helicopter's experimental data in Chapter 2. In Chapter 3, the optimization library based on C++ is built with Unified Modeling Language (UML), which includes the Simplex algorithm to Linear Programming(LP), the Active Set algorithm to Quadratic Programming(QP) and the Sequential Quadratic Programming(SQP) to the general nonlinear optimization problem. In Chapter 4, the nonlinear model predictive controller based on SQP is designed, in which the neural network model is used to get the predictive model; the SQP optimization algorithm is used to optimize the fuel flow of the turboshaft engine online. Finally, the real-time problem of the controller is discussed in detail. In Chapter 5, the Filled Function Method(FFM) for the global optimization is researched, and a new FFM with one parameter is proposed. The nonlinear model predictive controller based on the new FFM is designed. In Chapter 6, the online optimization for turboshaft engines based on variable inlet guide vane with LP and SQP methods is studied. The difference on real-time problem between the LP and SQP for aero-engine performance seeking control is discussed, and it states that the SQP is better than LP in real-time aspect. In Chapter 7, the optimization for turboshaft engines based on variable rotor speed is researched. The last Chapter is the conclusion of this dissertation.