Transient Performance Simulation of Aircraft Engine Integrated with Fuel and Control Systems

A new method for the simulation of gas turbine fuel systems based on an inter-component volume method has been developed. It is able to simulate the performance of each of the hydraulic components of a fuel system using physics-based models, which potentially offers more accurate results compared with those using transfer functions. A transient performance simulation system has been set up for gas turbine engines based on an inter-component volume (ICV) method. A proportional-integral (PI) control strategy is used for the simulation of engine controller. An integrated engine and its control and hydraulic fuel systems has been set up to investigate their coupling effect during engine transient processes. The developed simulation system has been applied to a model aero engine. The results show that the delay of the engine transient response due to the inclusion of the fuel system model is noticeable although relatively small. The developed method is generic and can be applied to any other gas turbines and their control and fuel systems

Online Game with Time-Varying Coupled Inequality Constraints

In this paper, online game is studied, where at each time, a group of players aim at selfishly minimizing their own time-varying cost function simultaneously subject to time-varying coupled constraints and local feasible set constraints. Only local cost functions and local constraints are available to individual players, who can share limited information with their neighbors through a fixed and connected graph. In addition, players have no prior knowledge of future cost functions and future local constraint functions. In this setting, a novel decentralized online learning algorithm is devised based on mirror descent and a primal-dual strategy. The proposed algorithm can achieve sublinearly bounded regrets and constraint violation by appropriately choosing decaying stepsizes. Furthermore, it is shown that the generated sequence of play by the designed algorithm can converge to the variational GNE of a strongly monotone game, to which the online game converges. Additionally, a payoff-based case, i.e., in a bandit feedback setting, is also considered and a new payoff-based learning policy is devised to generate sublinear regrets and constraint violation. Finally, the obtained theoretical results are corroborated by numerical simulations.Comment: arXiv admin note: text overlap with arXiv:2105.0620