Evolutionary Optimization for Gain Tuning of Jet Engine Min-Max Fuel Controller

Abstract

AS turbine aero engines (GTEs) have played a significant role in the expansion of the flight capabilities of modern aircraft. For a GTE, stable and safe operation of the engine components must be ensured in order to operate at the operability and performance level for which it is designed. The thrust response is also of great importance for an aircraft, both in terms of the speed of response and accomplishment of the adequate thrust [1]. Hence, an appropriate control system has always been an essential part of the GTEs to provide both regulation and management. The main task of a GTE control system is to provide the required performance while maintaining safe and stable operation [2]. The safetyconsiderationsincludethe flowinstability,highheatloads,and high cyclic stresses. In other words, the GTE control requirements include amainfuel controlforsetting andholdingsteady-state thrust (steady-state control mode) and fuel acceleration and deceleration schedules to provide limit protection (physical limitation control mode) and rapid time response for gas turbine engine (transient control mode) [3]. AsurveyonGTEcontrolstrategiesshowsthatvariousfuelcontrol methods have been used for GTE fuel control in the last two decades [4–16]. These studies show that the complexity of the engine control comes from the need to operate the engine as close as possible to its limits. In other words, the design of the control system for a gas turbine aero engine results in a series of single input single output controllers. Many methods such as PID, LQ, LQG, and H1 are used as one of the single feedback control loops of the GTE control system. In this case, the design method is based on a selection approach between various control loops. This strategy is named “min-max selection strategy,” as the selection of the control loops is based on a min-max approach between transient control loops. Minmax approach is an industrial method for the design of the GTE fuel control system. However, in order to provide an improved engine performance as well as the engine protection against the physical limitations, one of the most common complexities of the min-max selection strategy is controller gain tuning. Taking the nonlinearity and switching nature of this control strategy into account, gradient-based optimization methods have weak performance for gain tuning. As a result, this problem requires a non gradient optimization technique on the basis of the evolutionary algorithms. In this paper, application of an evolutionary algorithm for optimization of the min-max fuel controller parameters is presented. For this purpose, the control requirements and constraints for a gas turbine aero engine are first explained. The min-max fuel control strategy is then described and an initial min-max fuel controller is designed. Subsequently, using the genetic algorithm (GA), the parameters of the initial min-max fuel controller is tuned so that the engine requirements and constraints are satisfied. In optimization process, the fitness function is defined to minimize the settling time andfuelconsumption,wheretheweightfactorsaresetwithrespectto the importance of each function. In addition, a computer simulation programisdevelopedtoinvestigatetheeffectivenessoftheapproach for a single-spool jet engine. The results of simulation are validated by experimental data in both steady-state and transient modes to support the simulation model. Finally, the results are provided to investigate the performance of the optimized controller and to evaluate the effectiveness of the approach.