Herein, the design optimization of multi-objective controllers for the lateral–directional motion using proportional–integral–derivative controllers for a twin-engine, propeller-driven airplane is presented. The design optimization has been accomplished using the genetic algorithm and the main goal was to enhance the handling quality of the aircraft. The proportional–integral–derivative controllers have been designed such that not only the stability of the lateral–directional motion was satisfied but also the optimum result in longitudinal trim condition was achieved through genetic algorithm. Using genetic algorithm optimization, the handling quality was improved and placed in level 1 from level 2 for the proposed aircraft. A comprehensive sensitivity analysis to different velocities, altitudes and centre of mass positions is presented. Also, the performance of the genetic algorithm has been compared to the case where the particle swarm optimization tool is implemented. In this work, the aerodynamic coefficients as well as the stability and control derivatives were predicted using analytical and semi-empirical methods validated for this type of aircraft.
This study is intended to introduce an enhanced semi-empirical method for estimation of longitudinal and lateraldirectional stability and control derivatives in the preliminary design phase of light airplanes. Specialised for light, single or twin propeller-driven airplanes, available state-of-the-art analytical procedures and design data compendia are combined and modified in a unique compatible method, and automated in NAMAYEH software. In the present study, modified procedures and the software structure are presented. Afterwards, the proposed method is applied to a four-place, low wing, single-engine, propeller-driven general aviation airplane. In order to validate the proposed method, the estimated aerodynamic characteristics are compared with the wind tunnel test data as well as DATCOM and VLM-based method estimations. The results indicate that the proposed method is able to predict the aerodynamic characteristics in an acceptable range of accuracy from zero-lift to stall conditions in all configurations.
In considering aircraft design, it is very important to effectively size the tail configuration for stability and control. Multidisciplinary design optimization (MDO) focuses on the use of numerical optimization in the design of systems with multiple subsystems or disciplines of consideration. However, MDO uses deterministic calculations, and does not consider the uncertainties that arise from the employed analyses, including errors due to linearization and simplification. For problems with inadequate input data, the possibility-based design optimization (PBDO) scheme can be implemented in its stead to achieve reliable designs using membership functions for epistemic uncertainties. A multidisciplinary, possibilistic approach is presented to define the sizing of the empennage configuration of a twin-engine propeller-driven aircraft by changing shape parameters while satisfying the design requirements given the tailless aircraft configuration, the flight conditions, and various uncertainties. The corresponding disciplines are aerodynamics, stability and control, propulsion and weight and balance. Herein, different design requirements are considered including longitudinal/lateral/directional trim and stability characteristics, manufacturing and controllability criteria, handling qualities, operational requirements, airworthiness and survivability. The resulting aerodynamic characteristics and flight dynamic stability outcomes show that the optimized tail configuration for the proposed aircraft fully complied with airworthiness requirements and predefined constraints while considering several uncertainties due to the use of early-stage statistical estimations. The proposed approach can be used to enhance the preliminary design of multi-engine propeller-driven light aircraft where only low-fidelity, statistical estimations are available. The resulting output is not only an optimized aircraft configuration, but one where the stability of the design has been ensured. In this work, the aerodynamic characteristics have been determined using a validated semi-empirical program called MAPLA, developed for light aircraft designs and development in the preliminary design phase. Furthermore, the optimization framework consists of a deterministic optimizer that runs sequentially with a possibility assessment algorithm.
In this paper, an analytical model is proposed for evaluating electromagnetic performances of permanent magnet vernier machines (PMVMs) under healthy and faulty conditions. The proposed model employs flexible magnetic equivalent circuit (MEC) method, which its accuracy can be selected by tunable parameters. The model is capable of considering the influence of saturation effect, skewed slots, slot leakage fluxes, and various winding arrangements for the machines with desired properties. First, the proposed model is used to predict the no-load performance of machine at healthy condition. Then, the machine loading behaviors under healthy and demagnetization fault conditions are analyzed by the MEC model. Moreover, the results of the proposed model are compared and validated with those of 2D finite element method (FEM) and 3D-FEM. Eventually, a specific pattern is extracted from the stator current spectrum to detect the demagnetization fault.
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