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A Study of Parameter Identification Techniques for Complex Aircraft Systems Models
Technical Paper
2016-01-2045
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
Model based design is a standard practice within the aerospace industry. However, the accuracies of these models are only as good as the parameters used to define them and as a result a great deal of effort is spent on model tuning and parameter identification. This process can be very challenging and with the growing complexity and size of these models, manual tuning is often ineffective. Many methods for automated parameter tuning exist. However, for aircraft systems this often leads to large parameter search problems since frequency based identification and direct gradient search schemes are generally not suitable. Furthermore, the cost of experimentation often limits one to sparse data sets which adds an additional layer of difficulty. As a result, these search problems can be highly sensitive to the definition of the model fitness function, the choice of algorithm, and the criteria for convergence. In this paper, the challenge of setting up an effective parameter identification scheme is explored in the context of an aircraft Power Thermal Management System (PTMS) model. Through simulation case studies, the performance of a gradient approximation and an evolutionary search method are evaluated using four different fitness functions and a variety of solver options. The gradient approximation method was observed to be best suited for problems in which knowledge of the system could be used to improve the fitness function and to help remove local minima. It performed the best with a min-max normalized fitness function which weighs error terms according to measurement type. The evolutionary search was observed to be more robust to local minima and less sensitive to the choice of fitness function. In both cases, the choice of solver options had a significant impact and a model to model test of the parameter identification method is recommended for tuning these settings.
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Citation
Deppen, T., Raczkowski, B., Kim, B., Walters, E. et al., "A Study of Parameter Identification Techniques for Complex Aircraft Systems Models," SAE Technical Paper 2016-01-2045, 2016, https://doi.org/10.4271/2016-01-2045.Also In
References
- Roberts , R. A. , and Decker , D. D. Control Architecture Study Focused on Energy Savings of an Aircraft Thermal Management System ASME Journal of Dynamic Systems, Measurements, and Control 136 4 041003 041003-11 2014 10.1115/1.4026412
- Chaparro , B. M. , Thuillier , S. , Menezes , L. F. , Manach , P. Y. et al. Material Parameters Identification: Gradient-Based, Genetic and Hybrid Optimization Algorithms Computational Materials Science 44 2 339 346 2008 10.1016/j.commatsci.2008.03.028
- Byrd , R. H. , Hribar , M. E. , and Nocedal , J. An Interior Point Algorithm for Large-Scale Nonlinear Programming SIAM Journal on Optimization 9 4 877 900 1999 10.1137/S1052623497325107
- Powell , M. J. D. The Convergence of Variable Metric Methods For Nonlinearly Constrained Optimization Calculations Nonlinear Programming 3 27 63 Academic Press 1978 10.1016/B978-0-12-468660-1.50007-4
- Alonge , F. , D'Ippolito , F. , Ferrante , G. and Raimondi , F. M. Parameter Identification of Induction Motor Model Using Genetic Algorithms IEEE Proceedings on Control Theory and Applications 145 6 587 593 1998 10.1049/ip-cta:19982408
- Zagrouba , M. , Sellami , A. , Bouaïcha , M. and Ksouri , M. Identification of PV Solar Cells and Modules Parameters Using The Genetic Algorithms: Application to Maximum Power Extraction Solar Energy 84 5 860 866 2010 10.1016/j.solener.2010.02.012
- Tavakolpour , A. R. , Mat Darus , I. Z. , Tokhi , O. and Mailah , M. Genetic Algorithm-Based Identification of Transfer Function Parameters for a Rectangular Flexible Plate System Engineering Applications of Artificial Intelligence 23 8 1388 1397 2010 10.1016/j.engappai.2010.01.005
- Bodie , M. , Russell , G. , McCarthy , K. , Lucas , E. et al. Thermal Analysis of an Integrated Aircraft Model 48th AIAA Aerospace Sciences Meeting Including the New Horizons Forum and Aerospace Exposition, Aerospace Sciences Meetings 2010 10.2514/6.2010-288
- Bodie , M. and Wolff , M. Robust Optimization of an Aircraft Power Thermal Management System 46th AIAA/ASME/SAE/ASEE Joint Propulsion Conference & Exhibit 2010 10.2514/6.2010-7086
- Jain , Y. K. and Bhandare , S. K. Min Max Normalization Based Data Perturbation Method for Privacy Protection International Journal of computer & Communication Technology 2 8 45 50 2011
- http://www.mathworks.com/help/optim/ug/fmincon.html
- Deb , K. and Agrawal R. B. Simulated binary crossover for continuous search space Complex Systems 9 115 148 1995
- Amrhein , M. , O'Connell , T. C. and Wells , J. R. An Integrated Design Process for Optimized High-Performance Electrical Machines IEEE International Electric Machines & Drives Conference 847 854 2013 10.1109/IEMDC.2013.6556197