Search Results

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.