Modelling and Control Prototyping of Unmanned Helicopters
Jaime del Cerro, Antonio Barrientos, A. Martínez · InTech eBooks · 2009
The first part of this chapter describes a procedure for modeling and identification a small helicopter. Model has been derived from literature, but changes introduced in the original model have contributed to improve the stability of the model with no reduction of the precision. The proposed identification methodology based on evolutionary algorithms is a generic procedure, having a wide range of applications. The identified model allows performing realistic simulations, and the results have been validated. The model has been used for designing real controllers on a real helicopter by using a fast prototyping method detailed in section 4. The model has confirmed a robust behavior when changes in the flight conditions happen. It does work for hover and both frontal and lateral non-aggressive flight. The accuracy and convenience of a parametric model depends largely on the quality of its parameters, and the identification process often requires good or deep knowledge of the model and the modeled phenomena. The proposed identification algorithm does away with the complexity of model tuning: it only requires good-quality flight data within the planned simulation envelope. The genetic algorithm has been capable of finding adequate values for the model's 28 parameters, values that are coherent with their physical meaning, and that yields an accurate model. It is not the objective of this chapter to study what the best control technique is. The aim is to demonstrate that the proposed model is good enough to perform simulations valid for control designing and implementation using an automatic coding tool. Future work will focus on the following three objectives: