System identification of parameterized state-space model of a small scale UAV helicopter

The success of model-based ight control law design for autonomous helicopter is largely dependent on the availability of reliable model of the system. Considering the complexity of the helicopter dynamics, and inherent di�culty involves with physical measurement of the system parameters, the grey modeling approach which involves the development of parameterized model from �rst principles and estimation of these parameters using system identi�cation (sysID) technique has been proposed in the literatures. Prediction Error Modeling (PEM) algorithm has been identi�ed as an e�ective system identi�cation technique. However, application of this method to complex system like helicopter is not a trivial exercise due to inherent coupling in the system states and the challenges associated with parameter initialization in PEM algorithm. In this work, an e�ective procedure in application of PEM algorithm available in MATLAB toolbox is presented for small scale helicopter using real-time ight data. The approach was able to yield satisfactory model suitable for model-based ight control design