Indirect self-tuning controller for a two degree of freedom tracker model
Amir Naderolasli
Abstract
Tracker systems have turned into an increasingly important issue in guidance systems and play a key role in navigational tracking. The aim of this study is to investigate a newly-developed self-tuning adaptive strategy for increasing the precision of stabilisation and control in two-Degree of Freedom (DOF) tracker systems. A new self-tuning adaptive strategy is proposed for boosting the stabilisation and regulation in two-DOF tracker systems. The strategy is, in effect, an identifier-based adaptive strategy operating on Recursive Least Squares (RLS), which results in a non-minimum phase model. Together, the self-tuning stabiliser and tracker act as inner and outer loops of the targeted control system in order to track a desired command for ensuring a consistent and desirable stabilisation. The performance of the proposed method is further examined by utilising simulation techniques to show its functional capability in coupling with possible external disturbances, parameters uncertainties and measurement noise effects.