Abstract
In this paper, Predictive Functional Control (PFC) is used for X-Y pedestal control for LEO satellite tracking. According to the nonlinear characteristics of the X-Y pedestal and pedestal model variation caused by its operating point change, the use of system identification algorithm, which is based on special types of orthonormal functions known as Laguerre functions, is presented. This algorithm is combined with PFC to obtain a novel adaptive control algorithm entitled Adaptive Predictive Functional Control (APFC). In this combination, Laguerre functions are utilized for system identification, while the PFC is the control law. An interesting feature of the proposed algorithm is its desirable performance against the interference effect of channel X and channel Y. The proposed APFC algorithm is compared with Proportional Integral Derivative (PID) controller using simulation results. The results confirm that the proposed controller improves the performance in terms of the pedestal model variations; that is, the controller is capable of adapting to the model changes desirably.
Highlights
Pedestals play a substantial role in satellite tracking, as they are important modules in satellite tracking stations
X-Y Pedestals are considered as a suitable solution for Low Earth Orbit (LEO) satellite tracking, especially in the tracking of the target near their zenith position where the well-known Elevation over Azimuth (El/Az) pedestals cannot track the target
In this paper, unstructured system identification based on Laguerre functions [24,25,26,27,28,29,30,31] is combined by predictive functional control to achieve an adaptive predictive functional control algorithm
Summary
Pedestals play a substantial role in satellite tracking, as they are important modules in satellite tracking stations. Since the system model is nonlinear and time-variant (as a result of the satellite motion being followed by the antenna motion), applying online system identification methods and adaptive control [23] are considered to be appropriate options in order to achieve a desirable performance. In this paper, unstructured system identification based on Laguerre functions [24,25,26,27,28,29,30,31] is combined by predictive functional control to achieve an adaptive predictive functional control algorithm In this line, PFC is the control law, while the Laguerre functions are utilized for system modeling. For detailed information about the elements of the matrices in (2), see Appendix A and [2,7]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
