Adaptive Predictive Functional Control of X-Y Pedestal for LEO Satellite Tracking Using Laguerre Functions

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.

Keywords

• adaptive predictive functional control (APFC)
• Laguerre functions
• LEO satellite tracking
• unstructured system identification
• X-Y pedestal