MODELING AND STATISTICAL CONTROL OF A GIMBALED LASER TARGET SYSTEM

Abstract

The space-based solar power system is an alternative to the ground-based solar power system because of its round-the-clock availability. For the space-based solar power transmission, the accurate pointing of a laser from space to ground poses a challenging control task. A gimbaled laser target system, which is used for pointing laser to a target, is a test bench for such a transmission system. The objective of this research is to determine the optimal controller for the gimbaled laser target system in terms of pointing error and error variation. In order to achieve the objective, we modeled the gimbaled laser target system, simulated the model with the controllers, and tested them on the test bench. In this thesis, we developed a mathematical model of a two-axis gimbaled laser target system. The model consists of a pitch-yaw gimbal for the dynamic laser motion, brushless dc motors for actuating the gimbal, and an image-based position sensor. We used a Proportional-Integral-Derivative (PID) controller as the basis for the performance comparison since it is the most commonly used control method in the industry. Then we compared the PID controller with two statistical control methods - Linear Quadratic Gaussian (LQG), and Minimal Cost Variance (MCV) optimal controllers. We evaluated the pointing performance of the controllers by measuring the mean and the standard deviation of the pointing error. The simulation results indicated that the statistical controllers perform better than the PID controller under Gaussian disturbances. Between the statistical controllers, the LQG method had the smaller pointing error, while the MCV method had the smaller standard deviation of the pointing error. We then implemented the PID, LQG, and MCV controllers in an off-the-shelf dSPACE digital signal processing controller board, and tested the controllers on the test bench in a real time environment. The experimental results showed that the LQG method decreased the mean pointing error by 46.28% compared to the PID method. The LQG method reduced the standard deviation of pointing error by 47.85% compared to the PID method. The MCV method reduced the standard deviation of the pointing error by 53.09% compared to the LQG method. Both the simulation and experimental results showed that the MCV controller improved the pointing error variation performance over the LQG controller significantly, while slightly degrading the pointing error performance of the gimbaled laser target system. Experimental results indicate that the statistical controllers will provide a design parameter either to improve the mean pointing error or the standard deviation of the pointing error for the gimbaled laser target system. Subsequently, we believe that the statistical controllers will improve the space-based solar power transmission efficiency.