Sungwook Yang

On-orbit estimation of dynamic properties for STSAT3

Reliable and efficient attitude control requires the accurate dynamic properties. On orbit, the mass and inertia values are to be changed by some activities such as the propellant use, the solar panel deployment, etc. To obtain the accurate mass properties, the estimation should be performed. For the initial on-orbit estimation of the mass properties, the gyro-based attitude data is applied for the batch method. The gyro-based attitude data includes the noise, which affects the estimation accuracy. We suggested several filtering methods including the extended Kalman filtering algorithm to obtain the well-conditioned attitude data. Applying the proper filters, we can obtain the reliable estimation result of the mass properties of STSAT3.

Path Tracking Controller Design and Simulation for Korean Lunar Lander Demonstrator

In Korea, Lunar exploration program has been prepared with the aim of launching in the 2020s. As a part of it, a lunar lander demonstrator was developed, which was the model for verifying the system such as structure, propulsion, and control system, before launching into the deep space. This paper deals with the path tracking performance of the lunar lander demonstrator with respect to the thruster controller based on Pulse Width Pulse Frequency Modulator (PWPFM) and Pulse Width Modulator (PWM). First, we derived equations of motion, considering the allocation of the thrusters, and designed the path tracking controller based on Euler angle. The signal generated from the path tracking controller is continuous, so PWPFM and PWM modulator are adopted for generating ON/OFF signal. Finally, MATLAB simulation is performed for evaluating the path tracking ability. We compared the path tracking performances of PWPFM and PWM based thrust controller, using performance measures such as the total impulse and the position error with respect to the desired path.

Rigid Body Inertia Estimation Using Extended Kalman and Savitzky-Golay Filters

Inertia properties of rigid body such as ground, aerial, and space vehicles may be changed by several occasions, and this variation of the properties influences the control accuracy of the rigid body. For this reason, accurate inertia properties need to be obtained for precise control. An estimation process is required for both noisy gyro measurements and the time derivative of the gyro measurements. In this paper, an estimation method is proposed for having reliable estimates of inertia properties. First, the Euler equations of motion are reformulated to obtain a regressor matrix. Next, the extended Kalman filter is adopted to reduce the noise effects in gyro angular velocity measurements. Last, the inertia properties are estimated using linear least squares. To achieve reliable and accurate angular accelerations, a Savitzky-Golay filter based on an even number sampled data is utilized. Numerical examples are presented to demonstrate the performance of the proposed algorithm for the case of a space vehicle. The numerical simulation results show that the proposed algorithm provides accurate inertia property estimates in the presence of noisy measurements.