Atmospheric Experiment

A pendulum experiment was constructed to investigate whether damping enhancing mechanisms can be added to the attachment point of the wire boom to reduce the duration of the wire boom oscillations. Grover et al.[87] presented a damping washer at the attachment point to introduce extra damping. A basic pendulum was created with a30 cm long wire attached to a10 gmass. The nominal position of the

mass is defined where there is no offset angle relative to the gravity force acting on the mass. A camera was placed at a fixed location to observe the movement of the mass when released at a known distance from its nominal position.

This experiment was repeated a number of times to investigate the repeatability of the results and the effect of adding damping enhancing mechanisms. Two damping enhancing mechanisms were investigated. The first was the addition of insulation around the wire. The insulation that was investigated was in the form of a thin tube of Kynar material. The second was the addition of a round spring that surrounded the wire at the attachment point. Both the enhancers were limited to15 mmin length.

The results of the experiment are shown in Figure 4.18. The horizontal pixel distance of the tip mass relative to its nominal position was extracted from the camera footage. A data point was extracted at the maximum positive horizontal distance from the nominal position at certain number of pendulum periods following release. This resulted in the relative comparison of energy release after each period of the pendulum movement. Figure 4.18a shows these points as a combined image and Figure 4.18b presents the distance of the experiments conducted. The experiment was conducted once for the case without any damping enhancer and twice for the insulation and spring cases respectively.

As one would expect, the results show that the damping enhancers were effective and did increase the damping of the out-plane distance of the wire boom. The added insulation only increased the damping slightly when compared to the standard case. The thickness of the insulation can be increased, which should increase the effectiveness of this method. The spring did seem to be much more effective than the insulation. It is clear that this simple and basic experiment can be used to investigate the relative effectiveness of different damping enhancers and wires that are to be used in the final deployment mechanism.

(a) Camera output of mass position

0 20 40 60 100 150 200 250 300 350 Numbercofcpendulumcperiods X − Offsetc(pixels) NocEnhancer Insulation1 Insulation2 Spring1 Spring2

(b) Mass position with damping enhancers

Figure 4.18 – Atmospheric pendulum experiment

4.5.3 Vacuum Experiment

The results obtained in the atmospheric pendulum experiment cannot be used to determine the damping ratio of the wire boom system due to the influence of atmospheric drag. Similar tests need to be completed in a vacuum to experimentally derive the damping ratio for a particular wire boom. This experiment will have to be operated remotely within the vacuum chamber.

The entire pendulum experiment has to be placed in a vacuum chamber, therefore the vacuum chamber will need to be large enough to contain the entire experiment. The pendulum mass can be released from its offset position after the chamber reaches an acceptable vacuum level. The pendulum experiment must consist of a pendulum system with a remote release system for the tip mass and a fixed camera to inspect the tip mass after release. Adding a small light to the tip mass or some other form of lighting within the chamber to make the tip mass clear is suggested. A mechanical lever or electromagnet can be used to release the tip mass remotely, but with the requirement that the same initial conditions are ensured with each experiment reload. A diagram depicting such a conceptual experimental setup is shown in Figure 4.19. Similar experiments were conducted by Morbhat[88] and Huang et al.[84] with success. This experiment must be repeated for the specific deployment mechanism, damping enhancer, wire and tip mass to be used in the final wire boom system.

Figure 4.19 – Proposed experimental setup for vacuum pendulum damping measurement

4.6

Conclusion

A deployment mechanism for a spinning sail CubeSat was investigated and active and passive deployment strategies have been proposed. The active mechanism has an actuator for slowly releasing the wire booms. The passive deployment makes use of the centrifugal force of the spinning system to pull out the wire booms. A deployment demonstrator that could perform both types of deployment methods was built. A pulse deployment controller and model estimation methods to determine the progress of deployment were introduced for the passive deployment case. The outcome of the active and passive deployment methods were investigated theoretically by means of simulation. The deployment mechanism was used to investigate the deployment methods. The practical results show good correspondence with the theoretical models. It is clear from the tests that the practical deployment of the spinning structures is feasible. Although the active deployment mechanism produced a more controlled deployed system, it is suggested that the deployment strategy should include either an active and passive method or multiple active methods to reduce the risk of deployment failure.

Further experiments with regard to the wire dynamics were performed. These experiments confirmed that tilting or speed changes induce offset angles in the wire boom. A few damping enhancers were identified for the wire boom oscillations, and were tested with a pendulum to confirm their relative effectiveness. A similar vacuum pendulum test would be able to produce parameters to increase the accuracy of wire dynamic models.

Chapter 5

ADCS Design

5.1

Introduction

The solar sail satellite is dependent on an accurate attitude determination and control system (ADCS) to perform optimally. The ADCS is responsible for carrying out the required attitude manoeuvres to gain and direct the thrust from the sun. Attitude control and knowledge is also required to point payloads at a target, absorb disturbance torques present in the space environment and maintain a nominal orientation that ensures sufficient power generation of the solar panels.

The basic components of an ADCS are illustrated in Figure 5.1. The satellite’s current mode of operation will require a particular attitude mode, which will determine the required attitude outcome, whether to maintain a stable spin around a single axis or point a payload to a target. A specific attitude mode will require a suitable attitude control loop implementation. The attitude control loop starts with the control generator, which produces particular attitude or angular rate references. An attitude controller makes use of the knowledge of the satellite’s current orientation to determine the required control signals to achieve the reference. The control signals from the attitude controller are converted to a physical torque that acts on the satellite body by means of an actuator, for example a reaction wheel.

A state estimator or state observer estimates the current attitude of the satellite. The state estimator uses measurements from sensors and mathematical models to estimate the current orientation of the satellite. These sensors measure the vector direction from the satellite to particular external bodies, like the sun, earth or stars. These vector measurements are compared to modelled vectors mostly determined by the satellite’s current position in its orbit and time.

Each attitude control mode uses different combinations of these components to be able to achieve the current attitude requirement. This chapter introduces a number of these components required for the design of an ADCS of a spinning solar sail. Various state observers are presented to estimate the current attitude and angular rate of the satellite from on-board sensors. The Rate Kalman filter, TRIAD algorithm, Full State Extended Kalman Filter (EKF) and Gyro-based EKF are introduced and supply estimator options for all possible satellite modes. Safe-mode attitude controllers, which aim to get the satellite in a controlled and known attitude are presented. The deployment of the sail and other deployables create disturbances that influence the satellite’s operations, therefore controllers that absorb these disturbances are suggested. Accurate attitude pointing controllers for tracking the sun or pointing a payload are discussed. Chemical/electric thrusters, reaction wheels or control moment gyro (CMG) actuator implementations of the tri-spin satellite can generate the required torques. All the controllers and estimators are aimed at the tri-spin solar sail configuration presented in §3.2.1.3, but can be applied to other spinning and stabilised solar sailing satellites.

Control Generator Attitude Controller Attitude Estimator Orbit Model Actuator Sensors Satellite Dynamics Disturbance Noise B-dot Rate Controller Quaternion feedback Magnetorquers Reaction Wheels Magnetometer Sun Sensor Star Tracker RKF TRIAD EKF

Figure 5.1 – Generic attitude determination and control system

5.2

Attitude Determination

The attitude is determined by applying a mathematical model and measurements from the attitude sensors. Different control modes require different estimators. The satellite needs the body rates of the satellite during the detumbling, safe-mode and deployment phases. A magnetic rate Kalman filter (RKF) is robust in the sense that it determines the body rates of the satellite independent of the current orientation and position of the satellite in its orbit. The TRIAD algorithm is an analytical method to calculate the attitude of the satellite from two independent measured vectors. An extended Kalman filter (EKF) uses a combination of sensors like the fine sun sensor and nadir sensor to determine the current attitude of the satellite. In applications where the satellite is not in an earth-centred orbit, a star-tracker is a necessity. Angular body rate sensors and a star tracker can create an accurate and fast attitude estimation method. This attitude information is required to perform precise pointing of the sailing satellite.

Many of the estimators presented here were introduced by Steyn[98] and further described by Auret[70]. Only the information necessary to implement the filters is presented. The steps and definitions below are required to implement the filters in simulation and flight software. The model-based estimators (RKF, EKF and Gyro-based EKF) will require a few iterations of these steps before accurate estimates of the states will be available. Refer to the sources mentioned above for more detail regarding the inner workings and derivation of the filters.