Journal of Guidance Control and Dynamics 

About: Journal of Guidance Control and Dynamics is an academic journal published by American Institute of Aeronautics and Astronautics. The journal publishes majorly in the area(s): Spacecraft & Optimal control. It has an ISSN identifier of 0731-5090. Over the lifetime, 7980 publications have been published receiving 270361 citations.

An eigensystem realization algorithm for modal parameter identification and model reduction

Abstract: A method, called the Eigensystem Realization Algorithm (ERA), is developed for modal parameter identification and model reduction of dynamic systems from test data. A new approach is introduced in conjunction with the singular value decomposition technique to derive the basic formulation of minimum order realization which is an extended version of the Ho-Kalman algorithm. The basic formulation is then transformed into modal space for modal parameter identification. Two accuracy indicators are developed to quantitatively identify the system modes and noise modes. For illustration of the algorithm, examples are shown using simulation data and experimental data for a rectangular grid structure.

Distributed Piezoelectric-Polymer Active Vibration Control of a Cantilever Beam

Abstract: An active vibration damper for a cantilever beam was designed using a distributed-parameter actuator and distributed-parameter control theory. The distributed-parameter actuator was a piezoelectric polymer, poly (vinylidene fluoride). Lyapunov's second method for distributed-parameter systems was used to design a control algorithm for the damper. If the angular velocity of the tip of the beam is known, all modes of the beam can be controlled simultaneously. Preliminary testing of the damper was performed on the first mode of the cantilever beam. A linear constant-gain controller and a nonlinear constant-amplitude controller were compared. The baseline loss factor of the first mode was 0.003 for large-amplitude vibrations (± 2 cm tip displacement) decreasing to 0.001 for small vibrations (±0.5 mm tip displacement). The constant-gain controller provided more than a factor of two increase in the modal damping with a feedback voltage limit of 200 V rms. With the same voltage limit, the constant-amplitude controller achieved the same damping as the constant-gain controller for large vibrations, but increased the modal loss factor by more than an order of magnitude to at least 0.040 for small vibration levels.

Three-axis attitude determination from vector observations

Abstract: Two computationally efficient algorithms are presented for determining three-axis attitude from two or more vector observations. The first of these, the TRIAD algorithm, provides a deterministic (i.e., nonoptimal) solution for the attitude based on two vector observations. The second, the QUEST algorithm, is an optimal algorithm which determines the attitude that achieves the best weighted overlap of an arbitrary number of reference and observation vectors. Analytical expressions are given for the covariance matrices for the two algorithms using a fairly realistic model for the measurement errors. The mathematical relationship of the two algorithms and their relative merits are discussed and numerical examples are given. The advantage of computing the covariance matrix in the body frame rather than in the inertial frame (e.g., in terms of Euler angles) is emphasized. These results are valuable when a single-frame attitude must be computed frequently. They will also be useful to the mission analyst or spacecraft engineer for the evaluation of launch-window constraints or of attitude accuracies for different attitude sensor configurations.

Kalman Filtering for Spacecraft Attitude Estimation

Abstract: HIS report reviews the methods of Kalman filtering in attitude estimation and their development over the last two decades. This review is not intended to be complete but is limited to algorithms suitable for spacecraft equipped with three-axis gyros as well as attitude sensors. These are the systems to which we feel that Kalman filtering is most ap- plicable. The Kalman filter uses a dynamical model for the time development of the system and a model of the sensor measurements to obtain the most accurate estimate possible of the system state using a linear estimator based on present and past measurements. It is, thus, ideally suited to both ground-based and on-board attitude determination. However, the applicability of the Kalman filtering technique rests on the availability of an accurate dynamical model. The dynamic equations for the spacecraft attitude pose many difficulties in the filter modeling. In particular, the external torques and the distribution of momentum internally due to the use of rotating or rastering instruments lead to significant uncertainties in the modeling. For autonomous spacecraft the use of inertial reference units as a model replacement permits the circumvention of these problems. In this representation the angular velocity of the spacecraft is obtained from the gyro data. The kinematic equations are used to obtain the attitude state and this is augmented by means of additional state-vector components for the gyro biases. Thus, gyro data are not treated as observations and the gyro noise appears as state noise rather than as observation noise. It is theoretically possible that a spacecraft is three-axis stabilized with such rigidity that the time development of the system can be described accurately without gyro information, or that it is one-axis stabilized so that only a single gyro is needed to provide information on the time history of the system. The modification of the algorithms presented here in order to apply to those cases is slight. However, this is of little practical importance because a control system capable of such