Comparison of System Identification Techniques for the Dexterous Orbital Servicing System (DOSS)

The major contribution of system identification is the development of analytical models of a system. Many identification techniques can adequately describe the input and output map. One of the challenges of these techniques is to correctly infer from the measured data the characteristics of the individual, contributing components producing a more accurate system model. In this thesis linear, dynamic, multivariable state-space models for three joints of the Dexterous Orbital Servicing System (DOSS) are identified. DOSS is a representative space station manipulator at the NASA Langley Research Center. The dynamic models of the manipulator will first be estimated by applying nonparametric identification methods to determine each joint's response characteristics using various input excitations. These excitations include stun of sinusoids, pseudorandom binary sequences (PRBS), bipolar ramping pulses, and chirp input signals. Next, two different parametric system identification techniques will be applied to identify the best dynamical description of the joints. The manipulator is localized about a representative space station orbital replacement limit (ORU) task allowing the use of linear system identification methods. Comparisons, observations, and results of both parametric system identification techniques are discussed. The thesis concludes by proposing a model reference control system to aid in astronaut ground tests. This approach would allow the identified models to mimic on-orbit dynamic characteristics of the actual flight manipulator thus providing astronauts with realistic on-orbit responses to perform space station tasks in a ground-based environment.