System identification and control of a 3D truss structure using PLID and LQG

This thesis deals with the experimental application of a system identification tech nique called pseudo-linear identification (PLID). PLID is a discrete-time, multi-input, multi-output (MEMO), state space, simultaneous parameter estimator and one step ahead state predictor of linear time invariant systems. No measurements are assumed perfect under PLED; that is the inputs and outputs are allowed to have zero mean white gaussian (ZMWG) additive noise. Furthermore, the states are also assumed to have additive ZMWG noise. Like most system identification techniques, PLED requires the system to be completely controllable and observable under the given actuator and sensor suite. The only firm assumption made on model structure is that the transfer function be strictly proper; that is, the frequency response is bounded and tends towards zero as frequency is in creased to infinity. Pole and zero locations are not confined; indeed, unstable systems can be identified, and furthermore, they can be controlled because PLED provides simultaneous one step ahead state predictions. Developed by Hopkins et. al. in 1988 [1], this method has seen little application (due in part to its youth); however, it is shown in the following pages to be a powerful technique for performing state space system identification, as well as on-line model order reduction. The experiment involves applying PLED to a 3 -Dimensional (3-D) kinematic truss structure (referred to here forward as the testbed ) in a batch mode (off-line). Batch mode identification, by definition, implies that the testbed does not change appreciably between the time it was identified and the time it will be controlled. For most kinematic structures, this is true. PLED can be used for real-time (on-line) system identification. However, due to the complexity of typical structures (e.g., flexible mechanical systems), and the high bandwidth of control (hundreds of hertz), this is not possible with current personal computer (PC) based controllers. Ultimately, the state space model generated by PLED will be used to design a closed loop controller for the testbed that will increase its damping twenty fold, from approximately 0.25% zeta to 5% zeta. Due to time constraints, we will only show simulation results of the closed loop system

Experimental verification of a novel system ID technique called PLID using a flexible 3-D structure

Presented below is a summary of the results obtained to date on the verification of a novel state space model identification technique called PLID (Pseudo Linear IDentification), given in Hopkins et al.1 This technique has several unique features that include: (1) optimal joint parameter and state estimation (that gives rise to its nonlinearities); (2) provisions for sensor, actuator, and state noise; (3) and it converges almost surely to the true plant parameters provided that the plant is linear, completely controllable/observable, strictly proper, time invariant, and all noise sources are zero mean white gaussian (ZMWG). Experiments carried out on a flexible, modally dense 3-D truss structure standing 4 feet tall have shown PLID to be a robust technique capable of managing significant deviations from the assumptions made to prove strict optimality. Using the 3 actuators and 3 sensors attached to the structure, models varying in size from 24 to 64 states have been used to approximate this infinite dimensional testbed in the frequency range between 50 to 500 Hz. Sensor signals with RMS levels of approximately 2 volts have been predicted by PLID to within 0.01 volts RMS

Hybrid Multivariable Controller Architecture

We present a multivariable controller architecture that is a hybrid combination of a classically designed controller and an observer-based controller. The design process starts with a classical multivariable feedback controller, designed by any convenient method, such as sequential SISO loop closing. After designing the classical controller, an observer-based modern controller is designed to be stable in parallel combination with the classical controller. The hybrid configuration is realized by introducing an additional feedback path between the two feedback controllers, to subtract the effects of the classical controller from the observer-state estimate. All of the controller gains are re-tuned to improve a variety of performance measures. The additional feedback path does not increase the number of states in the controller but allows significantly higher gains to be used in the observer-based controller, resulting in better isolation from input disturbances. A six-input, nine-output lightweight space structure (LSS) provides a working example. The classical controller was implemented as six 40th-order SISO feedback controllers, at a sample rate of 20 kHz, closed in parallel around the six main mount struts, achieving very good isolation across the struts. A 240th-order observer-based modern controller, also at a 20 kHz sample rate, was designed to work with the classical closed loops and has been implemented in the hybrid configuration described. This non-square modern controller uses feedback signals from three non-collocated sensors, in addition to the six used by the classical SISO controllers, and improves isolation by about 5 dB in the most critical regions of the controller bandwidth

Multiplexed SNP Typing of Ancient DNA Clarifies the Origin of Andaman mtDNA Haplogroups amongst South Asian Tribal Populations

The issue of errors in genetic data sets is of growing concern, particularly in population genetics where whole genome mtDNA sequence data is coming under increased scrutiny. Multiplexed PCR reactions, combined with SNP typing, are currently under-exploited in this context, but have the potential to genotype whole populations rapidly and accurately, significantly reducing the amount of errors appearing in published data sets. To show the sensitivity of this technique for screening mtDNA genomic sequence data, 20 historic samples of the enigmatic Andaman Islanders and 12 modern samples from three Indian tribal populations (Chenchu, Lambadi and Lodha) were genotyped for 20 coding region sites after provisional haplogroup assignment with control region sequences. The genotype data from the historic samples significantly revise the topologies for the Andaman M31 and M32 mtDNA lineages by rectifying conflicts in published data sets. The new Indian data extend the distribution of the M31a lineage to South Asia, challenging previous interpretations of mtDNA phylogeography. This genetic connection between the ancestors of the Andamanese and South Asian tribal groups ∼30 kya has important implications for the debate concerning migration routes and settlement patterns of humans leaving Africa during the late Pleistocene, and indicates the need for more detailed genotyping strategies. The methodology serves as a low-cost, high-throughput model for the production and authentication of data from modern or ancient DNA, and demonstrates the value of museum collections as important records of human genetic diversity

ACCESS Pointing Control System

ACCESS (Actively-Corrected Coronograph for Exoplanet System Studies) was one of four medium-class exoplanet concepts selected for the NASA Astrophysics Strategic Mission Concept Study (ASMCS) program in 2008/2009. The ACCESS study evaluated four major coronograph concepts under a common space observatory. This paper describes the high precision pointing control system (PCS) baselined for this observatory