Structured Uncertainty Identification and Control Synthesis
This paper presents a systematic method to design robust controllers from experimental data so as
Control↗
Engineering topics
Scheid, R. E.
Publications and source records attributed to Scheid, R. E..
A Globally Optimal Minimax Solution for Spectral Overbounding and Factorization
An algorithm is introduced to find a minimum phase trqansfer function of specified order whose magnitude
Spectral↗
Automated on-orbit frequency domain identification for large space structures
Recent experiences in the field of flexible structure control in space have indicated a need for on-orbit system identification to support robust control redesign to avoid in-flight instabilities and maintain high spacecraft performance. This paper highlights an automated frequency domain system identification methodology recently developed to fulfill this need. The methodology is focused to support (1) the estimation of system quantities useful for robust control analysis and design; (2) experiment design tailored to performing system identification in a typically constrained on-orbit environment; and (3) the automation of operations to reduce 'human in the loop' requirements.
Bayard, D. S.↗
Combined control-structural optimization
An approach to combined control-structural optimization aimed at enhancing early design trade-offs is outlined and illustrated by numerical examples. The approach employs a homotopic strategy and is capable of generating families of designs that can be used in early trade studies. Analytical results are obtained for classes of structure/control objectives with LQG and LQR costs. For these, it is demonstrated that global optima can be computed for small values of the homotopy parameter.
Milman, M.↗
A linear programming approach to characterizing norm bounded uncertainty from experimental data
The linear programming spectral overbounding and factorization (LPSOF) algorithm, an algorithm for finding a minimum phase transfer function of specified order whose magnitude tightly overbounds a specified nonparametric function of frequency, is introduced. This method has direct application to transforming nonparametric uncertainty bounds (available from system identification experiments) into parametric representations required for modern robust control design software (i.e., a minimum-phase transfer function multiplied by a norm-bounded perturbation).
Scheid, R. E.↗
Frequency domain identification for robust large space structure control design
A methodology is demonstrated for frequency domain identification of large space structures which systematically transforms experimental raw data into a form required for synthesizing H(infinity) controllers using modern robust control design software (e.g., Matlab Toolboxes). A unique feature of this approach is that the additive uncertainty is characterized to a specified statistic confidence rather than with hard bounds. In this study, the difference in robust performance is minimal between the two levels of confidence. In general cases, the present methodology provides a tool for performance/confidence level tradeoff studies. For simplicity, the additive uncertainty on a frequency grid is considered and the interpolation error in between grid points is neglected.
Yam, Y.↗
Controlling Shape And Vibration Of Antennas
Report discusses application of advanced techniques to maintain large wrap-rib, offset-feed spaceborne antenna reflector in precise shape required for high performance. Idea is to use integrated system of sensors, control processor, and actuators to measure and suppress both vibrations and static or slowly varying (e.g., thermal) deviations from desired shape. Technology applicable to other elastically deformable structures.
Mettler, E.↗
A homotopy approach for combined control-structure optimization - Constructive analysis and numerical examples
This paper outlines the development of methods for the combined control-structure optimization of physical systems encountered in the technology of large space structures. The objectives of the approach taken in this paper is not to produce the 'best' optimized design, but rather to efficiently produce a family of design options so as to assist in early trade studies, typically before hard design constraints are imposed. The philosophy is that these are candidate designs to be passed on for further considerations, and their function is more to guide the development of the system design rather than to represent the ultimate product. A homotopy approach involving multi-objective functions is developed for this purpose. Analytical and numerical examples are also presented.
Scheid, R. E.↗
Integrated identification and robust control tuning for large space structures
System identification is studied for the explicit purpose of supporting modern H-infinity robust control design objectives. In the analysis, the true plant is not assumed to be in the identification model set. An integrated identification/robust control problem is posed in which the optimal solution guarantees the best robust performance relative to the system information contained in a given experimental data set. A numerical example demonstrating an approximate solution to the problem indicates the usefulness of the approach.
Yam, Y.↗
A Hankel singular value approach for identification of low level dynamics in flexible structures
The intensity of dynamics in a flexible structure is characterized by its Hankel singular values. Low level dynamics may be caused by generic properties of a structure or by its actuator and sensor configurations. In the latter case, it is shown that the dynamics can significantly be amplified by small perturbations of actuator and/or sensor configurations. In the presented examples, the variations of sensor configuration of 0.05 or less caused an increase of Hankel singular values of order 1000. This approach is useful for model reduction and model order determination in the presence of noise.
Gawronski, W.↗
Precision pointing compensation for DSN antennas with optical distance measuring sensors
The pointing control loops of Deep Space Network (DSN) antennas do not account for unmodeled deflections of the primary and secondary reflectors. As a result, structural distortions due to unpredictable environmental loads can result in uncompensated boresight shifts which degrade pointing accuracy. The design proposed here can provide real-time bias commands to the pointing control system to compensate for environmental effects on pointing performance. The bias commands can be computed in real time from optically measured deflections at a number of points on the primary and secondary reflectors. Computer simulations with a reduced-order finite-element model of a DSN antenna validate the concept and lead to a proposed design by which a ten-to-one reduction in pointing uncertainty can be achieved under nominal uncertainty conditions.
Scheid, R. E.↗
Autonomous frequency domain identification: Theory and experiment
The analysis, design, and on-orbit tuning of robust controllers require more information about the plant than simply a nominal estimate of the plant transfer function. Information is also required concerning the uncertainty in the nominal estimate, or more generally, the identification of a model set within which the true plant is known to lie. The identification methodology that was developed and experimentally demonstrated makes use of a simple but useful characterization of the model uncertainty based on the output error. This is a characterization of the additive uncertainty in the plant model, which has found considerable use in many robust control analysis and synthesis techniques. The identification process is initiated by a stochastic input u which is applied to the plant p giving rise to the output. Spectral estimation (h = P sub uy/P sub uu) is used as an estimate of p and the model order is estimated using the produce moment matrix (PMM) method. A parametric model unit direction vector p is then determined by curve fitting the spectral estimate to a rational transfer function. The additive uncertainty delta sub m = p - unit direction vector p is then estimated by the cross spectral estimate delta = P sub ue/P sub uu where e = y - unit direction vectory y is the output error, and unit direction vector y = unit direction vector pu is the computed output of the parametric model subjected to the actual input u. The experimental results demonstrate the curve fitting algorithm produces the reduced-order plant model which minimizes the additive uncertainty. The nominal transfer function estimate unit direction vector p and the estimate delta of the additive uncertainty delta sub m are subsequently available to be used for optimization of robust controller performance and stability.
Yam, Yeung↗
Frequency domain identification experiment on a large flexible structure
Recent experiences in the field of flexible structure control in space have indicated a need for on-orbit system identification to support robust control redesign to avoid in-flight instabilities and maintain high spacecraft performance. The authors highlight an automated frequency domain system identification methodology recently developed to fill this need. The methodology supports (1) the estimation of system quantities useful for robust control analysis and design, (2) experiment design tailored to performing system identification in a typically constrained on-orbit environment, and (3) the automation of operations to reduce human-in-the-loop requirements. A basic overview of the methodology is presented first, followed by an experimental verification of the approach performed on the JPL/AFAL testbed facility.
Bayard, D. S.↗
Methods for combined control-structure optimization
This paper outlines the development of methods for the combined control-structure optimization of physical systems encountered in the technology of large space structures. The objective of the approach taken in this paper is not to produce the 'best' optimized design, but rather to efficiently produce a family of design options so as to asist in early trade studies, typically before hard design constraints are imposed. The philosophy is that these are candidate designs to be passed on for further consideration, and their function is more to guide the development of the system design rather than to represent the ultimate product. A homotopy approach involving multi-objective functions is developed for this purpose, and a numerical example is presented.
Milman, M.↗
Flexible structure control laboratory development and technology demonstration
An experimental structure is described which was constructed to demonstrate and validate recent emerging technologies in the active control and identification of large flexible space structures. The configuration consists of a large, 20 foot diameter antenna-like flexible structure in the horizontal plane with a gimballed central hub, a flexible feed-boom assembly hanging from the hub, and 12 flexible ribs radiating outward. Fourteen electrodynamic force actuators mounted to the hub and to the individual ribs provide the means to excite the structure and exert control forces. Thirty permanently mounted sensors, including optical encoders and analog induction devices provide measurements of structural response at widely distributed points. An experimental remote optical sensor provides sixteen additional sensing channels. A computer samples the sensors, computes the control updates and sends commands to the actuators in real time, while simultaneously displaying selected outputs on a graphics terminal and saving them in memory. Several control experiments were conducted thus far and are documented. These include implementation of distributed parameter system control, model reference adaptive control, and static shape control. These experiments have demonstrated the successful implementation of state-of-the-art control approaches using actual hardware.
Vivian, H. C.↗