NASA Scientific and Technical Aerospace Reports

esearch. An adjunct area of research yielded modified linear quadratic Gaussian (LQG) control design techniques that also
can be applied to nonadaptive control. For the Modified LQG (MLQG) controller, the proposed designs remove the
assumption that the Kalman filter as the observer and the controller gain matrix design are necessarily based on the same
model as the best system model. The filter and controller gain matrices are both determined by models possibly other than the
system model. In order to achieve optimal performance, the interrelationship of the system model to the filter and controller
design models is established by minimizing a position correlation (mean square error on output) measure. Enhanced
robustness is realized by considering the performance over the range of values of specified parameter(s) of the system model.
DTIC
Adaptive Control; Kalman Filters; Models
20040073697 Florida Agricultural and Mechanical Univ., Tallahassee, FL
Automated Modern Control Design
Collins, Emmanuel G.; Oct. 21, 2003; 3 pp.; In English
Contract(s)/Grant(s): DAAD19-01-1-0720
Report No.(s): AD-A422597; ARO-41420.1-CI-H; No Copyright; Avail: CASI; A01, Hardcopy
The aim of this research is to demonstrate that fuzzy logic may be used to harness human expertise to automatically tune
modern control systems, which can lead to higher performing control systems and savings in the time devoted by the control
engineer. Designing controllers for which selected system (input and output) variances are constrained have practical
applications to a variety of problems, including control design for flexible structures. This research has demonstrated that a
fuzzy algorithm developed by the investigators allows the design of reduced- order, H2 optimal controllers that satisfy bounds
on selected system variances. This is the first time that an algorithm has been developed and demonstrated for weight selection
in the design of reduced-order controllers. In addition, this research developed a fuzzy algorithm for choosing weights in
single-input, single-output H loop shaping control design with multiple time-domain and frequency-domain objectives. As a
theoretical extension of the fuzzy weight selection algorithms, this research also developed a fuzzy algorithm for solving
inexplicit and undetermined nonlinear systems of the form F(x)=0, where F: R(super n) (right arrow) R(super m). An inexplicit
system is one for which there is no analytical expression for the function F(x). An undetermined nonlinear system is one for
which m < n. These results have wide applicability since zero-finding problems are prevalent in engineering and science.
The report briefly summarizes some of the most important results obtained in this research: H2 Optimal Reduced Order
Control Design Using a Fuzzy Logic Methodology with Bounds on System Variances; Facilitating SISO Design of
Multiobjective H Loop Shaping Control Systems; and Solution of Inexplicit Systems of Nonlinear Algebraic Equations by
Fuzzy Logic. The details of this research can be found in the publications listed at the end of the report.
DTIC
Automatic Control; Fuzzy Systems; Man Machine Systems; Nonlinear Systems
20040073803 Purdue Univ., West Lafayette, IN
Analysis of Statistical Performance Measures
Zoltowski, Michael D.; May 12, 2004; 13 pp.; In English; Original contains color illustrations
Contract(s)/Grant(s): N00014-03-01-0077
Report No.(s): AD-A422819; PURDUE-TR-EE-04-7; No Copyright; Avail: CASI; A03, Hardcopy
When only a limited number of snapshots is available for estimating the spatial correlation matrix, a low- rank solution
of the MVDR equations, obtained via a small number of iterations of Conjugate Gradients (CG), can yield a higher SINR than
the full-rank MVDR beamformer. A primary issue addressed in this effort is whether the unity gain constraint in the look
direction should be enforced a-priori via the use of a blocking matrix, constituting Steering Dependent Conjugate Gradients
(SD-CG), or effected a- posteriori through simple scaling of the beamforming vector, constituting Steering Independent
Conjugate Gradients (SI-CG). A major contribution was that the two methods yield exactly the same low-rank beamformer.
This is an important result since the construction, and application to the data, of a blocking matrix for each "look"
direction is computationally burdensome. A simplified expression for the power estimate obtained with the SI-CG beamformer
was also developed. Extensive simulations were conducted to verify the efficacy of the theory. While it was known that the
optimal number of steps of SI-CG varies with look direction, simulations presented here reveal that the optimal number of
principal eigenvectors for the PCI beamformer varies substantially with look direction.
DTIC
Beamforming; Sonar
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