Study of Two Instrumental Variable Methods for Closed-Loop Multivariable System Identification.

New control strategies are based on the model of the process and it is thus necessary to identify the systems to be controlled. It is also often necessary to identify them during closed-loop operation in order to maintain efficient operation and product quality. Some results of multivariable closed-loop identification carried out on a simulated 2 x 2 linear time-invariant system, using two new versions of instrumental variable methods called IV4D and IV4UP as the identification methods, are presented. In each case pseudorandom binary signals (PRBS), or dithers, are applied to the outputs of the feedback controllers. Algorithms IV4D and IV4UP are created in a four step environment where iterations are performed to obtain the best possible estimated model. For IV4D only the dither is used as part of the instrument. For IV4UP only the part of the input that comes from the dither is used for the instrument. This is obtained with the estimated model and with the description of the controllers using the closed-loop transfer function between the dither and the input to the process. The implementation is made to be run in MatLab and it uses several of the functions defined in its System Identification Toolbox (Ljung, 1991). Both instrumental variable (IV) algorithms perform very well identifying closed-loop multivariable systems under the influence of white noise and correlated noise disturbances. The two new instrumental variable methods are compared with the prediction error method, PEM, and with IV4, the regular instrumental variable open-loop algorithm, both of them are obtained from the MatLab System Identification Toolbox. IV4 does not perform well in closed-loop operation. From the simulated results, the performances of the new IV algorithms are the best but, PEM\u27s performance is very close. Finally, real plant data are analyzed with IV4D and its results are compared with the results of other identification methods, PEM and Dynamic Matrix Identification (DMI) (Cutler and Yocum, 1991). For this closed-loop real plant data PEM is the best that performs followed by IV4D, while DMI does not perform well

The 1981 NASA/ASEE Summer Faculty Fellowship Program: Research reports

Research reports related to spacecraft industry technological advances, requirements, and applications were considered. Some of the topic areas addressed were: (1) Fabrication, evaluation, and use of high performance composites and ceramics, (2) antenna designs, (3) electronics and microcomputer applications and mathematical modeling and programming techniques, (4) design, fabrication, and failure detection methods for structural materials, components, and total systems, and (5) chemical studies of bindary organic mixtures and polymer synthesis. Space environment parameters were also discussed

Publications of the Jet Propulsion Laboratory, July 1969 - June 1970

JPL bibliography of technical reports released from July 1969 through June 197

Computational intelligence approaches to robotics, automation, and control [Volume guest editors]

No abstract available

DEVELOPMENT OF SOLID TUNABLE OPTICS FOR ULTRA-MINIATURE IMAGING SYSTEMS

Ph.DDOCTOR OF PHILOSOPH

INDOOR-WIRELESS LOCATION TECHNIQUES AND ALGORITHMS UTILIZING UHF RFID AND BLE TECHNOLOGIES

The work presented herein explores the ability of Ultra High Frequency Radio Frequency (UHF RF) devices, specifically (Radio Frequency Identification) RFID passive tags and Bluetooth Low Energy (BLE) to be used as tools to locate items of interest inside a building. Localization Systems based on these technologies are commercially available, but have failed to be widely adopted due to significant drawbacks in the accuracy and reliability of state of the art systems. It is the goal of this work to address that issue by identifying and potentially improving upon localization algorithms. The work presented here breaks the process of localization into distance estimations and trilateration algorithms to use those estimations to determine a 2D location. Distance estimations are the largest error source in trilateration. Several methods are proposed to improve speed and accuracy of measurements using additional information from frequency variations and phase angle information. Adding information from the characteristic signature of multipath signals allowed for a significant reduction in distance estimation error for both BLE and RFID which was quantified using neural network optimization techniques. The resulting error reduction algorithm was generalizable to completely new environments with very different multipath behavior and was a significant contribution of this work. Another significant contribution of this work is the experimental comparison of trilateration algorithms, which tested new and existing methods of trilateration for accuracy in a controlled environment using the same data sets. Several new or improved methods of triangulation are presented as well as traditional methods from the literature in the analysis. The Antenna Pattern Method represents a new way of compensating for the antenna radiation pattern and its potential impact on signal strength, which is also an important contribution of this effort. The performance of each algorithm for multiple types of inputs are compared and the resulting error matrix allows a potential system designer to select the best option given the particular system constraints