Recent developments in microelectromechanical systems (MEMS) have lead to a variety of microsensors and actuators that have great potential for guidance and control of aircraft and spacecraft. Such devices can deliver high-bandwidth performance with low power consumption, and their small size and weight permit the use of numerous sensors and/or actuators in applications where conventional sensor/actuator technology limits the number of measurement channels and actuator degrees of freedom. For these emerging technologies to realize competitive performance levels, innovative methods are required for device calibration and closed-loop control. The necessity of such methods arise from the fact that fabrication irregularities can produce a wide range of dynamic responses among any batch of supposedly identical devices due to the microscopic scale of key electro-mechanical components. The sensitivity and variability of sensor and actuator dynamics can be compensated by precise calibration of individual devices based on detailed modeling and parameter identification from input/output data, and by control loops built into the micro device. Broader Impact:This research focuses on the development of multivariable system identification and control strategies for improving the performance of MEMS vibratory angular rate sensors. The intellectual merit of this research derives from the study of problems stimulated by the following needs: 1) The first major research topic develops algorithms for achieving optimum device sensitivity. The highest signal-to-noise ratio is achieved when two dynamic modes of the sensor are rendered degenerate. Robust test methods and algorithms have been developed that vastly improve the SNR associated with the angular rate estimate via real-time tuning of the sensor dynamics. Furthermore, on-line algorithms continuously probe the sensor dynamics during operation in order to maintain the tuned condition; 2) The second major research topic develops a process for minimizing the rate uncertainty at designated integration times via the shaping of closed-loop noise spectra. In this case, additional freedom in the control filters is exploited for shaping the Allan variance of the rate estimate in a desired manner. This research program is conducted in the PIs Microsensor Laboratory on sensor prototypes loaned to the PI from NASAs Jet Propulsion Laboratory. The research contributions have significant broader impacts well beyond graduate education. The algorithms and methods devised under this program have changed the way the PIs collaborators at JPL and elsewhere model, test and control their sensor prototypes. In the undergraduate engineering curriculum at UCLA, a series of design courses expose students to this rapidly evolving sensor technology with projects that include the design and construction of a stabilized sensor platform for the UCLA DARPA Grand Challenge Team using commercial GyroChip vibratory gyros donated by BEI Technologies.
