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Conventional linear digital control fails to provide precise positioning of a control object under the influence of static friction, Coulomb friction, and backlash. This paper presents an adaptive pulse width control (PWC) scheme for a precise point-to-point positioning system. This scheme is developed based on the relationship between the displacement of a control object due to a single pulse input and the pulse width. The coefficient appearing in this relationship is estimated by a parameter adaptation algorithm. Sufficient conditions for asymptotic stability of this adaptive scheme are developed using Popov hyperstability theorem. This adaptive PWC is tested on a laboratory positioning table and is shown to be effective.

We describe a set of methods for locating and quantifying natural gas leaks using a small unmanned aerial system equipped with a path-integrated methane sensor. The algorithms are developed as part of a system to enable the continuous monitoring of methane, supported by a series of over 200 methane release trials covering 51 release location and flow rate combinations. The system was found throughout the trials to reliably distinguish between cases with and without a methane release down to 2 standard cubic feet per hour (0.011 g/s). Among several methods evaluated for horizontal localization, the location corresponding to the maximum path-integrated methane reading performed best with a mean absolute error of 1.2 m if the results from several flights are spatially averaged. Additionally, a method of rotating the data around the estimated leak location according to the wind is developed, with the leak magnitude calculated from the average crosswind integrated flux in the region near the source location. The system is initially applied at the well pad scale (100–1000 m2 area). Validation of these methods is presented including tests with unknown leak locations. Sources of error, including GPS uncertainty, meteorological variables, data averaging, and flight pattern coverage, are discussed. The techniques described here are important for surveys of small facilities where the scales for dispersion-based approaches are not readily applicable.

Natural gas is an abundant resource across the United States, of which methane (CH4) is the main component. About 2% of extracted CH4 is lost through leaks. The Remote Methane Leak Detector (RMLD)-Unmanned Aerial Vehicle (UAV) system was developed to investigate natural gas fugitive leaks in this study. The system is composed of three major technologies: miniaturized RMLD (mini-RMLD) based on Backscatter Tunable Diode Laser Absorption Spectroscopy (TDLAS), an autonomous quadrotor UAV and simplified quantification and localization algorithms. With a miniaturized, downward-facing RMLD on a small UAV, the system measures the column-integrated CH4 mixing ratio and can semi-autonomously monitor CH4 leakage from sites associated with natural gas production, providing an advanced capability in detecting leaks at hard-to-access sites compared to traditional manual methods. Automated leak characterization algorithms combined with a wireless data link implement real-time leak quantification and reporting. This study placed particular emphasis on the RMLD-UAV system description and the quantification algorithm development based on a mass balance approach. Early data were gathered to test the prototype system and to evaluate the algorithm performance. The quantification algorithm derived in this study tended to underestimate the gas leak rates and yielded unreliable estimations in detecting leaks under 7 × 10 − 6 m3/s (~1 Standard Cubic Feet per Hour (SCFH)). Zero-leak cases can be ascertained via a skewness indicator, which is unique and promising. The influence of the systematic error was investigated by introducing simulated noises, of which Global Positioning System (GPS) noise presented the greatest impact on leak rate errors. The correlation between estimated leak rates and wind conditions were investigated, and steady winds with higher wind speeds were preferred to get better leak rate estimations, which was accurate to approximately 50% during several field trials. High precision coordinate information from the GPS, accurate wind measurements and preferred wind conditions, appropriate flight strategy and the relative steady survey height of the system are the crucial factors to optimize the leak rate estimations.

A 440 MHz wireless and passive surface acoustic wave (SAW) chemical sensor was developed for CO2 detection. The developed SAW gas sensor is composed of single phase unidirectional transducers (SPUDTs), three shorted grating reflectors, and CO2-sensitive polymer film on 41° YX LiNbO3 substrate. Coupling of modes (COM) modeling was used to find optimal design parameters. Using the extracted design parameters, the SAW device was fabricated. Teflon AF 2400 was used as the sensitive film because it provides high CO2 solubility, permeability and selectivity. In wireless device testing using a network analyzer, four sharp reflection peaks with high signal-to-noise (S/N) ratio, small signal attenuation, and few spurious peaks were observed in the time domain. The time positions of the reflection peaks were well matched with the predicted values from the simulation. Infusion of CO2 into the chamber induced large phase shifts of the reflection peaks. Good linearity and repeatability were observed for a CO2 concentration of 0–450 ppm. The obtained sensitivity was 1.98° ppm−1. Temperature and humidity effects were also investigated during the sensitivity evaluation process.