Accuracy in starphotometry

Starphotometry, the night-time counterpart of sunphotometry, has not yet achieved the commonly sought observational error level of 1 %: a spectral optical depth (OD) error level of 0.01. In order to address this issue, we investigate a large variety of systematic (absolute) uncertainty sources. The bright-star catalogue of extraterrestrial references is noted as a major source of errors with an attendant recommendation that its accuracy, particularly its spectral photometric variability, be significantly improved. The small field of view (FOV) employed in starphotometry ensures that it, unlike sun- or moonphotometry, is only weakly dependent on the intrinsic and artificial OD reduction induced by scattering into the FOV by optically thin clouds. A FOV of 45 arcsec (arcseconds) was found to be the best trade-off for minimizing such forward-scattering errors concurrently with flux loss through vignetting. The importance of monitoring the sky background and using interpolation techniques to avoid spikes and to compensate for measurement delay was underscored. A set of 20 channels was identified to mitigate contamination errors associated with stellar and terrestrial atmospheric gas absorptions, as well as aurora and airglow emissions. We also note that observations made with starphotometers similar to our High Arctic instrument should be made at high angular elevations (i.e. at air masses less than 5). We noted the significant effects of snow crystal deposition on the starphotometer optics, how pseudo OD increases associated with this type of contamination could be detected, and how proactive techniques could be employed to avoid their occurrence in the first place. If all of these recommendations are followed, one may aspire to achieve component errors that are well below 0.01: in the process, one may attain a total 0.01 OD target error.

Handling Measurement Delay in Iterative Real-Time Optimization Methods

This paper is concerned with the real-time optimization (RTO) of chemical plants, i.e., the optimization of the steady-state operating points during operation, based on inaccurate models. Specifically, modifier adaptation is employed to cope with the plant-model mismatch, which corrects the plant model and the constraint functions by bias and gradient correction terms that are computed from measured variables at the steady-states of the plant. This implies that the sampling time of the iterative RTO scheme is lower-bounded by the time to reach a new steady-state after the previously computed inputs were applied. If analytical process measurements (PAT technology) are used to obtain the steady-state responses, time delays occur due to the measurement delay of the PAT device and due to the transportation delay if the samples are transported to the instrument via pipes. This situation is quite common because the PAT devices can often only be installed at a certain distance from the measurement location. The presence of these time delays slows down the iterative real-time optimization, as the time from the application of a new set of inputs to receiving the steady-state information increases further. In this paper, a proactive perturbation scheme is proposed to efficiently utilize the idle time by intelligently scheduling the process inputs taking into account the time delays to obtain the steady-state process measurements. The performance of the proposed proactive perturbation scheme is demonstrated for two examples, the Williams–Otto reactor benchmark and a lithiation process. The simulation results show that the proposed proactive perturbation scheme can speed up the convergence to the true plant optimum significantly.

Centralized unidirectional consensus of connected automated vehicles convoys with sample delayed data control

This paper investigates the problem of centralized look ahead (CLA) consensus of connected automated vehicles convoys (CAVC) based on sample data control in the presence of measurement delay and engine’s lag. A double-integrator model is considered to describe the 1-D motion of automated vehicles (AVs). In the practical implementation, data loss and time delay are unavoidable in CAVC networks. Therefore, these issues are considered in modeling and control design of CAVCs and a CLA consensus is defined for all following AVs. By employing the Lyapunov-Krassovskii theorem, the sufficient conditions guaranteeing the zero tracking error of CAVCs in the presence of delay and data loss are derived. Then, by doing the error proliferation analysis in the frequency domain, sufficient conditions on control parameters assuring string stability are attained. Numerical studies are carried out to confirm the performance of the proposed consensus algorithm.

Pediatric clinical exercise testing system project

Commercially made exercise testing equipments are designed for testing adults with greater exercise capacity and relatively large minute ventilation compared to pediatric population. As the size of breaths becomes smaller and irregular, as in small children with pulmonary diseases, measurement delay errors may introduce errors to the final results in the exercise testing system. For this reason, a custom made Exercise System was built at the Exercise Laboratory Department at the Hospital for Sick Children. It incorporates a special algorithm that corrects measurement delay errors caused by small breaths. The algorithm calculates the lag time of the expired breath to reach the sampling port and re-aligns the gas concentration reading in time with the corresponding real-time recording of the breath. The Exercise System is currently used for clinical and research purposes. The system shows satisfactory results for adult testing; however, the system requires validation of increase in accuracy of results for testing in pediatrics, especially for ill patients with very small tidal volumes. The main objective of this study is to demonstrate that incorporating the lag time in the algorithm to process and calculate the oxygen (0₂) consumption improves the accuracy of the results in small children exercise testing. In addition, investigate the theory and operation of the Exercise System and document the system designs and testing results for publishing purposes.

Pediatric clinical exercise testing system project

Commercially made exercise testing equipments are designed for testing adults with greater exercise capacity and relatively large minute ventilation compared to pediatric population. As the size of breaths becomes smaller and irregular, as in small children with pulmonary diseases, measurement delay errors may introduce errors to the final results in the exercise testing system. For this reason, a custom made Exercise System was built at the Exercise Laboratory Department at the Hospital for Sick Children. It incorporates a special algorithm that corrects measurement delay errors caused by small breaths. The algorithm calculates the lag time of the expired breath to reach the sampling port and re-aligns the gas concentration reading in time with the corresponding real-time recording of the breath. The Exercise System is currently used for clinical and research purposes. The system shows satisfactory results for adult testing; however, the system requires validation of increase in accuracy of results for testing in pediatrics, especially for ill patients with very small tidal volumes. The main objective of this study is to demonstrate that incorporating the lag time in the algorithm to process and calculate the oxygen (0₂) consumption improves the accuracy of the results in small children exercise testing. In addition, investigate the theory and operation of the Exercise System and document the system designs and testing results for publishing purposes.