Output disturbance rejection using parallel model predictive control

The solution time of the online optimization problems inherent to Model Predictive Control (MPC) can become a critical limitation when working in embedded systems. One proposed approach to reduce the solution time is to split the optimization problem into a number of reduced order problems, solve such reduced order problems in parallel and selecting the solution which minimises a global cost function. This approach is known as Parallel MPC. The potential capabilities of disturbance rejection are introduced using a simulation example. The algorithm is implemented in a linearised model of a Boeing 747-200 under nominal flight conditions and with an induced wind disturbance. Under significant output disturbances Parallel MPC provides a significant improvement in performance when compared to Multiplexed MPC (MMPC) and Linear Quadratic Synchronous MPC (SMPC). © 2013 IEEE.

Enhancing parametric sensitivity using mode localization in electrically coupled mems resonators

We use vibration localization as a sensitive means of detecting small perturbations in stiffness in a pair of weakly coupled micromechanical resonators. For the first time, the variation in the eigenstates is studied by electrostatically coupling nearly identical resonators to allow for stronger localization of vibrational energy due to perturbations in stiffness. Eigenstate variations that are orders of magnitude greater than corresponding shifts in resonant frequency for an induced stiffness perturbation are experimentally demonstrated. Such high, voltagetunable parametric sensitivities together with the added advantage of intrinsic common mode rejection pave the way to a new paradigm of mechanical sensing. ©2009 IEEE.

Autonomous extraction of optimal flame fronts in OH planar laser-induced fluorescence images.

The location of a flame front is often taken as the point of maximum OH gradient. Planar laser-induced fluorescence of OH can be used to obtain the flame front by extracting the points of maximum gradient. This operation is typically performed using an edge detection algorithm. The choice of operating parameters a priori poses significant problems of robustness when handling images with a range of signal-to-noise ratios. A statistical method of parameter selection originating in the image processing literature is detailed, and its merit for this application is demonstrated. A reduced search space method is proposed to decrease computational cost and render the technique viable for large data sets. This gives nearly identical output to the full method. These methods demonstrate substantial decreases in data rejection compared to the use of a priori parameters. These methods are viable for any application where maximum gradient contours must be accurately extracted from images of species or temperature, even at very low signal-to-noise ratios.

Phone-level pronunciation scoring and assessment for interactive language learning

This paper investigates a method of automatic pronunciation scoring for use in computer-assisted language learning (CALL) systems. The method utilizes a likelihood-based `Goodness of Pronunciation' (GOP) measure which is extended to include individual thresholds for each phone based on both averaged native confidence scores and on rejection statistics provided by human judges. Further improvements are obtained by incorporating models of the subject's native language and by augmenting the recognition networks to include expected pronunciation errors. The various GOP measures are assessed using a specially recorded database of non-native speakers which has been annotated to mark phone-level pronunciation errors. Since pronunciation assessment is highly subjective, a set of four performance measures has been designed, each of them measuring different aspects of how well computer-derived phone-level scores agree with human scores. These performance measures are used to cross-validate the reference annotations and to assess the basic GOP algorithm and its refinements. The experimental results suggest that a likelihood-based pronunciation scoring metric can achieve usable performance, especially after applying the various enhancements.

High-quality pulse compressor for WDM/OTDM applications

The paper reports the results of a high-quality pulse source incorporating a gain-switched laser diode followed by a novel compact two-cascade fibre compression scheme. The pulse compression scheme incorporates a dispersive delay line and a nonlinear pulse compressor based on a dispersion-imbalanced fibre loop mirror (DILM). We analyse and demonstrate for the first time significant improvement of the loop performance by means of the chirped pulse switching. As a result, the DILM provides high-quality nonlinear pulse compression as well as rejection of the nonsoliton component. In the experiment, 20ps pulses from a gain switched laser diode are compressed to a duration of 300fs at a repetition rate in range 70MHz-10GHz. The pulses are pedestal free and transform-limited. Spectral filtering of the output signal by means of a bandpass filter results in generation of wavelength-tuneable picosecond pulses with a duration defined by the filter bandwidth. Alternatively, signal filtering by an arrayed waveguide grating (AWG) results in multichannel picosecond pulse generation for WDM and OTDM applications. The pulse source is built of standard components and is of compact and potentially robust design.

Coexistence of high-bit-rate quantum key distribution and data on optical fiber

Quantum key distribution (QKD) uniquely allows distribution of cryptographic keys with security verified by quantum mechanical limits. Both protocol execution and subsequent applications require the assistance of classical data communication channels. While using separate fibers is one option, it is economically more viable if data and quantum signals are simultaneously transmitted through a single fiber. However, noise-photon contamination arising from the intense data signal has severely restricted both the QKD distances and secure key rates. Here, we exploit a novel temporal-filtering effect for noise-photon rejection. This allows high-bit-rate QKD over fibers up to 90 km in length and populated with error-free bidirectional Gb/s data communications. With high-bit rate and range sufficient for important information infrastructures, such as smart cities and 10 Gbit Ethernet, QKD is a significant step closer towards wide-scale deployment in fiber networks.

Risk based lifetime costs assessment of a ground source heat pump (GSHP) system design: Methodology and case study

Space heating accounts for a large portion of the world's carbon dioxide emissions. Ground Source Heat Pumps (GSHPs) are a technology which can reduce carbon emissions from heating and cooling. GSHP system performance is however highly sensitive to deviation from design values of the actual annual energy extraction/rejection rates from/to the ground. In order to prevent failure and/or performance deterioration of GSHP systems it is possible to incorporate a safety factor in the design of the GSHP by over-sizing the ground heat exchanger (GHE). A methodology to evaluate the financial risk involved in over-sizing the GHE is proposed is this paper. A probability based approach is used to evaluate the economic feasibility of a hypothetical full-size GSHP system as compared to four alternative Heating Ventilation and Air Conditioning (HVAC) system configurations. The model of the GSHP system is developed in the TRNSYS energy simulation platform and calibrated with data from an actual hybrid GSHP system installed in the Department of Earth Science, University of Oxford, UK. Results of the analysis show that potential savings from a full-size GSHP system largely depend on projected HVAC system efficiencies and gas and electricity prices. Results of the risk analysis also suggest that a full-size GSHP with auxiliary back up is potentially the most economical system configuration. © 2012 Elsevier Ltd.

Estimation of soil properties and deformations in staged constructions based on mcmc method

This paper presents a Bayesian probabilistic framework to assess soil properties and model uncertainty to better predict excavation-induced deformations using field deformation data. The potential correlations between deformations at different depths are accounted for in the likelihood function needed in the Bayesian approach. The proposed approach also accounts for inclinometer measurement errors. The posterior statistics of the unknown soil properties and the model parameters are computed using the Delayed Rejection (DR) method and the Adaptive Metropolis (AM) method. As an application, the proposed framework is used to assess the unknown soil properties of multiple soil layers using deformation data at different locations and for incremental excavation stages. The developed approach can be used for the design of optimal revisions for supported excavation systems. © 2010 ASCE.

Conceptual design of Americium nuclear battery for space power applications

This work presents simplified 242mAm-fueled nuclear battery concept design featuring direct fission products energy conversion and passive heat rejection. Optimization of the battery operating characteristics and dimensions was performed. The calculations of power conversion efficiency under thermal and nuclear design constraints showed that 5.6 W e/kg power density can be achieved, which corresponds to conversion efficiency of about 4%. A system with about 190 cm outer radius translates into 17.8 MT mass per 100 kW e. Total power scales linearly with the outer surface area of the battery through which the residual heat is rejected. Tradeoffs between the battery lifetime, mass, dimensions, power rating, and conversion efficiency are presented and discussed. The battery can be used in a wide variety of interplanetary missions with power requirements in the kW to MW range. Copyright © 2007 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.