Mac protocols for linear wireless (sensor) networks

Wireless sensor networks (WSNs) consist of a large number of sensor nodes, characterized by low power constraint, limited transmission range and limited computational capabilities [1][2].The cost of these devices is constantly decreasing, making it possible to use a large number of sensor devices in a wide array of commercial, environmental, military, and healthcare fields. Some of these applications involve placing the sensors evenly spaced on a straight line for example in roads, bridges, tunnels, water catchments and water pipelines, city drainages, oil and gas pipelines etc., making a special class of these networks which we define as a Linear Wireless Network (LWN). In LWNs, data transmission happens hop by hop from the source to the destination, through a route composed of multiple relays. The peculiarity of the topology of LWNs, motivates the design of specialized protocols, taking advantage of the linearity of such networks, in order to increase reliability, communication efficiency, energy savings, network lifetime and to minimize the end-to-end delay [3]. In this thesis a novel contention based Medium Access Control (MAC) protocol called L-CSMA, specifically devised for LWNs is presented. The basic idea of L-CSMA is to assign different priorities to nodes based on their position along the line. The priority is assigned in terms of sensing duration, whereby nodes closer to the destination are assigned shorter sensing time compared to the rest of the nodes and hence higher priority. This mechanism speeds up the transmission of packets which are already in the path, making transmission flow more efficient. Using NS-3 simulator, the performance of L-CSMA in terms of packets success rate, that is, the percentage of packets that reach destination, and throughput are compared with that of IEEE 802.15.4 MAC protocol, de-facto standard for wireless sensor networks. In general, L-CSMA outperforms the IEEE 802.15.4 MAC protocol.

Feedback linearization of antagonistically actuated variable stiffness joints with twisted string actuators

The work of this thesis is on the implementation of a variable stiffness joint antagonistically actuated by a couple of twisted-string actuator (TSA). This type of joint is possible to be applied in the field of robotics, like UB Hand IV (the anthropomorphic robotic hand developed by University of Bologna). The purposes of the activities are to build the joint dynamic model and simultaneously control the position and stiffness. Three different control approaches (Feedback linearization, PID, PID+Feedforward) are proposed and validated in simulation. To improve the properties of joint stiffness, a joint with elastic element is taken into account and discussed. To the end, the experimental setup that has been developed for the experimental validation of the proposed control approaches.

Development of a model-based transient calibration process for diesel engine electronic control module tables – Part 2: modelling and optimization

This is the second part of a study investigating a model-based transient calibration process for diesel engines. The first part addressed the data requirements and data processing required for empirical transient emission and torque models. The current work focuses on modelling and optimization. The unexpected result of this investigation is that when trained on transient data, simple regression models perform better than more powerful methods such as neural networks or localized regression. This result has been attributed to extrapolation over data that have estimated rather than measured transient air-handling parameters. The challenges of detecting and preventing extrapolation using statistical methods that work well with steady-state data have been explained. The concept of constraining the distribution of statistical leverage relative to the distribution of the starting solution to prevent extrapolation during the optimization process has been proposed and demonstrated. Separate from the issue of extrapolation is preventing the search from being quasi-static. Second-order linear dynamic constraint models have been proposed to prevent the search from returning solutions that are feasible if each point were run at steady state, but which are unrealistic in a transient sense. Dynamic constraint models translate commanded parameters to actually achieved parameters that then feed into the transient emission and torque models. Combined model inaccuracies have been used to adjust the optimized solutions. To frame the optimization problem within reasonable dimensionality, the coefficients of commanded surfaces that approximate engine tables are adjusted during search iterations, each of which involves simulating the entire transient cycle. The resulting strategy, different from the corresponding manual calibration strategy and resulting in lower emissions and efficiency, is intended to improve rather than replace the manual calibration process.

Variations of the Atlantic meridional overturning circulation in control and transient simulations of the last millennium

The variability of the Atlantic meridional overturing circulation (AMOC) strength is investigated in control experiments and in transient simulations of up to the last millennium using the low-resolution Community Climate System Model version 3. In the transient simulations the AMOC exhibits enhanced low-frequency variability that is mainly caused by infrequent transitions between two semi-stable circulation states which amount to a 10 percent change of the maximum overturning. One transition is also found in a control experiment, but the time-varying external forcing significantly increases the probability of the occurrence of such events though not having a direct, linear impact on the AMOC. The transition from a high to a low AMOC state starts with a reduction of the convection in the Labrador and Irminger Seas and goes along with a changed barotropic circulation of both gyres in the North Atlantic and a gradual strengthening of the convection in the Greenland-Iceland-Norwegian (GIN) Seas. In contrast, the transition from a weak to a strong overturning is induced by decreased mixing in the GIN Seas. As a consequence of the transition, regional sea surface temperature (SST) anomalies are found in the midlatitude North Atlantic and in the convection regions with an amplitude of up to 3 K. The atmospheric response to the SST forcing associated with the transition indicates a significant impact on the Scandinavian surface air temperature (SAT) in the order of 1 K. Thus, the changes of the ocean circulation make a major contribution to the Scandinavian SAT variability in the last millennium.

Genetic diversity in an indigenous horse breed: implications for mating strategies and the control of future inbreeding

The Franches-Montagnes is an indigenous Swiss horse breed, with approximately 2500 foalings per year. The stud book is closed, and no introgression from other horse breeds was conducted since 1998. Since 2006, breeding values for 43 different traits (conformation, performance and coat colour) are estimated with a best linear unbiased prediction (BLUP) multiple trait animal model. In this study, we evaluated the genetic diversity for the breeding population, considering the years from 2003 to 2008. Only horses with at least one progeny during that time span were included. Results were obtained based on pedigree information as well as from molecular markers. A series of software packages were screened to combine best the best linear unbiased prediction (BLUP) methodology with optimal genetic contribution theory. We looked for stallions with highest breeding values and lowest average relationship to the dam population. Breeding with such stallions is expected to lead to a selection gain, while lowering the future increase in inbreeding within the breed.

Control of muscle relaxation during anesthesia: a novel approach for clinical routine

During general anesthesia drugs are administered to provide hypnosis, ensure analgesia, and skeletal muscle relaxation. In this paper, the main components of a newly developed controller for skeletal muscle relaxation are described. Muscle relaxation is controlled by administration of neuromuscular blocking agents. The degree of relaxation is assessed by supramaximal train-of-four stimulation of the ulnar nerve and measuring the electromyogram response of the adductor pollicis muscle. For closed-loop control purposes, a physiologically based pharmacokinetic and pharmacodynamic model of the neuromuscular blocking agent mivacurium is derived. The model is used to design an observer-based state feedback controller. Contrary to similar automatic systems described in the literature this controller makes use of two different measures obtained in the train-of-four measurement to maintain the desired level of relaxation. The controller is validated in a clinical study comparing the performance of the controller to the performance of the anesthesiologist. As presented, the controller was able to maintain a preselected degree of muscle relaxation with excellent precision while minimizing drug administration. The controller performed at least equally well as the anesthesiologist.

Adaptive control of sinusoidal brushless DC motor actuators

Electrical Power Assisted Steering system (EPAS) will likely be used on future automotive power steering systems. The sinusoidal brushless DC (BLDC) motor has been identified as one of the most suitable actuators for the EPAS application. Motor characteristic variations, which can be indicated by variations of the motor parameters such as the coil resistance and the torque constant, directly impart inaccuracies in the control scheme based on the nominal values of parameters and thus the whole system performance suffers. The motor controller must address the time-varying motor characteristics problem and maintain the performance in its long service life. In this dissertation, four adaptive control algorithms for brushless DC (BLDC) motors are explored. The first algorithm engages a simplified inverse dq-coordinate dynamics controller and solves for the parameter errors with the q-axis current (iq) feedback from several past sampling steps. The controller parameter values are updated by slow integration of the parameter errors. Improvement such as dynamic approximation, speed approximation and Gram-Schmidt orthonormalization are discussed for better estimation performance. The second algorithm is proposed to use both the d-axis current (id) and the q-axis current (iq) feedback for parameter estimation since id always accompanies iq. Stochastic conditions for unbiased estimation are shown through Monte Carlo simulations. Study of the first two adaptive algorithms indicates that the parameter estimation performance can be achieved by using more history data. The Extended Kalman Filter (EKF), a representative recursive estimation algorithm, is then investigated for the BLDC motor application. Simulation results validated the superior estimation performance with the EKF. However, the computation complexity and stability may be barriers for practical implementation of the EKF. The fourth algorithm is a model reference adaptive control (MRAC) that utilizes the desired motor characteristics as a reference model. Its stability is guaranteed by Lyapunov’s direct method. Simulation shows superior performance in terms of the convergence speed and current tracking. These algorithms are compared in closed loop simulation with an EPAS model and a motor speed control application. The MRAC is identified as the most promising candidate controller because of its combination of superior performance and low computational complexity. A BLDC motor controller developed with the dq-coordinate model cannot be implemented without several supplemental functions such as the coordinate transformation and a DC-to-AC current encoding scheme. A quasi-physical BLDC motor model is developed to study the practical implementation issues of the dq-coordinate control strategy, such as the initialization and rotor angle transducer resolution. This model can also be beneficial during first stage development in automotive BLDC motor applications.

COMPUTATIONAL ANALYSIS OF THE AEROELASTIC DYNAMICS OF A WIND TURBINE BLADE WITH VARIABLE-SPEED STALL CONTROL

The accuracy of simulating the aerodynamics and structural properties of the blades is crucial in the wind-turbine technology. Hence the models used to implement these features need to be very precise and their level of detailing needs to be high. With the variety of blade designs being developed the models should be versatile enough to adapt to the changes required by every design. We are going to implement a combination of numerical models which are associated with the structural and the aerodynamic part of the simulation using the computational power of a parallel HPC cluster. The structural part models the heterogeneous internal structure of the beam based on a novel implementation of the Generalized Timoshenko Beam Model Technique.. Using this technique the 3-D structure of the blade is reduced into a 1-D beam which is asymptotically equivalent. This reduces the computational cost of the model without compromising its accuracy. This structural model interacts with the Flow model which is a modified version of the Blade Element Momentum Theory. The modified version of the BEM accounts for the large deflections of the blade and also considers the pre-defined structure of the blade. The coning, sweeping of the blade, tilt of the nacelle and the twist of the sections along the blade length are all computed by the model which aren’t considered in the classical BEM theory. Each of these two models provides feedback to the other and the interactive computations lead to more accurate outputs. We successfully implemented the computational models to analyze and simulate the structural and aerodynamic aspects of the blades. The interactive nature of these models and their ability to recompute data using the feedback from each other makes this code more efficient than the commercial codes available. In this thesis we start off with the verification of these models by testing it on the well-known benchmark blade for the NREL-5MW Reference Wind Turbine, an alternative fixed-speed stall-controlled blade design proposed by Delft University, and a novel alternative design that we proposed for a variable-speed stall-controlled turbine, which offers the potential for more uniform power control and improved annual energy production.. To optimize the power output of the stall-controlled blade we modify the existing designs and study their behavior using the aforementioned aero elastic model.

EVALUATION OF INTELLIGENT COMPACTION CONTROL IN THE M-189 RECONSTRUCTION PROJECT AT IRON RIVER, MICHIGAN

This research evaluated an Intelligent Compaction (IC) unit on the M-189 highway reconstruction project at Iron River, Michigan. The results from the IC unit were compared to several traditional compaction measurement devices including Nuclear Density Gauge (NDG), Geogauge, Light Weight Deflectometer (LWD), Dynamic Cone Penetrometer (DCP), and Modified Clegg Hammer (MCH). The research collected point measurements data on a test section in which 30 test locations on the final Class II sand base layer and the 22A gravel layer. These point measurements were compared with the IC measurements (ICMVs) on a point-to-point basis through a linear regression analysis. Poor correlations were obtained among different measurements points using simple regression analysis. When comparing the ICMV to the compaction measurements points. Factors attributing to the weak correlation include soil heterogeneity, variation in IC roller operation parameters, in-place moisture content, the narrow range of the compaction devices measurement ranges and support conditions of the support layers. After incorporating some of the affecting factors into a multiple regression analysis, the strength of correlation significantly improved, especially on the stiffer gravel layer. Measurements were also studied from an overall distribution perspective in terms of average, measurement range, standard deviation, and coefficient of variance. Based on data analysis, on-site project observation and literature review, conclusions were made on how IC performed in regards to compaction control on the M-189 reconstruction project.

MULTIDIMENSIONAL OPTIMAL DROOP CONTROL FOR WIND RESOURCES IN DC MICROGRIDS

Two important and upcoming technologies, microgrids and electricity generation from wind resources, are increasingly being combined. Various control strategies can be implemented, and droop control provides a simple option without requiring communication between microgrid components. Eliminating the single source of potential failure around the communication system is especially important in remote, islanded microgrids, which are considered in this work. However, traditional droop control does not allow the microgrid to utilize much of the power available from the wind. This dissertation presents a novel droop control strategy, which implements a droop surface in higher dimension than the traditional strategy. The droop control relationship then depends on two variables: the dc microgrid bus voltage, and the wind speed at the current time. An approach for optimizing this droop control surface in order to meet a given objective, for example utilizing all of the power available from a wind resource, is proposed and demonstrated. Various cases are used to test the proposed optimal high dimension droop control method, and demonstrate its function. First, the use of linear multidimensional droop control without optimization is demonstrated through simulation. Next, an optimal high dimension droop control surface is implemented with a simple dc microgrid containing two sources and one load. Various cases for changing load and wind speed are investigated using simulation and hardware-in-the-loop techniques. Optimal multidimensional droop control is demonstrated with a wind resource in a full dc microgrid example, containing an energy storage device as well as multiple sources and loads. Finally, the optimal high dimension droop control method is applied with a solar resource, and using a load model developed for a military patrol base application. The operation of the proposed control is again investigated using simulation and hardware-in-the-loop techniques.

DC MICROGRID STABILIZATION THROUGH FUZZY CONTROL OF INTERLEAVED, HETEROGENEOUS STORAGE ELEMENTS

As microgrid power systems gain prevalence and renewable energy comprises greater and greater portions of distributed generation, energy storage becomes important to offset the higher variance of renewable energy sources and maximize their usefulness. One of the emerging techniques is to utilize a combination of lead-acid batteries and ultracapacitors to provide both short and long-term stabilization to microgrid systems. The different energy and power characteristics of batteries and ultracapacitors imply that they ought to be utilized in different ways. Traditional linear controls can use these energy storage systems to stabilize a power grid, but cannot effect more complex interactions. This research explores a fuzzy logic approach to microgrid stabilization. The ability of a fuzzy logic controller to regulate a dc bus in the presence of source and load fluctuations, in a manner comparable to traditional linear control systems, is explored and demonstrated. Furthermore, the expanded capabilities (such as storage balancing, self-protection, and battery optimization) of a fuzzy logic system over a traditional linear control system are shown. System simulation results are presented and validated through hardware-based experiments. These experiments confirm the capabilities of the fuzzy logic control system to regulate bus voltage, balance storage elements, optimize battery usage, and effect self-protection.

Reliability of intraoperative high-resolution 2D ultrasound as an alternative to high-field strength MR imaging for tumor resection control: a prospective comparative study

OBJECT: Ultrasound may be a reliable but simpler alternative to intraoperative MR imaging (iMR imaging) for tumor resection control. However, its reliability in the detection of tumor remnants has not been definitely proven. The aim of the study was to compare high-field iMR imaging (1.5 T) and high-resolution 2D ultrasound in terms of tumor resection control. METHODS: A prospective comparative study of 26 consecutive patients was performed. The following parameters were compared: the existence of tumor remnants after presumed radical removal and the quality of the images. Tumor remnants were categorized as: detectable with both imaging modalities or visible only with 1 modality. RESULTS: Tumor remnants were detected in 21 cases (80.8%) with iMR imaging. All large remnants were demonstrated with both modalities, and their image quality was good. Two-dimensional ultrasound was not as effective in detecting remnants<1 cm. Two remnants detected with iMR imaging were missed by ultrasound. In 2 cases suspicious signals visible only on ultrasound images were misinterpreted as remnants but turned out to be a blood clot and peritumoral parenchyma. The average time for acquisition of an ultrasound image was 2 minutes, whereas that for an iMR image was approximately 10 minutes. Neither modality resulted in any procedure-related complications or morbidity. CONCLUSIONS: Intraoperative MR imaging is more precise in detecting small tumor remnants than 2D ultrasound. Nevertheless, the latter may be used as a less expensive and less time-consuming alternative that provides almost real-time feedback information. Its accuracy is highest in case of more confined, deeply located remnants. In cases of more superficially located remnants, its role is more limited.

Revenue Management in Make-To-Order Manufacturing: Case Study of Capacity Control at ThyssenKrupp VDM

While revenue management (RM) is traditionally considered a tool of service operations, RM shows considerable potential for application in manufacturing operations. The typical challenges in make-to-order manufacturing are fixed manufacturing capacities and a great variety in offered products, going along with pronounced fluctuations in demand and profitability. Since Harris and Pinder in the mid-90s, numerous papers have furthered the understanding of RM theory in this environment. Nevertheless, results to be expected from applying the developed methods to a practical industry setting have yet to be reported. To this end, this paper investigates a possible application of RM at ThyssenKrupp VDM, leading to considerable improvements in several areas.

Fuzzy Multi-Objective Linear Programming and Simulation Approach to the Development of Valid and Realistic Master Production Schedule

Master production schedule (MPS) plays an important role in an integrated production planning system. It converts the strategic planning defined in a production plan into the tactical operation execution. The MPS is also known as a tool for top management to control over manufacture resources and becomes input of the downstream planning levels such as material requirement planning (MRP) and capacity requirement planning (CRP). Hence, inappropriate decision on the MPS development may lead to infeasible execution, which ultimately causes poor delivery performance. One must ensure that the proposed MPS is valid and realistic for implementation before it is released to real manufacturing system. In practice, where production environment is stochastic in nature, the development of MPS is no longer simple task. The varying processing time, random event such as machine failure is just some of the underlying causes of uncertainty that may be hardly addressed at planning stage so that in the end the valid and realistic MPS is tough to be realized. The MPS creation problem becomes even more sophisticated as decision makers try to consider multi-objectives; minimizing inventory, maximizing customer satisfaction, and maximizing resource utilization. This study attempts to propose a methodology for MPS creation which is able to deal with those obstacles. This approach takes into account uncertainty and makes trade off among conflicting multi-objectives at the same time. It incorporates fuzzy multi-objective linear programming (FMOLP) and discrete event simulation (DES) for MPS development.

Risk of Cardiovascular Events and Blood Pressure Control in Hypertensive HIV-Infected Patients: HIV Cohort Study (SHCS)

Background: Prevalence of hypertension in HIV infection is high, and information on blood pressure control in HIV-infected individuals is insufficient. We modeled blood pressure over time and the risk of cardiovascular events in hypertensive HIV-infected individuals. Methods: All patients from the Swiss HIV Cohort Study with confirmed hypertension (systolic or diastolic blood pressure above 139 or 89 mm Hg on 2 consecutive visits and presence of at least 1 additional cardiovascular risk factor) between April 1, 2000 and March 31, 2011 were included. Patients with previous cardiovascular events, already on antihypertensive drugs, and pregnant women were excluded. Change in blood pressure over time was modeled using linear mixed models with repeated measurement. Results: Hypertension was diagnosed in 2595 of 10,361 eligible patients. Of those, 869 initiated antihypertensive treatment. For patients treated for hypertension, we found a mean (95% confidence interval) decrease in systolic and diastolic blood pressure of −0.82 (−1.06 to −0.58) mm Hg and −0.89 (−1.05 to −0.73) mm Hg/yr, respectively. Factors associated with a decline in systolic blood pressure were baseline blood pressure, presence of chronic kidney disease, cardiovascular events, and the typical risk factors for cardiovascular disease. In patients with hypertension, increase in systolic blood pressure [(hazard ratio 1.18 (1.06 to 1.32) per 10 mm Hg increase], total cholesterol, smoking, age, and cumulative exposure to protease inhibitor–based and triple nucleoside regimens were associated with cardiovascular events. Conclusions: Insufficient control of hypertension was associated with increased risk of cardiovascular events indicating the need for improved management of hypertension in HIV-infected individuals.