This thesis was conducted as part of the efforts related to WPI's Precision Personnel Location (PPL) project, the purpose of which is to locate emergency personnel in hazardous indoor environments using radio location techniques. A unique signal processing algorithm, sART, developed within the PPL project provides means to determine precise position estimates of a wideband transmitter from multipath corrupted signals captured by distributed receivers. This algorithm has synchronization requirements that can not be met without extraordinary expense and complexity by direct means. This thesis develops digital signal processing that achieves the necessary synchronization to satisfy the sART algorithm requirements without additional implementation complexity. The mathematical underpinnings of this solution are introduced and the results are evaluated in the context of experimental data.

In modern power system, the energy conversion includes a large number of the energy processors, and demands high quality, small, lightweight, reliable and efficient power procedures. The existing linear power regulators can only handle low power levels and demonstrate a low efficiency in the power processing. Pulse-width modulated (PWM) converters demonstrate high turn on and turn off losses, and increase in the electromagnetic interference (EMI). Resonant power conversion becomes more suitable in the renewable energy and energy harvesting applications. Since the resonant conversion requires operating in high frequency, the electrical components such as transformers, filter inductors and capacitors become much smaller and lighter. This can result in reducing size and cost. In addition, use of soft switching technique in the resonant conversion reduced the switching losses and EMI level. In this research project, a DC/DC resonant converter has been designed and modelled in PSCAD/EMTDC. The functionality of DC/DC resonant converter is validated in a hardware implementation of the small scale DC system.

The challenge this thesis addresses is to speed up the development of concurrent programs by increasing the efficiency with which concurrent programs can be tested and consequently evolved. The goal of this thesis is to generate methods and tools that help software engineers increase confidence in the correct operation of their programs. To achieve this goal, this thesis advocates testing of concurrent software using a systematic approach capable of enumerating possible executions of a concurrent program. The practicality of the systematic testing approach is demonstrated by presenting a novel software infrastructure that repeatedly executes a program test, controlling the order in which concurrent events happen so that different behaviors can be explored across different test executions. By doing so, systematic testing circumvents the limitations of traditional ad-hoc testing, which relies on chance to discover concurrency errors. However, the idea of systematic testing alone does not quite solve the problem of concurrent software testing. The combinatorial nature of the number of ways in which concurrent events of a program can execute causes an explosion of the number of possible interleavings of these events, a problem referred to as state space explosion. To address the state space explosion problem, this thesis studies techniques for quantifying the extent of state space explosion and explores several directions for mitigating state space explosion: parallel state space exploration, restricted runtime scheduling, and abstraction reduction. In the course of its research exploration, this thesis pushes the practical limits of systematic testing by orders of magnitude, scaling systematic testing to real-world programs of unprecedented complexity.

In modern power system, the energy conversion includes a large number of the energy processors, and demands high quality, small, lightweight, reliable and efficient power procedures. The existing linear power regulators can only handle low power levels and demonstrate a low efficiency in the power processing. Pulse-width modulated (PWM) converters demonstrate high turn on and turn off losses, and increase in the electromagnetic interference (EMI). Resonant power conversion becomes more suitable in the renewable energy and energy harvesting applications. Since the resonant conversion requires operating in high frequency, the electrical components such as transformers, filter inductors and capacitors become much smaller and lighter. This can result in reducing size and cost. In addition, use of soft switching technique in the resonant conversion reduced the switching losses and EMI level. In this research project, a DC/DC resonant converter has been designed and modelled in PSCAD/EMTDC. The functionality of DC/DC resonant converter is validated in a hardware implementation of the small scale DC system.

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The state-space realization problem is a very basic and fundamental problem of control theory. The topic is also becoming increasingly important as practitioners of both physical and social sciences find it crucial to model very complex systems based on input-output data only. In this thesis, a review of the topic will be given for general nonlinear systems and for the less general linear case as well. The thesis will also present some new theoretical results that contribute to the development of the state-space realization topic. Specifically, an important result will show that if a system can be identified by an input-output equation of a particular form, which is fairly general, then a state-space realization can always be easily derived directly from the input-output map. Finally, the theory will be applied to find a state-space model for a nonlinear hydraulic system based on its input-output data.

Many hours are spent by systemand control engineers deriving reduced order dynamicmodels portraying the dominant systemdynamics of thermohydraulic systems. A need therefore exists to develop a method that will automate the model derivation process. The model format preferred for control system design and analysis during preliminary system design is the state space format. The aim of this study is therefore to develop an automated and generic state space model extraction method that can be applied to thermohydraulic systems. Well developed system identification methods exist for obtaining state space models from input-output data, but these models are not transparent, meaning the parameters do not have any physical meaning. For example one cannot identify system parameters such as heat or mass transfer coefficients. Another approach is needed to derive state space models automatically. Many commercial thermohydraulic simulation codes follow a network approach towards the representation of thermohydraulic systems. This approach is probably one of the most advanced approaches in terms of technical development. It would therefore be useful to develop a state space extraction algorithm that would be able to derive reduced order state space models from network representations of thermohydraulic systems. In this regard a network approach is followed in the development of the state space extraction algorithm. The advantage of using a network-based extraction method is that the extracted state space model is transparent and the algorithm can be embedded in existing simulation software that follow a network approach. In this study an existing state space extraction algorithm, used for electrical network analysis, is modified and applied in a new way to extract state space models of thermohydraulic systems. A thermohydraulic system is partitioned into its respective physical domains which, unlike electrical systems, have multiple variables. Network representations are derived for each domain. The state space algorithm is applied to these network representations to extract symbolic state spacemodels. The symbolic parametersmay then be substitutedwith numerical values. The state space extraction algorithm is applied to small scale thermohydraulic systems such as a U-tube and a heat exchanger, but also to a larger, more complex system such as the Pebble Bed Modular Reactor Power Conversion Unit (PBMR PCU). It is also shown that the algorithm can extract linear, nonlinear, time-varying and time-invariant state space models. The extracted state space models are validated by solving the state space models and comparing the solutions with Flownex results. Flownex is an advanced and extensively validated thermo-fluid simulation code. The state space models compared well with Flownex results. The usefulness of the state space model extraction algorithm in model-based control system design is illustrated by extracting a linear time-invariant state space model of the PBMR PCU. This model is embedded in an optimal model-based control scheme called Model-Predictive Control (MPC). The controller is compared with standard optimised control schemes such as PID and Fuzzy PID control. The MPC controller shows superior performance compared to these control schemes. This study succeeded in developing an automated state space model extraction method that can be applied to thermohydraulic networks. Hours spent on writing down equations from first principles to derive reduced order models for control purposes can now be replaced with a click of a button. The need for an automated state space model extraction method for thermohydraulic systems has therefore been resolved / Thesis (Ph.D. (Computer and Electronical Engineering)--North-West University, Potchefstroom Campus, 2009.

Many hours are spent by systemand control engineers deriving reduced order dynamicmodels portraying the dominant systemdynamics of thermohydraulic systems. A need therefore exists to develop a method that will automate the model derivation process. The model format preferred for control system design and analysis during preliminary system design is the state space format. The aim of this study is therefore to develop an automated and generic state space model extraction method that can be applied to thermohydraulic systems. Well developed system identification methods exist for obtaining state space models from input-output data, but these models are not transparent, meaning the parameters do not have any physical meaning. For example one cannot identify system parameters such as heat or mass transfer coefficients. Another approach is needed to derive state space models automatically. Many commercial thermohydraulic simulation codes follow a network approach towards the representation of thermohydraulic systems. This approach is probably one of the most advanced approaches in terms of technical development. It would therefore be useful to develop a state space extraction algorithm that would be able to derive reduced order state space models from network representations of thermohydraulic systems. In this regard a network approach is followed in the development of the state space extraction algorithm. The advantage of using a network-based extraction method is that the extracted state space model is transparent and the algorithm can be embedded in existing simulation software that follow a network approach. In this study an existing state space extraction algorithm, used for electrical network analysis, is modified and applied in a new way to extract state space models of thermohydraulic systems. A thermohydraulic system is partitioned into its respective physical domains which, unlike electrical systems, have multiple variables. Network representations are derived for each domain. The state space algorithm is applied to these network representations to extract symbolic state spacemodels. The symbolic parametersmay then be substitutedwith numerical values. The state space extraction algorithm is applied to small scale thermohydraulic systems such as a U-tube and a heat exchanger, but also to a larger, more complex system such as the Pebble Bed Modular Reactor Power Conversion Unit (PBMR PCU). It is also shown that the algorithm can extract linear, nonlinear, time-varying and time-invariant state space models. The extracted state space models are validated by solving the state space models and comparing the solutions with Flownex results. Flownex is an advanced and extensively validated thermo-fluid simulation code. The state space models compared well with Flownex results. The usefulness of the state space model extraction algorithm in model-based control system design is illustrated by extracting a linear time-invariant state space model of the PBMR PCU. This model is embedded in an optimal model-based control scheme called Model-Predictive Control (MPC). The controller is compared with standard optimised control schemes such as PID and Fuzzy PID control. The MPC controller shows superior performance compared to these control schemes. This study succeeded in developing an automated state space model extraction method that can be applied to thermohydraulic networks. Hours spent on writing down equations from first principles to derive reduced order models for control purposes can now be replaced with a click of a button. The need for an automated state space model extraction method for thermohydraulic systems has therefore been resolved / Thesis (Ph.D. (Computer and Electronical Engineering)--North-West University, Potchefstroom Campus, 2009.

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