For the successful deployment of task-achieving multi-robot systems (MRS), the interactions must be coordinated among the robots within the MRS and between the robots and the task environment. There have been a number of impressive experimentally demonstrated coordinated MRS. However it is still of a premature stage for real world applications. This dissertation presents an MRS control scheme using Artificial Immune Systems (AIS). This methodology is firmly grounded in the biological sciences and provides robust performance for the intertwined entities involved in any task-achieving MRS. Based on its formal foundation, it provides a platform to characterize interesting relationships and dependencies among MRS task requirements, individual robot control, capabilities, and the resulting task performance. The work presented in this dissertation is a first of its kind wherein the principles of AIS have been used to model and organize the group behavior of the MRS. This has been presented in the form of a novel algorithm. In addition to the above, generic environments for computer simulation and real experiment have been realized to demonstrate the working of an MRS. These could potentially be used as a test bed to implement other algorithms onto the MRS. The experiment in this research is a bomb disposal task which involves a team of three heterogeneous robots with different sensors and actuators. And the algorithm has been tested practically through computer simulations.

The data assimilation process of adjusting variables in a reservoir simulation model to honor observations of field data is known as history matching and has been extensively studied for few decades. However, limited success has been achieved due to the high complexity of the problem and the large computational effort required by the practical applications. An automatic history matching module based on the ensemble Kalman filter is developed and validated in this dissertation. The ensemble Kalman filter has three steps: initial sampling, forecasting through a reservoir simulator, and assimilation. The initial random sampling is improved by the singular value decomposition, which properly selects the ensemble members with less dependence. In this way, the same level of accuracy is achieved through a smaller ensemble size. Four different schemes for the assimilation step are investigated and direct inverse and square root approaches are recommended. A modified ensemble Kalman filter algorithm, which addresses the preference to the ensemble members through a nonequally weighting factor, is proposed. This weighted ensemble Kalman filter generates better production matches and recovery forecasting than those from the conventional ensemble Kalman filter. The proposed method also has faster convergence at the early time period of history matching. Another variant, the singular evolutive interpolated Kalman filter, is also applied. The resampling step in this method appears to improve the filter stability and help the filter to deliver rapid convergence both in model and data domains. This method and the ensemble Kalman filter are effective for history matching and forecasting uncertainty quantification. The independence of the ensemble members during the forecasting step allows the benefit of high-performance computing for the ensemble Kalman filter implementation during automatic history matching. Two-level computation is adopted; distributing ensemble members simultaneously while simulating each member in a parallel style. Such computation yields a significant speedup. The developed module is integrated with reservoir simulators UTCHEM, GEM and ECLIPSE, and has been implemented in the framework Integrated Reservoir Simulation Platform (IRSP). The successful applications to two and three-dimensional cases using blackoil and compositional reservoir cases demonstrate the efficiency of the developed automatic history matching module.

published_or_final_version / Physics / Master / Master of Philosophy

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The MANIMEA $ rm ( underline{MA}nurial underline{NI}trogen underline{M}anagement{:} underline{E}nvironmental underline{A}spects)$ model is a one-dimensional dynamic model that simultaneously simulates nitrogen transformations (volatilization, net mineralization-immobilization, and denitrification), nitrogen transport (runoff and leaching), plant uptake, and adsorption in homogeneous, unsaturated soils. The simulated system is divided into two components: the applied manure layer and the soil. The model describes the transformation processes occurring in both components separately. It is also capable of accounting for both micro and macroporous flows. In addition, the simulation can be done for time steps shorter than 1 day. / The model was developed to be interactive and user-friendly and was constructed on a modular basis using Microsoft FORTRAN PowerStation$ sp circler$ as a compiler. It can be run on an IBM$ sp circler$ or IBM compatible microcomputer with a minimum requirement of a 386 microprocessor with 4 MB RAM. This model was developed as a nitrogen management-oriented model. However, it can also be used to gain further understanding of nitrogen processes for research and teaching purposes. / The accuracy of the stimulation was enhanced by taking into account moisture and temperature variation and distribution in the soil. The SWACROP and the HEAT programs were integrated into the MANIMEA model to generate transient moisture and temperature profiles, respectively. The Numerical Method Of Lines (NMOL) technique, which implements finite difference method, was used to numerically solve the partial differential equations in the model. / Generally, the results generated by the MANIMEA model using the parameters from literature agreed with the results obtained by analytical solutions and from experiments. It was found that the model is highly sensitive to the volatilization and net mineralization rate constants $(K sb{v}$ and $K sb{m}).$ The study showed that the MANIMEA model can be implemented to evaluate nitrogen transformations, transport, and plant uptake for a wide range of climatic and soil conditions and organic type of wastes. Such a tool can contribute to the protection of our environment through a better management of organic nitrogen fertilizer and a better understanding of the nitrogen processes.

As modern integrated-circuit (IC) technology advances, the level of integration increases, and so too does the clock speed of on-chip signals. As a result, signal integrity has become a major issue on which the circuit performance is largely based. Clock jitter is one of the main issues of signal integrity, and it has become one of the most important circuit limitations. / While extensive research is on-going to reduce clock jitter in ICs, researchers have also been actively involved in discovering ways to characterize it through applications of new time measurement units, or TMUs for short. A number of TMUs have been designed with resolutions down to the picosecond range, among which the time-to-voltage converter (TVC) is a very popular family of circuits used for making highly precise and accurate time measurements. These circuits are popular due to their excellent linearity properties and their ease of fabrication. Nonetheless, these circuits suffer from metastability issues, limiting the lower end of their measurement range. / This thesis first reviews the past TMU circuits, and then presents a TVC architecture that solves the metastability problem. In addition, pipelined operation is added to further increase the throughput of the design. The resolution of the TVC is made adjustable such that it can be used as a stand-alone TMU for different types of applications. The proposed TVC is both verified in simulation and experimentally using a custom designed circuit in a standard 0.18 microm CMOS process supplied by TSMC. Finally, a calibration method is included to further improve the linearity of the overall design.

Water is characterised by both its quantity (availability) and its quality. Salinity, which is one of the major water quality parameters limiting use of a wide range of land and water resources, refers to the total dissolved solutes in water. It is influenced by a combination of several soil-water-salt-plant related processes. In order to develop optimum management schemes for environmental control through relevant hydrological modelling techniques, it is important to identify and understand these processes affecting salinity. Therefore, the various sources and processes controlling salt release and transport from the soil surface through the root zone to groundwater and streams as well as reservoirs are extensively reviewed in this project with subsequent exploration of some hydro salinity modelling approaches. The simulation of large and complex hydrological systems, such as these at a catchment scale, requires a flexible and efficient modelling tool to assist in the assessment of the impact of land and water use alternatives on the salt balance. The currently available catchment models offer varying degrees of suitability with respect to modelling hydrological problems, dependent on the model structure and the type of the approach used. The A CR U agrohydrological modelling system, with its physically-conceptually based characteristics as well as being a multi-purpose model that is able to operate both as a lumped and distributed model, was found to be suitable for hydro salinity modelling at a catchment scale through the incorporation of an appropriate hydro salinity module. The main aim of this project was to develop, validate and verify a hydro salinity module for the ACRU model. This module is developed in the object-oriented version of ACRU, viz. ACRU2000, and it inherits the basic structure and objects of the model. The module involves the interaction of the hydrological processes represented in ACRU and salinity related processes. Hence, it is designated as ACRUSalinity. In general, the module is developed through extensive review of ACRU and hydrosalinity models, followed by conceptualisation and design of objects in the module. It is then written in Java object-oriented programming language. The development of ACRUSalinity is based mainly on the interaction between three objects, viz. Components, Data and Processes. Component objects in ACRU2000 represent the physical features in the hydrological system being modelled. Data objects are mainly used to store data or information. The Process objects describe processes that can take place in a conceptual or real world hydrological system. The Process objects in ACRUSalinity are grouped into six packages that conduct: • the initial salt load determination in subsurface components and a reservoir • determination of wet atmospheric deposition and salt input from irrigation water • subsurface salt balance, salt generation and salt movement • surface flow salt balance and salt movement • reservoir salt budgeting and salt routing and • channel-reach salt balancing and, in the case of distributed hydro salinity modelling, salt transfer between sub-catchments. The second aim of the project was the validation and verification of the module. Code validation was undertaken through mass balance computations while verification of the module was through comparison of simulated streamflow salinity against observed values as recorded at gauging weir UIH005 which drains the Upper Mkomazi Catchment in KwaZuluNatal, South Africa. Results from a graphical and statistical analysis of observed and simulated values have shown that the simulated streamflow salinity values mimic the observed values remarkably well. As part of the module development and validation, sensitivity analysis of the major input parameters of ACRUSalinity was also conducted. This is then followed by a case study that demonstrates some potential applications of the module. In general, results from the module evaluation have indicated that ACRUSalinity can be used to provide a reasonable first order approximation in various hydrosalinity studies. Most of the major sources and controlling factors of salinity are accommodated in the ACRUSalinity module which was developed in this project. However, for a more accurate and a better performance of the module in diversified catchments, further research needs to be conducted to account for the impact of salt loading from certain sources and to derive the value of some input parameters to the new module. The research needs include incorporation in the module of the impact of salt loading from fertilizer applications as well as from urban and industrial effluents. Similarly, further research needs to be undertaken to facilitate the module's conducting salt routing at sub-daily time step and to account for the impact of bypass flows in heavy soils on the surface and subsurface salt balances. / Thesis (M.Sc.)-University of Natal, Pietermaritzburg, 2003.

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