This dissertation aims at solving the consensus control problem of multi-agent systems with Lipschitz nonlinearity. This depends on the design of the controller that enables each agent or subsystem in multi-agent systems with Lipschitz nonlinearity to reach consensus; using the understanding of the agents' connection network from the knowledge of graph theory as well as the control system design strategy. The objective is achieved by designing a type of distributed control, namely the consensus control, which manipulates the relative information of each agent in a multi-agent systems in order to arrive at a single solution. In addition, containment control is also developed to solve containment problem. It is an extension of consensus control via leader-follower configuration, aimed at having each agent contained by multiple leaders in a multi-agent systems with Lipschitz nonlinearity. Four types of controllers are proposed - state-feedback consensus controller, observer-based consensus controller, state-feedback containment controller and observer-based containment controller; each provides the stability conditions based on Lyapunov stability analysis in time domain which enabled each agent or subsystem to reach consensus. The observer-based controllers are designed based on the consensus observer that is related to Luenberger observer. Linear Matrix Inequality (LMI) and Algebraic Riccati Equation (ARE) are utilized to obtain the solutions for the stability conditions. The simulation results of the proposed controllers and observers have been carried out to prove their theoretical validity. Several practical examples of flexible robot arm simulations are included to further validate the theoretical aspects of the thesis.

Mitigating energy poverty requires a multi-criteria decision protocol integrating socio-economic, cultural, environmental, and technical systems, influencing energy access, and consumption. Situations of energy poverty are typical in rural and urban poor households, particularly in sub-Saharan Africa. These situations are commonly prevalent in informal settlements, sprawling across the periphery of South African metros. Majorities of informal households lack access to grid-electricity and consume local energy sources for their energy needs. There are ongoing government efforts directed to mitigating energy poverty among energy-poor households, such as informal households, through policies and subsidies. Socio-economic and cultural environments also redefine the extent to which energy poverty is mitigated in these households. At present, informal households are constantly and rapidly growing, and as a result, compromise policy effectiveness and other functional strategies, targeting to mitigating energy poverty in these households, and achieving universal energy access in South Africa. Accordingly, this research study adopted a multidisciplinary approach to understanding related matters of energy poverty based on energy policies; electricity access, and pricing; geospatial analysis; energy use and access; and management strategies, with emphasis on informal settlements in South Africa. The first part of the study reviewed energy pro-poor policies, relevant to improving energy access and energy-use efficiency in energy-poor households in South Africa. The study also investigated electricity access (access rates), connection costs (access costs), and electricity tariffs to understand historical precedents and forecast scenarios, and the relationships to gaining complete electricity access by 2030 in the City of Cape Town. The third part mapped and monitored informal areas to understand landscape processes and poverty with energy poverty propagations by Land Cover (LC) and Land-Cover Change (LCC) in the City of Cape Town. The fourth part of the research investigated energy-use patterns and other energy-related matters in a selected informal settlement - a typical case study of an energy-poor community in South Africa and sub-Saharan Africa. The last part proposed and designed a novel System Reinforcing Model (SRM), an Energy Access Sustainability (EAS) management scheme, applicable to mitigating energy poverty in any energy-poor community. The study review validated government efforts in improving energy access in energy-poor households through commissioned energy pro-poor policies but not without drawbacks and proposed recommendations to support future policy reforms. The research also revealed iv A novel systems approach to energy poverty in sub-Saharan Africa: A South African informal settlement as case study. increasing patterns in historical trends of access rates, costs, and tariffs, and relationships between parameters within the assessment period (from 2010 to 2018). The forecast analyses (from 2019 to 2030) demonstrated that total electricity access could not be reached by 2030 without a shift in Business-As-Usual (BAU) patterns in the City of Cape Town. The LC conversions of informal areas revealed poverty with energy poverty propagations through landscape degradation processes - Persistence and Intensification - in the City of Cape Town. The research study further revealed poor energy use patterns and behaviour in the target Settlement. Informal households in the settlement mainly adopted local energy fuels and appliances in satisfying household energy needs. The novel part of the research study described the application of a systems approach - Systems engineering (SE) and Systems Thinking (SsT) - into energy poverty and access processes to developing the new SRM. SE and SsT concept analyses were employed in identifying and integrating four operating system interfaces in these processes into the new SRM. The new SRM simulated complex systems and elements within the interfaces and categorized them as design decisions and system designs. These systems and elements were grounded in energy-use patterns and behaviour, energy access, and EAS, as well as socio-economic, cultural, technical, and environmental features. Arrays of feedback loops in reinforcing patterns in the new SRM modelled the interactions between, and within, design decisions and system designs, for future energy access rebranding, based on significant sustainability outcomes of favourably coalesced system interfaces. SRM was applied in the target settlement, where the model’s significance was validated. Based on its multi-criteria decision approach, among its many features, SRM revealed system parts instigating energy poverty situations and limiting EAS in the target settlement. SRM tailored energy access solutions, whilst integrating significant outcomes of the whole research study, to advancing energy poverty mitigation and EAS in the target settlement. / Thesis (PhD (Technology Management))--University of Pretoria, 2020. / UP Postgraduate Bursary / International Council on Systems Engineering (INCOSE) / Graduate School of Technology Management (GSTM) / PhD (Technology Management) / Unrestricted

Anomaly detection in computer systems operating within complex environments,such as cyber-physical systems (CPS), has become increasingly popularduring these last years due to useful insights this process can provide aboutcomputer systems’ health conditions against known reference nominal states.As performance anomalies lead degraded service delivery, and, eventually,system-wide failures, promptly detecting such anomalies may trigger timelyrecovery responses. In this thesis, Process Mining, a discipline aiming at connectingdata science with process science, is broadly explored and employedfor detecting performance anomalies in complex computer systems, proposinga methodology for connecting event data to high-level process models forvalidating functional and non-functional requirements, evaluating system performances,and detecting anomalies. The proposed methodology is appliedto the industry-relevant European Rail Traffic Management System/EuropeanTrain Control System (ERTMS/ETCS) case-study. Experimental results sampledfrom an ERTMS/ETCS system Demonstrator implementing one of thescenarios the standard prescribe have shown Process Mining allows characterizingnominal system performances and detect deviations from such nominalconditions, opening the opportunity to apply recovery routines for steeringsystem performances to acceptable levels.

Recent years have shown a growing concern over increasing traffic volume worldwide. The insufficient road capacity and the resulting congestions have become major problems in many urban areas. Congestions negatively impact the economy, the environment and the health of the population as well as the drivers satisfaction. Current solutions to this topical and timely problem rely on the exploitation of Intelligent Transportation Systems (ITS) technologies. ITS urban traffic management involves the collection and processing of a large amount of geographically distributed information to control distributed infrastructure and individual vehicles. The distributed nature of the problem prompted the development of a novel, scalable ITS-Cloud platform. The ITS-Cloud organises the processing and manages distributed data sources to provide traffic management methods with more accurate information about the state of the traffic. A new approach to service allocation, derived from the existing cloud and grid computing approaches, was created to address the unique needs of ITS traffic management. The ITS-Cloud hosts the collection of software services that form the Cloud based Traffic Management System (CTMS). CTMS combines intersection control algorithms with intersection approach advices to the vehicles and dynamic routing. The CTMS contains a novel Two-Step traffic management method that relies on the ITS-Cloud to deliver a detailed traffic simulation image and integrates an adaptive intersection control algorithm with a microscopic prediction mechanism. It is the first method able to perform simultaneous adaptive intersection control and intersection approach optimization. The Two-Step method builds on a novel pressure based adaptive intersection control algorithm as well as two new traffic prediction schemes. The developed traffic management system was evaluated using a new microscopic traffic simulation tool tightly integrated with the ITS-Cloud. The novel traffic management approaches were shown to outperform benchmark methods for a realistic range of traffic conditions and road network configurations. Unique to the work was the investigation of interactions between ITS components.

The objective of the thesis is concerned on the problem of detecting superpositional signals in a wireless channel. In many wireless systems, an observed signal is commonly represented as a linear combination of the transmitted signal with the interfering signals dispersed in space and time. These systems are generally known as the interference-limited systems. The mathematical model of these systems is generally referred as a superpositional model. A distinguished characteristic of signal transmission in a time-varying wireless channel is that the channel process is not known a priori. Reliable signal reception inherently requires exploiting the structure of the interfering signals under channel uncertainty. Our goal is to design computational efficient receivers for various interference-limited systems by using advanced statistical signal processing techniques. The thesis consists of four main parts. Firstly, we have proposed a novel Multi-Input Multi-Output (MIMO) signal detector, known as the neighbourhood exploring detector (NED). According to the maximum likelihood principle, the space time MIMO detection problem is equivalent to a NP-hard combinatorial optimization problem. The proposed detector is a sub-optimal maximum likelihood detector which eliminates exhaustive multidimensional searches. Secondly, we address the problem of signal synchronization for Global Positioning System (GPS) in a multipath environment. The problem of multipath mitigation constitutes a joint estimation of the unknown amplitudes, phases and time delays of the linearly combined signals. The complexity of the nonlinear joint estimation problem increases exponentially with the number of signals. We have proposed two robust GPS code acquisition systems with low complexities. Thirdly, we deal with the problem of multipath mitigation in the spatial domain. A GPS receiver integrated with the Inertial Navigation System (INS) and a multiple antenna array is considered. We have designed a software based GPS receiver which effectively estimates the directions of arrival and the time of arrival of the linearly combined signals. Finally, the problem of communications with unknown channel state information is investigated. Conventionally, the information theoretical communication problem and the channel estimation problem are decoupled. However the training sequence, which facilitates the estimation of the channel, reduces the throughput of the channel. We have analytically derived the optimal length of the training sequence which maximizes the mutual information in a block fading channel.

Nowadays the complexity and size of business systems is growing steadily and, as practise shows, the situation is not going to change in the nearest future. This necessitates difficulties not only for lifecycle of programmes’ development but for maintenance and expansibility also. That’s why, solving them, requires a broader perspective that views the system as consisting of other systems. This work looks what kind of methods can be applied in this context. The analysis of modern technologies (Java programming language) and modelling methods (functional decomposition and object-oriented system engineering) are presented. Suggested system decomposition approach is the synthesis of already existing ones. In this work new method has been applied for the development of experimental Information System of Territorial Departments of Environmental Inspection. The prototype of the mentioned system has been realized by using J2EE (Java 2, Enterprise Edition) technologies. Developed software implements the requirements for usage and maintenance (large number of the users, security rights, compatibility, centralised administration, etc.) of large distributed systems. Suggested approach may be used while expanding the existing software or developing similar applications.

This paper provides an evolutionary perspective on financial systems based on complex systems theory. This perspective is used to organize the discussion about the convergence and non-convergence of financial systems. In recent years the discussion about the relative merits and the efficiency of market- and bank-based financial systems is subject to considerable academic and policy debate throughout the world. Bank- and market-based systems are found to give rise to different economic and corporate dynamics. Based on a notion of financial systems as configuration of complementary elements, it is suggested that the convergence of financial systems is best conceptualized as path dependent process of institutional change. This is illustrated with special reference to the recent developments of convergence of financial systems in Europe. The implication of the evolutionary perspective on financial systems is that neither theories using a simple evolutionary argument of survival of the fittest nor theories related to a institutional ossification perspective can provide much guidance for analyzing the transformations of financial systems. A multilevel institutional analysis which takes the interdependencies between national and firm-level institutions explicitly into account is required. (author's abstract) / Series: Working Papers Series "Growth and Employment in Europe: Sustainability and Competitiveness"

Thesis (M.S.)--University of Alabama at Birmingham, 2008. / Description based on contents viewed Oct. 7, 2008; title from PDF t.p. Includes bibliographical references (p. 80-81).

This thesis aims to propose multiple methods for performing a hardware-in-the-loop simulation, providing the hardware and software tools necessary for design and execution. For this purpose, methods of modeling commonly encountered dynamical system components are explored and techniques suitable for calculating the states of the modeled system are presented. Modules and subsystems that enable the realization of a hardware-in-the-loop simulation application and its interfacing with external controller hardware are explained. The thesis also presents three different simulation scenarios. Solutions suitable for these scenarios are provided along with their implementations. The details and specifications of the developed software packages and hardware platforms are given. The provided results illustrate the advantages and disadvantages of the approaches used in these solutions.

Thesis (M.S.)--University of Tennessee, Knoxville, 2010. / Title from title page screen (viewed on July 20, 2010). Thesis advisor: Paul Ayers. Vita. Includes bibliographical references.