<p dir="ltr">State estimation is a type of an <i>inverse problem</i> in which some amount of observed data needs to be processed using computer algorithms (which are designed using analytical techniques) to infer or reconstruct the underlying model that produced the data. Due to the ubiquity of data and interconnected control systems in the present day, many engineering domains have become replete with inverse problems that can be formulated as state estimation problems. The interconnectedness of these control systems imparts the associated state estimation problems with distinctive structural properties that must be taken into consideration. For instance, the observed data could be high-dimensional and have a dependency structure that is best described by a graph. Furthermore, the control systems of today interface with each other and with the internet, bringing in new possibilities for large-scale collaborative sensor fusion, while also (potentially) introducing new sources of disturbances, faults, and cyberattacks. </p><p dir="ltr">The main thesis of this document is to investigate the unique challenges related to the issues of robustness, resilience (to faults and cyberattacks), and scalability of state estimation algorithms. These correspond to research questions such as, <i>"Does the state estimation algorithm retain its performance when the measurements are perturbed by unknown disturbances or adversarial inputs?"</i> and <i>"Does the algorithm have any bottlenecks that restrict the size/dimension of the problems that it could be applied to?".</i> Most of these research questions are motivated by a singular domain of application: autonomous navigation of unmanned aerial vehicles (UAVs). Nevertheless, the mathematical methods and research philosophy employed herein are quite general, making the results of this document applicable to a variety of engineering tasks, including anomaly detection in time-series data, autonomous remote sensing, traffic monitoring, coordinated motion of dynamical systems, and fault-diagnosis of wireless sensor networks (WSNs), among others.</p>

Society today brings a high pace development and demand of Artificial intelligence systems as well as robotics. To further expand and to take one step closer to have Unmanned Aerial Vehicles (UAVs) working in the cities, the European Union Aviation Safety Agency launched a project that introduces U-space airspace, an airspace where UAVs, for instance, are allowed to operate for commercial services.The problems defined for U-space airspace resemble problems defined in the area of multi-agent path finding, such as scaling and traffic etc., resulting an interest to research whether MAPF-solutions can be applied to U-space scenarios. The following thesis extends the state-of-the-art MAPF-algorithm Continuous-time Conflict based search (CCBS) to handle simplified U-space scenarios, as well as extend other A*-based algorithms, such as a version of the Receding Horizon Lattice-based Motion Planning named Extended Multi-agent A* algorithm with Wait-Time (EMAWT) and an extended A* named Extended Multi-agent A* algorithm (EMA) to handle them. Comparisons of the three algorithms resulted in the EMAWT being the most reliable and stable solution throughout all tests, whilst for fewer agents, the CCBS being the clear best solution.

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Multi-agent systems are employed for a group of agents to achieve coordinated tasks, in which distributed sensing, computing, communication and control are usually integrated with shared resources. Efficient usage of these resources is therefore an important issue. In addition, in applications such as robotics, a group of agents may encounter the request of a sequence of tasks and deadline constraint on the completion of each task is a common requirement. Thus, the integration of multi-agent task scheduling and control synthesis is of great practical interest. In this thesis, we study control of multi-agent systems under a networked control system framework. The first purpose is to design resource-efficient communication and control strategies to solve consensus problem for multi-agent systems.The second purpose is to jointly schedule task sequence and design controllers for multiagent systems that are subject to a sequence of deadline-constrained tasks. In the first part, a distributed asynchronous event-triggered communication and control strategy is proposed to tackle multi-agent consensus. It is shown that the proposed event-triggered communication and control strategy fulfils the reduction of both the rates of sensor-controller communication and controller-actuator communication as well as excluding Zeno behavior. To further relax the requirement of continuous sensing and computing, a periodic event-triggered communication and control strategy is proposed in the second part. In addition, an observer-based encoder-decoder with finite-level quantizeris designed to deal with the constraint of limited data rate. An explicit formula for the maximum allowable sampling period is derived first. Then, it is proven that exponential consensus can be achieved in the presence of data rate constraint. Finally, in the third part, the problem of deadline-constrained multi-agent task scheduling and control synthesis is addressed. A dynamic scheduling strategy is proposed and a distributed hybrid control law is designed for each agent that guarantees the completion and deadline satisfaction of each task. The effectiveness of the theoretical results in the thesis is verified by several simulation examples. / <p>QC 20180918</p>

Formation control is a classical problem and has been a prime topic of interest among the scientific community in the past few years. Although a vast amount of literature exists in this field, there are still many open questions that require an in-depth understanding and a new perspective. This thesis contributes towards exploring the wide dimensions of formation control and implementing a formation control scheme for a group of multi-agent systems. These systems are autonomous in nature and are represented by double integrated dynamics. It is assumed that the agents are connected in an undirected graph and use a leader-follower architecture to reach formation when the leading agent is given a velocity that is piecewise constant. A MATLAB code is written for the implementation of formation and the consensus-based control laws are verified. Understanding the effects on formation due to a fixed formation geometry is also observed and reported. Also, a link that describes the functional similarity between desired formation geometry and the Laplacian matrix has been observed. The use of Laplacian matrix in stability analysis of the formation is of special interest.

This thesis explores the possibility of combining a noise-based terrain generator with a multi-agent system-based citygenerator for use in overworld map generation for games.The resulting artifact is a generator capable of creating awide variety of landscapes and populating them with citiesthat take advantage of available space and resources. Thegenerated noise is used as a height map which is colorizedto form the basis of the terrain. City agents traverse the space, looking for an optimal place to settle within their view. Once they find their final position, each city creates a number of building agents based on the nearby resources. The city agents take each other and the terrain into account when deciding where the buildings shall be placed. Then, road agents connectfirst the houses, then the cities together. Lastly, points ofinterests such as dungeons, bandit camps and wizard towers are placed, their final positions determined in a similar fashion to the city agents. The analysis of the results indicate that the generator is capable of producing novel terrain, and cities that adapt somewhat well to their surroundings, but offer little variety in existing features from map to map. In addition, more control is necessary to implement the artifact into adevelopment workflow. Respondents rated the maps produced by the generator lower than a map from an existing game ,converted into a similar format, and on a similar level as another map, also from an existing game.

The main aim of transport stakeholders has always been to transport freight efficiently, as this efficiency contributes to the growth and success of their business. A country like Namibia is no different as the efficiency of transport lies in the effective utilisation of carrier capacity in any direction. Due to the various types of freight, transport operators rarely have the capacity to cover all freight movement requests. This research put the empty runs experienced by most of the Namibian transporters at 33%. Empty runs could however be reduced through collaboration and sharing of capacity among transport stakeholders. Multi-agent systems (MAS) are various individual computer agents that are configured independently to interact with other agents to achieve one goal. These systems have been explored as an approach to achieve collaboration among transporter stakeholders. Taking into consideration the characteristics and requirements of MAS, this research was able to conduct a feasibility of its implementation within Namibia. Concluding with an evaluation of available Multi-agent based systems that could achieve collaboration and reduce empty runs in the Namibian transport environment. / Information Science / M.Tech. (Information Technology)

Thesis (MScEng)--Stellenbosch University, 2013. / ENGLISH ABSTRACT: This thesis documents the research conducted into the control of the feeder subsystem of a Reconfigurable Assembly System (RAS). The research was motivated by a new set of modern manufacturing requirements associated with an aggressive and dynamic global market. The motivation can be more specifically attributed to the need for selective automation, through the installation of reconfigurable systems, in the South African manufacturing industry. The objective of the research was to implement and evaluate Multi-Agent Systems (MASs) and IEC 61499 function block systems as potential control strategies for reconfigurable systems. The control strategies were implemented for the control of the feeder subsystem of an experimental RAS at Stellenbosch University. The subsystem's hardware consisted of a singulation unit with a machine vision camera, part magazines and a six DOF pick-'n-place robot. The structure of the control strategies is based on the ADACOR holonic reference architecture. The mapping of the subsystem holons to the structures of the control strategies is explained. The development and implementation of the control strategies, along with the accompanying lower level software, is described in detail. A system reconfigurability assessment was performed and the results are discussed. The assessment was performed at two levels – the Higher Level Control (HLC) (where the control strategies were implemented) and the low level control and hardware. The assessment was done through four reconfiguration experiments. The evaluation of the HLC was done through both quantitative and qualitative performance measures. The implications of the reconfiguration, involved in each of the respective experiments, on the low level software and hardware are discussed. The experimental results show that agent-based control adds more reconfigurability to the feeder subsystem than IEC 61499 function block control, and that agents have more advantages regarding customizability, convertibility and scalability than IEC 61499 function blocks. Also, the ability of agent-based control to implement reconfiguration changes during subsystem operation makes it more suitable to the case study application. / AFRIKAANSE OPSOMMING: Hierdie tesis dokumenteer die navorsing gedoen in die beheer van die voerder sub-stelsel vir 'n herkonfigureerbare monteringstelsel. Die navorsing was gemotiveer deur „n nuwe stel vereistes vir moderne vervaardiging wat met 'n aggresiewe en dinamiese globale mark geassosieer word. Die motivering kan meer spesifiek toegeskryf word aan die behoefte tot selektiewe outomatisasie, deur middel van die implimentering van herkonfigureerbare stelsels, in the Suid-Afrikaanse vervaardigingsnywerheid. Die doel van die navorsing is om multi-agent stelsels en IEC 61499 funksie-blok stelsels, as potensiële beheerstrategiëe vir herkonfigureerbare stelsels, te implementer en evalueer. Die beheerstrategiëe was geïmplementeer vir die voerder sub-stelsel van „n eksperimentele herkonfigureerbare monteringstelsel by Universiteit Stellenbosch. Die hardeware behels „n skeier-eenheid (singulation unit) met „n masjienvisie kamera, onderdeelmagasyne en „n ses-vryheidsgraad gearktikuleerde optel-en-plaas robot. Die struktuur van die beheerstrategiëe is gebaseer op die ADACOR holoniese verwysingsargitektuur. Die afbeelding van die sub-stelsel holons na die struktuur van die beheerstrategiëe word verduidelik. Die ontwikkeling en implementering van die beheerstrategiëe, asook die gepaardgaande laer-vlak programmatuur, word in detail beskryf. Die stelsel se herkonfigureerbaarheid was geassesseer en die resultate daarvan word bespreek. Die assessering was op twee vlakke gedoen – die hoër-vlak beheer (waar die beheerstrategiëe geimplementeer was) en die lae-vlak beheer en hardeware. Die assessering was gedoen deur middel van vier herkonfigurasie eksperimente. Die hoër-vlak beheer was geëvalueer deur beide kwalitatiewe en kwantitatiewe metings. Die implikasies van die herkonfigurasie, betrokke by die onderskeie eksperimente, op die lae-vlak beheer en hardeware word beskryf. Die eksperimentele resultate wys dat agent-baseerde beheer meer herkonfigureerbaarheid tot die voerder sub-stelsel toevoeg as IEC 61499 funksie-blok beheer. Dit is geïdentifiseer dat agente meer voordele inhou ten opsigte van aanpasbaarheid, skakelbaarheid en skaalbaarheid as IEC funksie-blokke. Agent-baseerde beheer laat ook toe dat herkonfigurasieveranderinge tydens sub-stelsel werking geïmplimenteer kan word – dus is dit meer geskik vir aanwending in die gevallestudie.

Algorithmically designed reward functions can influence groups of learning agents toward measurable desired sequential joint behaviours. Influencing learning agents toward desirable behaviours is non-trivial due to the difficulties of assigning credit for global success to the deserving agents and of inducing coordination. Quantifying joint behaviours lets us identify global success by ranking some behaviours as more desirable than others. We propose a real-valued metric for turn-taking, demonstrating how to measure one sequential joint behaviour. We describe how to identify the presence of turn-taking in simulation results and we calculate the quantity of turn-taking that could be observed between independent random agents. We demonstrate our turn-taking metric by reinterpreting previous work on turn-taking in emergent communication and by analysing a recorded human conversation. Given a metric, we can explore the space of reward functions and identify those reward functions that result in global success in groups of learning agents. We describe 'medium access games' as a model for human and machine communication and we present simulation results for an extensive range of reward functions for pairs of Q-learning agents. We use the Nash equilibria of medium access games to develop predictors for determining which reward functions result in turn-taking. Having demonstrated the predictive power of Nash equilibria for turn-taking in medium access games, we focus on synthesis of reward functions for stochastic games that result in arbitrary desirable Nash equilibria. Our method constructs a reward function such that a particular joint behaviour is the unique Nash equilibrium of a stochastic game, provided that such a reward function exists. This method builds on techniques for designing rewards for Markov decision processes and for normal form games. We explain our reward design methods in detail and formally prove that they are correct.

Les environnements domotiques sont des environnements ubiquitaires dans lesquels des équipements domestiques, disséminés dans une habitation, fournissent des services utilisables à distance au travers d'un réseau. Des systèmes domotiques sont proposés pour permettre aux utilisateurs de contrôler les équipements en fonction de leurs besoins.Idéalement, ces systèmes orchestrent l'exécution des services fournis par les équipements pour réaliser des services complexes. Mieux encore, ces systèmes doivent s'adapter à la variété des environnements en termes d'équipements et des besoins des utilisateurs. Ils doivent également pouvoir s'adapter dynamiquement, si possible de manière autonome, au changement de leur contexte d'exécution (apparition ou disparition d'un équipement, évolution des besoins).Dans cette thèse, nous apportons une réponse à cette problématique avec SAASHA, un système domotique multi-agents à base de composants. La combinaison de ses deux paradigmes permet de gérer l'adaptation à trois niveaux : présentation (interfaces utilisateur),organisation (architecture du système) et comportement (architecture interne des agents).Les agents perçoivent le contexte et ses changements. Les utilisateurs se voient proposer une vue dynamique du contexte leur permettant de définir des scénarios personnalisés sous forme de règles. Les agents se répartissent les rôles pour réaliser les scénarios. Ils modifient dynamiquement leur architecture interne grâce à la génération, au déploiement et à l'assemblage de composants pour se doter de nouveaux comportements de contrôle des équipements et des scénarios. Les agents collaborent ainsi pour exécuter les scénarios. En cas de changement, ces trois niveaux d'adaptation sont mis en oeuvre de manière dynamique et autonome pour maintenir la continuité de service. Un prototype de SAASHA, basé sur les standards industriels UPnP et OSGi, a été développé pour évaluer la faisabilité de notre proposition. / Home automation environments are ubiquitous environments where domestic devices, scattered throughout a home, provide services that can be used remotely over a network. Home automation systems are proposed to enable the users of controlling the devices according to their needs. Ideally, these systems orchestrate the execution of the services provided by the devices to achieve complex services. Even more, these systems must adapt to the variety of environments in terms of devices and users needs. They must also be able to adapt dynamically, if possible in an autonomous manner, to the changes of their execution context (appearance or disappearance of a device, changing needs).In this thesis, we provide an answer to this problematic with SAASHA, a multi-agent home automation system based on components. The combination of these two paradigms enables managing the adaptation on three levels: presentation (user interface), organization (system architecture) and behavior (internal architecture of agents). The agents perceive their context and its changes. The Users are offered a dynamic view of the context allowing them to define custom scenarios as rules. The agents divide the roles among them to realize the scenarios. They modify dynamically their internal architecture throughout the generation, deployment and assembly of components to adopt new device control behaviors and scenarios. The agents collaborate to execute the scenarios. In case of a change, these three levels of adaptation are updated dynamically and autonomously to maintain the service continuity. A SAASHA prototype, based on UPnP and OSGi industry standards, has been developed to assess the feasibility of our proposal.