A PID controller and a Fuzzy Logic controller were designed to balance an inverted pendulum system. Both controllers were implemented in a Digital Signal Processor (DSP). Measurements of the angular position of the pendulum (feedback signal) were taken from a precision potentiometer and transformed into digital by an Analog Interface Board (AlB) to be processed by the DSP. The DSP generated the digital control signal that was converted into analog by the AlB and then filtered and amplified to drive a DC motor. The DC motor provided the control force for the mobil base where the inverted pendulum was mounted. The PID controller was designed to move an unstable pole of the system from the tight side of the s-plane into the left side of the s-plane to provide stability and fast response. The Fuzzy Logic controller was designed using thirteen control rules that were generated using human intuition. It was found that the Fuzzy Logic controller required a considerably larger amount of memory than the PID controller. In general, the Fuzzy Logic controller performed better than the PID controller. It was concluded that nonlinearities present in some components of the system caused the PID controller not to perform as well. It was also found that the Fuzzy Logic controller was less sensitive to these nonlinearities, resulting in a better control of the inverted pendulum.

This thesis tries to research the term “robust controllers”. Its aim is to compare the robustness of discrete PID controllers (Discrete Equivalent Continuous Controller, Discrete Impulse Area Invariant, Takahashi, Feed-Forward), adaptive discrete PID controllers (Discrete Impulse Area Invariant, Takahashi, Feed-Forward), optimal controllers (quadratic optimal), and adaptive optimal controllers (quadratic optimal) on chosen transfer functions. Its aim is also to check the influence of A/D and D/A converters. The aims to obtain are demarked at the beginning of the text and also there is an explanation of the term “robustness.” Later on there is a description and an approximation to each of the chosen kinds of controllers and the identification methods used in the thesis (for adaptive controllers the method of recursive least-squares was used). The Kharitonov's Theorem are made on the chosen transfer function. Next there is a description of the methods with which the robustness of the controllers will be tested. The first method is the integral criteria, particular ITAE criterion and quadratic criterion. The second one is the analysis of the generalised circle criterion. Furthermore there are various displays of the results obtained and their corresponding comments. The results obtained are graphically displayed and by means of these schemes the particular types of controllers are compared. All of the simulations and results obtained were acquired through the use of the program MATLAB- Simulink. In the end of the thesis there is an overall evaluation.

The diploma thesis deals with the self-tuning PSD controllers. The parameters of the model are obtained by a non-recurring method of least squares. With the assistance of the Matlab/Simulink programme, the individual processes of the PSD controller are compared on a second order system. In the thesis, a simulation of the self-tuning cascade control of PMSM‘s current and speed loop is created. The following part of the thesis covers the implementation of individual algorithms on the dSPACE platform for the real PMSM.

Le contexte de l'évolution des infrastructures des opérateurs de télécommunications vers les paradigmes SDN et NFV nécessite de lever différents verrous techniques, liés d'une part à la centralisation des fonctions de contrôle, d'autre part aux contraintes d'approches qui s'inspirent directement du Cloud Computing. Dans cette thèse, nous avons abordés deux problématiques. Dans la première nous cherchons à définir une architecture SDN plus adaptée et performante par rapport aux besoins des opérateurs. Pour cela, nous avons proposé un plan de contrôle SDN distribué et flexible visant à dépasser les limites du protocole OpenFlow centralisé ainsi que les contraintes de la virtualisation des fonctions réseaux. L'architecture proposée permet la composition, puis la validation et le déploiement différenciés de services réseaux composables et reconfigurables dynamiquement en prenant en compte les SLA associés aux services. Nous avons illustré certaines propriétés de cette architecture, distribution, composition, dynamicité dans une preuve de concepts. Dans la deuxième, pour réaliser les SLA attendus, nous cherchons à optimiser le placement des services réseaux dans cette infrastructure. Nous avons d'abord traité la problématique du placement de contrôleurs SDN en optimisant des métriques de latence, de charge et de fiabilité, puis de manière plus générale le placement de chaînes de fonctions réseaux virtualisées. Nous avons démontré pour cela les potentialités et les performances des algorithmes évolutionnaires pour tenter de proposer un outil de résolution générique de placement de fonctions réseaux. / The evolution of telecommunications operators’ infrastructures towards the SDN and NFV paradigms requires to surmount various technical barriers. On one hand, it is necessary to deal with the centralization of control functions, and on the other hand with the constraints of approaches coming directly from Cloud Computing. In this thesis, we addressed two issues. Firstly, we tried to define a SDN architecture more suited to the requirement of operators. For this purpose, we proposed a distributed and flexible SDN control plane to overcome the limitations of the centralized OpenFlow protocol, as well as the constraints of network function virtualization. The proposed architecture allows for the differentiated composition, validation and deployment of dynamically reconfigurable network services, taking into account the SLAs associated with the services. We have illustrated some of its characteristics, namely, distribution, composition, dynamicity in a proof of concept. Secondly, to achieve the expected SLAs, we try to optimize the placement of network services in this infrastructure. We first dealt with the issue of SDN controllers placement seeking for the optimization of latency, load and reliability metrics. Then, we considered the placement of virtualized network functions chains. We have therefore demonstrated the potentialities and performances of evolutionary algorithms with the perspective to propose a generic resolution tool for placement of network functions.

This paper presents renewable energy, power electronics, and distributed generators. The focus is on wind farm generator, photovoltaic cell, and battery bank system. Power Conditioning system improves the performance of a power system. Apart from the benefits of converting between DC/AC, there is adequate control of real power and additional control of economic reactive power. This is possible because of multiple sources in the system. This project throws light on the basic principle of power system conditioning, its operation and control, and the economic studies.

With the ongoing trend in moving the upper levels of the automation hierarchy to the cloud, there has been investigation into supplying industrial automation as a cloud based service. There are many practical considerations which pose limitations on the feasibility of the idea. This research investigates some of the requirements which would be needed to implement a platform which would facilitate competition between different controllers which would compete to control a process in real-time. This work considers only the issues relating to implementation of the philosophy from a control theoretic perspective, issues relating to hardware/communications infrastructure and cyber security are beyond the scope of this work. A platform is formulated and all the relevant control requirements of the system are discussed. It is found that in order for such a platform to determine the behaviour of a controller, it would need to simulate the controller on a model of the process over an extended period of time. This would require a measure of the disturbance to be available, or at least an estimate thereof. This therefore increases the complexity of the platform. The practicality of implementing such a platform is discussed in terms of system identification and model/controller maintenance. A model of the surge tank from SibanyeStillwater’s Platinum bulk tailings treatment (BTT) plant, the aim of which is to keep the density of the tank outflow constant while maintaining a steady tank level, was derived, linearised and an input-output controllability analysis performed on the model. Six controllers were developed for the process, including four conventional feedback controllers (decentralised PI, inverse, modified inverse and H¥) and two Model Predictive Controllers (MPC) (one linear and another nonlinear). It was shown that both the inverse based and H¥ controllers fail to control the tank level to set-point in the event of an unmeasured disturbance. The competing concept was successfully illustrated on this process with the linear MPC controller being the most often selected controller, and the overall performance of the plant substantially improved by having access to more advanced control techniques, which is facilitated by the proposed platform. A first appendix presents an investigation into a previously proposed switching philosophy [15] in terms of its ability to determine the best controller, as well as the stability of the switching scheme. It is found that this philosophy cannot provide an accurate measure of controller performance owing to the use of one step ahead predictions to analyse controller behaviour. Owing to this, the philosophy can select an unstable controller when there is a stable, well tuned controller competing to control the process. A second appendix shows that there are cases where overall system performance can be improved through the use of the proposed platform. In the presence of constraints on the rate of change of the inputs, a more aggressive controller is shown to be selected so long as the disturbance or reference changes do not cause the controller to violate these input constraints. This means that switching back to a less aggressive controller is necessary in the event that the controller attempts to violate these constraints. This is demonstrated on a simple first order plant as well as the surge tank process. Overall it is concluded that, while there are practical issues surrounding plant and system identification and model/controller maintenance, it would be possible to implement such a platform which would allow a given plant access to advanced process control solutions without the need for procuring the services of a large vendor. / Dissertation (MEng)--University of Pretoria, 2020. / Electrical, Electronic and Computer Engineering / MEng / Unrestricted

The operation and control of the power system in an efficient way is important in order to keep the system secure, reliable and economical. With advancements in smart grid, several new algorithms have been developed for improved operation and control. These algorithms need to be extensively tested and validated in real time before applying to the real electric power grid. This work focuses on the development of a real time test bed for testing and validating power system control algorithms, hardware devices and cyber security vulnerability. The test bed developed utilizes several hardware components including relays, phasor measurement units, phasor data concentrator, programmable logic controllers and several software tools. Current work also integrates historian for power system monitoring and data archiving. Finally, two different power system test cases are simulated to demonstrate the applications of developed test bed. The developed test bed can also be used for power system education.

Multi-robot networks are used in a variety of military and civilian applications such as harbour protection, perimeter surveillance, search & rescue missions and cooperative estimation, among others. In order to develop functional multi-robot networks to achieve these tasks, a combination of theoretical and experimental work is required. Theoretical research aims to model the open and closed loop dynamics of multi-robot systems and to develop corresponding control algorithms for tackling the previously mentioned tasks. Experimental work focuses on the hardware or simulated implementations to test and evaluate the algorithms’ performance, and eventually inform refinements of theoretical algorithms to adapt to hardware imposed intrinsic constraints. As theoretical and algorithmic research in the field of multi-robot networks matures, a need for experimental validation of a variety of sophisticated algorithmic tools becomes apparent, with the two aspects co-developing to inform theoretical refinements that account for hardware induced constraints, and possible technological advances suggested by theoretical predictions. This thesis contributes a design for a hardware test platform for evaluating and implementing algorithms in the field of multi-robot networks. The test platform design implements an off the market robot solution for the robotic agents, discussing various additional embedded frameworks that allow for capabilities such as indoor agent localization, inter-agent wireless communication and agent locomotion, with the goal of understanding if a combination of existing market and academic technologies can be used to develop a cost effective hardware multi-agent test platform. The proposed hardware design is then validated on previously developed multiagent area coverage control and optimization algorithms. More specifically, the hardware test platform is used to implement various optimal coverage problems with time invariant risk density distributions. Both uniform and nonuniform risk density distribution scenarios are considered. These experimental results are compared with simulations to assess if the proposed hardware test platform design can plausibly reproduce behaviours that are consistent with theoretical predictions of area coverage control algorithms. Future work will include the extension of the testing capabilities of this test platform to a larger class of multi-agent control algorithms.

No description available.

<p>This thesis aims to design a controller to apply medication to patients with hypothyroidism, a disease that occurs due to the underacting thyroid gland. The body cannot produce sufficient thyroid hormones, which leads to an increase in the production of hormones in the pituitary gland. The thyroid malfunctioning could lead to other associated conditions like nausea, fatigue, heart conditions, higher cholesterol, and elevated blood pressure. Thus, it is essential to ensure that the levels of thyroid hormones, Triiodothyronine (T3) and Thyroxine (T4), are healthy. The production of these hormones is governed by the hypothalamus-pituitary-thyroid (HPT) axis, a part of the endocrine system. This illness cannot be cured but can be regulated entirely through medication. The standard practice to control hypothyroidism in patients is to prescribe a constant daily dosage of synthetic T4 (i.e., levothyroxine) and, in some cases, an additional dose of synthetic T3 (i.e., Liothyronine). In this thesis, simulation studies are performed where two patients with varying levels of hypothyroidism are prescribed constant doses of synthetic hormones. The medications initially help the patients but are unsuccessful in maintaining healthy ranges. Using model predictive control, an observer-controller-based compensator is proposed to prescribe varying medication doses as inputs based on the patient's requirement. The inputs are quantized to be practically implemented in a real patient scenario. This compensator successfully improves the patient's hormone levels toward healthy values and ensures that the hormone trajectories follow the body's circadian rhythm.  </p>