Model-based design is a powerful design technique for embedded system development. The technique enables virtual prototyping to develop and debug controllers before touching real hardware. There are many tools available covering the distinct steps of the design cycle including modeling, simulation, and implementation. Unfortunately, none of them covers all three steps. This thesis proposes a formalism coupling the model and the implementation of a controller for equation-based simulation tools. The resulting formalism translates defined controller models to platform specific code using a defined set of syntax. A case study of a line-following robot has been developed to illustrate the feasibility of the approach. The prototype has been tested and evaluated using a sequence of test scenarios of increasing difficulty. The final experiments suggest that the behaviors of both modeled and generated controllers are similar. The thesis concludes that the approach of model-implementation coupling of controllers in the simplest form is feasible for equation-based tools. This allows it to conduct the whole model-based design cycle within a single environment.

The increasing penetration of renewable energy resources within the Great Britain (GB) transmission system has created much greater variability of power flows within the transmission network. Consequently, modern transmission networks are presented with an ever increasing range of operating conditions. As a result, decision making in the Electricity National Control Centre (ENCC) of the GB electrical power transmission system is becoming more complex and control room actions are required for reducing timescales in the future so as to enable optimum operation of the system. To maximise utilisation of the electricity transmission system there is a requirement for fast transient and dynamic stability control. In this regard, GB electrical power transmissions system reinforcement using new technology, such as High Voltage Direct Current (HVDC) links and Thyristor-Controlled Series Compensation (TCSC), is planned to come into operation. The research aim of this PhD thesis is to fully investigate the effects of HVDC lines on power system small-disturbance stability in the presence of operational uncertainties. The main research outcome is the comprehensive probabilistic assessment of the stability improvements that can be achieved through the use of supplementary damping control when applied to HVDC systems. In this thesis, two control schemes for small-signal dynamic stability enhancement of an embedded HVDC link are proposed: Modal Linear Quadratic Gaussian (MLQG) controller and Model Predictive Controller (MPC). Following these studies, probabilistic methodologies are developed in order to test of the robustness of HVDC based damping controllers, which involves using classification techniques to identify possible mitigation options for power system operators. The Monte Carlo (MC) and Point Estimated Method (PEM) are developed in order to identify the statistical distributions of critical modes of a power system in the presence of uncertainties. In addition, eigenvalue sensitivity analysis is devised and demonstrated to ensure accurate results when the PEM is used with test systems. Finally, the concepts and techniques introduced in the thesis are combined to investigate robustness for the widely adopted MLQG controller and the recently introduced MPC, which are designed as the supplementary controls of an embedded HVDC link for damping inter-area oscillations. Power system controllers are designed using a linearised model of the system and tuned for a nominal operating point. The assumption is made that the system will be operating within an acceptable proximity range of its nominal operating condition and that the uncertainty created by changes within each operating point can possibly have an adverse effect on the controller’s performance.

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Práce pojímá controlling jako nástroj řízení, jenž podporuje podnikové rozhodování. Zabývá se činnostmi controllingu, které jsou realizovány v rámci firmy Stavby silnic a železnic, a. s. Diplomová práce shrnuje teoretické poznatky o controllingu, ukazuje provádění controllingu na praktickém příkladu firmy Stavby silnic a železnic, a. s. a navrhuje doporučení či možností rozvoje systému controllingu na úrovni závodu.

The present dissertation is thematically focussed on issues relevant to the controlling of a company, particularly those relevant to top-level management. The first part of this work presents the theoretical assumptions of controlling, as applied to the company ČD - Telematika a.s. Based on an assessment of knowledge identified from both theory and praxis, some recommendations regarding the streamlining and the efficient functioning of the controlling of the company are presented at the end of this dissertation. Internal documents from this company, based on real data for 2012, have been used in this dissertation.

Magnetorheological (MR) dampers are adaptive devices whose properties can be adjusted through the application of a controlled voltage signal. A semi-active suspension system incorporating MR dampers combines the advantages of both active and passive suspensions. For this reason, there has been a continuous effort to develop control algorithms for MR-damped vehicle suspension systems to meet the requirements of the automotive industry. The overall aims of this thesis are twofold: (i) The investigation of non-parametric techniques for the identification of the nonlinear dynamics of an MR damper. (ii) The implementation of these techniques in the investigation of MR damper control of a vehicle suspension system that makes minimal use of sensors, thereby reducing the implementation cost and increasing system reliability. The novel contributions of this thesis can be listed as follows: 1- Nonparametric identification modelling of an MR damper using Chebyshev polynomials to identify the damping force from both simulated and experimental data. 2- The neural network identification of both the direct and inverse dynamics of an MR damper through an experimental procedure. 3- The experimental evaluation of a neural network MR damper controller relative to previously proposed controllers. 4- The application of the neural-based damper controller trained through experimental data to a semi-active vehicle suspension system. 5- The development and evaluation of an improved control strategy for a semi-active car seat suspension system using an MR damper. Simulated and experimental validation data tests show that Chebyshev polynomials can be used to identify the damper force as an approximate function of the displacement, velocity and input voltage. Feed-forward and recurrent neural networks are used to model both the direct and inverse dynamics of MR dampers. It is shown that these neural networks are superior to Chebyshev polynomials and can reliably represent both the direct and inverse dynamic behaviours of MR dampers. The neural network models are shown to be reasonably robust against significant temperature variation. Experimental tests show that an MR damper controller based a recurrent neural network (RNN) model of its inverse dynamics is superior to conventional controllers in achieving a desired damping force, apart from being more cost-effective. This is confirmed by introducing such a controller into a semi-active suspension, in conjunction with an overall system controller based on the sliding mode control algorithm. Control performance criteria are evaluated in the time and frequency domains in order to quantify the suspension effectiveness under bump and random road excitations. A study using the modified Bouc-Wen model for the MR damper, and another study using an actual damper fitted in a hardware-in-the-loop- simulation (HILS), both show that the inverse RNN damper controller potentially gives significantly superior ride comfort and vehicle stability. It is also shown that a similar control strategy is highly effective when used for a semi-active car seat suspension system incorporating an MR damper.

This diploma thesis is concerned with the analysis of reporting activities in the company PBS Turbo s.r.o. The first part explains the concept of reporting as one of the basic functions of controlling. Additionally there is presented the theoretical knowledge of reporting. The second part focuses on an analysis of the current situation in reporting in the selected company. In the last part are detailed recommendations to make the process of reporting more effective.

Thanks to the Software-Defined Networking (SDN) paradigm, which segregates the control and data layers of traditional networks, large and scalable networks can now be dynamically configured and managed. It is a game-changing networking technology that provides increased flexibility and scalability through centralized management. The Controller Placement Problem (CPP), however, poses a crucial problem in SDN because it directly impacts the efficiency and performance of the network. The CPP attempts to determine the most ideal number of controllers for any network and their corresponding relative positioning. This is to generally minimize communication delays between switches and controllers and maintain network reliability and resilience. In this thesis, we present a modified Genetic Algorithm (GA) technique to solve the CPP efficiently. Our approach makes use the GA’s capabilities to obtain the best controller placement correlation based on important factors such as network delay, reliability and availability. We further optimize the process by means of certain deduced constraints to allow faster convergence. In this study, our primary objective is to optimize the control plane design by identifying the optimal controller placement, which minimizes delay and significantly improves both the switch-to-controller and controller-to-controller link availability. We introduce an advanced genetic algorithm methodology and showcase a precise technique for optimizing the inherent availability constraints. To evaluate the trade-offs between the deployment of controllers and the associated costs of enhancing particular node link availabilities, we performed computational experiments on three distinct networks of varying sizes. Overall, our work contributes to the growth trajectory of SDN research by offering a novel GA-based resolution to the controller placement problem that can improve network performance and dependability.

Controllern är en komplex yrkesroll som har påverkats mycket av digitaliseringen. Tidigare forskning har försökt konkretisera controllerns arbetsroll och arbetsuppgifter men ett kunskapsglapp har identifierats baserat på digitaliseringens påverkan på yrkesrollen. Syftet med detta arbete är därför att öka förståelsen kring hur controllerns roll relaterar till dess arbetsuppgifter i en digitaliserad miljö. Arbetet sammanställer en teoretisk referensram samt en empirisk del som baseras på en kvalitativ undersökning där semistrukturerade intervjuer har använts. Inkluderat i den teoretiska referensramen som presenteras är Nilsson, Olve & Parments modell över controllerns arbetsuppgifter, denna ämnar arbetet komplettera med en ny modell. Den kompletterande modellen framställs baserat på fyra nyckelbegrepp som har identifierats i den teoretiska referensramen. Nyckelbegreppen är mjuka värden, hårda värden, medarbetsinriktad interaktion och ledningsinriktad interaktion. Modellen har sammanställts för att besvara frågeställningen och ge en ökad förståelse för hur controllers olika roller relaterar till olika arbetsuppgifter i en digitaliserad miljö.