Diploma thesis describes the measurement and evaluation of displacements and deformations of the wooden roof structure of the aquapark hall in Brno – Kohoutovice. Part of the work is devoted to the preparation and testing of used devices and tools. The main part of the work consists of performing one stage of measurement using the polar method and the laser scanning method. The polar method measurement is compared with the results of the polar method of the previous stage. The next part of the work deals with the comparison of the polar method and the laser scanning method measured in the last stage. The results achieved are interpreted in the final part of the work.

The master’s thesis deals with method of adaptive control of electrical drives. It aims at control of DC motor with using self tunning controller (STC) and gain-schedulink in simulative enviroment of MATLAB. The first part of the thesis deals with of basic methods adaptive control of electrical drives and with of basic identification methods, computation of controller parameters and control laws of controllers. The second part of the thesis is aimed at applying adaptive controllers to mathematical model of controlled system. Include monitoring parameters of identification The thesis contains originate programs include source files.

The diploma thesis is focused on an adaptive control, especially in a self-tuning controller area. The thesis is divided into two main parts. The first part deals with identification methods of the adaptive control. The recursive least squares algorithm and the neural network method are the most popular identification methods. These methods are contrasted and the identification quality evaluation is done. The second part compares various types of the adaptive controllers with a non-adjustable PSD controller. The adaptive controllers are investigated from the various identification method point of view. The user graphic interface was realized for the identification and regulatory part. The time behavior of system responses after incoming disturbance and dynamic process changes during simulation systems control is compared with a physical model connected to B&R PLC. The comparison is done with the application of Matlab/Simulink program.

This master's thesis considers adaptive optimal controllers. It shows principles of optimal controllers, recursive identification using least-mean squares method and identification based on neural network.

This thesis deals with implementation of industrial used controlling block into Power Panel equipment of B&R in integrated development environment Automation Studio 3.0.71. It is PID controller with autotuner and visualization, which allowed bumpless transfer among controlling algorithms and manual control. PID and I-PD controllers with filtering of derivative action and dynamic antiwindup were implemented. Parameters of PID controller is possible to tune with the aid of ultimate gain and ultimate period according rules of Ziegler-Nichols. Ultimate parameters of controlled plant is possible to acquire with the aid of two identification methods, recursive least squares method and relay feedback. Recursive least squares method was implemented with directional forgetting. For relay feedback were used two types of relays: ideal and saturation relay for improving accuracy of searched ultimate values. The whole solution is programmed in ANSI C which Automation Studio supports. Created controller is control with the aid of touchscreen which is integrated in Power Panel. Trends of process values are viewed on the screen too. For comparison adaptive controller by B&R was implemented. This contoller is standardly supplied with Automation Studio in LoopConR library. All created algorithms were first validated on mathematical model of plant and then on real model in laboratory. The first part of thesis deals with theoretic analysis of used methods. The practical realization is described in the second part of this diploma thesis.

Tato práce je psaná v angličtině a je zaměřená na problematiku ekvalizace v digitálních komunikačních systémech. Teoretická část zahrnuje stručné pozorování různých způsobů návrhu ekvalizérů. Praktická část se zabývá implementací nejčastěji používaných ekvalizérů a s jejich adaptačními algoritmy. Cílem praktické části je porovnat jejich charakteristiky a odhalit činitele, které ovlivňují kvalitu ekvalizace. V rámci problematiky ekvalizace jsou prozkoumány tři typy ekvalizérů. Lineární ekvalizér, ekvalizér se zpětnou vazbou a ML (Maximum likelihood) ekvalizér. Každý ekvalizér byl testován na modelu, který simuloval reálnou přenosovou soustavu s komplexním zkreslením, která je složena z útlumu, mezisymbolové interference a aditivního šumu. Na základě implenentace byli určeny charakteristiky ekvalizérů a stanoveno že optimální výkon má ML ekvalizér. Adaptační algoritmy hrají významnou roli ve výkonnosti všech zmíněných ekvalizérů. V práci je nastudována skupina stochastických algoritmů jako algoritmus nejmenších čtverců(LMS), Normalizovaný LMS, Variable step-size LMS a algoritmus RLS jako zástupce deterministického přístupu. Bylo zjištěno, že RLS konverguje mnohem rychleji, než algoritmy založené na LMS. Byly nastudovány činitele, které ovlivnili výkon popisovaných algoritmů. Jedním z důležitých činitelů, který ovlivňuje rychlost konvergence a stabilitu algoritmů LMS je parametr velikosti kroku. Dalším velmi důležitým faktorem je výběr trénovací sekvence. Bylo zjištěno, že velkou nevýhodou algoritmů založených na LMS v porovnání s RLS algoritmy je, že kvalita ekvalizace je velmi závislá na spektrální výkonové hustotě a a trénovací sekvenci.

The electrical motors parameters identification is solved in this master’s thesis using subspace based methods. Electrical motors are simulated in Matlab/Simulink interactive environment, specifically permanent magnet DC motor and permanent magnet synchronous motor. Identification is developed in Matlab interactive environment. Different types of subspace algorithms are used for the estimation of parameters. Results of subspace parameters estimation are compared with least squares parameters estimation. The thesis describes subspace method, types of subspace algorithms, used electrical motors, nonlinear approach of identification and comparation of parameters identification.

This master‘s thesis deals with the design of modern process control algorithms suitable for SISO industrial control equipments. In this thesis the analysis of the controller design methodology using Mixed-sensitivity function is described. This method consists in shaping frequency characteristics of the sensitivity function and complementary sensitivity fiction using the weighting functions. The proposed H controllers are compared with the classical structure of a discrete PID controller with filtered derivative part. The proposed controllers are compared in terms of robustness, performance, complexity of the design and requirements necessary for their practical application (anti-windup, smooth switchover). Robustness of the controller is evaluated on the basis of modulus stability margin. Estimation of model´s parameters is solved least-square method. The proposed control system consists of an industrial PC and Automation Panel from the company B&R, decentralized system I/O and the real plant. Visualization for control workplace was created in the program Automation studio. This visualization is used to the easy transfer of information from a controlled process.

This final thesis deals with adaptive control of small brewery. Contains a short description of brewing technology and adaptive control. Includes design of small brawery and control system based on STM32F407 Cortex-M4 microcontroller. For online identification is used Recursive Least Squares Method. The controller function perform a modified PSD controller with filtered derivative component, reducing the first overshot and dynamic antiwindup. The proposed adaptive controller is implemented into microcontroller. Created device i used for semi-automatic beer production.

The goal of this thesis was to create a mathematical model of a steam turbine based on the data acquired by measurement, and to verify its behaviour. The first part contains research, which is supposed to introduce basic principles of the steam turbine and description of important construction parts and the possibilities of control. The second part describes the experimental identification method of least squares, used for the calculation of an ARX model of the steam turbine. Finally, the last part focuses on the program environment used for creation of the mathematical model and explanation of measured data analysis process. Furthermore this segment describes the created simulation program as well as a visualisation of the dynamic processes in the steam turbine, including the design of control.