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.

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.

The main fokus of this D thesis consists in the creating of horizontal points in Lešná village that is closed to Valašské Meziříčí, part Vysoká. Sixty five points of horizontal control (PPBP) were located and set in Vysoká. The network adjustment was done with the help of the method of lest squares and coordinates were counted with the G-NET/Mini programme.

Tato diplomová práce nastiňuje teoretické základy potřebné pro návrh algoritmu rekurzivní metody nejmenších čtverců a následně jeho aplikaci na experimentální data naměřená při testovacím manévru uskutečněném v roce 2001. Analyzována byla příčná dynamika jednostopého rovinného modelu vozidla. Práce také obsahuje srovnání výsledků získaných jednak rekurzivním algoritmem a dále i algoritmem Kalmanova filtru.

The main subject of the diploma thesis is a market price modeling by real estates. As a tool for modeling, is used a multiple linear regression. As starting points, are used an econometrical theory and knowledge about real estate valuation. The main goal is to find optimal model for best capture in the time and place.

Simultaneous evaluation of the whole set of the model parameters of different orders together with an ability to track unmodeled dynamics are desired features in the tasks of parameter estimation. A technique handling with the factors produced by an augmented covariance (ACM) or information (AIM) matrices is considered to be an appropriate tool for designing multiple model estimation. This is where the name augmented identification (AI) by using the least-squares method was taken. The method AI attains numerical stability of the calculation of the conventional least squares method while in the same time, fully extracts information contained in the observation. In order to track time varying parameters can be found that all the information pertinent to recursive identification and thus to data driven forgetting is concentrated in ACM as well as in AIM. In this thesis will be introduced how to selective forgetting to ACM should be applied in an effective way. It means forget only a portion of accumulated information which will be further modified by the newest data included in the regressor. In the estimation problems the knowledge of the inner states of the identified system is often required. Because the augmented identification belongs within the class so called prediction error method (PEM), some rational requirements can be deduced. As a result, state filter should constitute optimization procedure minimizing the predicted error of given state space model representation with respect to the vector of states. The proposed scheme will considerably extend the family of algorithms based on processing of ACM (AIM) about augmented filtering (AF). This all will establish a comprehensive concept of parametric estimation that compared with conventional approaches is characterized by versatility, low demands on a priori process information and by excellent numerical properties (robust against overparametrization, capable solving the multiple model problem).

Tato práce se zabývá návrhem adaptivního řídícího algortitmu pro konkrétní třídu elektromechanických aktuátorů, založeného na principu dopředného řízení pomocí inverzního dynamického modelu. Adaptibilita řízení spočívá v mechanismu získání inverzního dynamického modelu. Tato práce se zaměřuje na jeho online aproximaci pomocí lokálních aproximačních metod. Výstupem práce je shrnutí analýzy, simulačního testování a reálných experimentů, které testovaly možnosti praktického využití lokálných aproximačních metod pro účely adaptivního řízení v reálném prostředí.