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Quadratically Optimal Augmented Identification and Filtration
Dokoupil, Jakub ; Bobál, Vladimír (referee) ; Dostál,, Petr (referee) ; Pivoňka, Petr (advisor)
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).
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Control integrated system for workpiece recognition
Vostřel, Tomáš ; Blaha, Petr (referee) ; Pivoňka, Petr (advisor)
The diploma thesis deals with the usage of integrated machine vision by B&R, Smart Sensor, for metal rectangular-shaped workpiece recognition and position determinition. The description of the usage of machine vision in the industry is made, the solution concept is created and the program and the user visualisation implemented. The main outcome of this work is the VITemplate library which can be used in combination with the model-based Blob analysis implemented in Smart Sensor to control the robotic arm to successfully grab all the workpieces on the belt.
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Adaptive controllers for systems with time delay and its comparison with classical controllers.
Krykorka, Daniel ; Burlak, Vladimír (referee) ; Pivoňka, Petr (advisor)
Master thesis is focused on the philosophy of design adaptive controller. In the theoretic part are described parts of the adaptive controller, which belongs parts as online identification by recursive least-squares method and PSD controller, which can set its parameters according to identified system (use Z-N method). The part of control system with transport delay is situated at the conclusion of the theoretic part, there are focused on Smith predictor. Practical part is focused on verification of all algorithms, which was performed on models and real systems.
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Temperature controller of microwave reactor
Pokorný, Ondřej ; Chomát, Luděk (referee) ; Pivoňka, Petr (advisor)
Simple low-cost temperature feedback control loop was created, using personal computer as control and data acquisition element. It controlled the temperature inside mircowave pressure reactor. Medium in reactor tank (volume about 600 ml) was calorified by 1,8 kW magnetron, which power was driven by PSD controller. The PC- process interface was made by USB data acquisition modul UD128A8D. The utility program was written. It implemented PSD controller and data acquisition function. Furhtermore it implemented interface which enabled user to set the technological curve (time-temperature relation). The protocol of experiment was automatically stored to Micosoft Excel file before the program’s termination.
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Industrial PID controller with autotuning and visualisation
Prudký, Miroslav ; Chomát, Luděk (referee) ; Pivoňka, Petr (advisor)
The objective of the thesis is to create software, which implements industrial PID controller enabling smooth switch-over and automatic tuning of parameters. The next objective is to create visualization for this controller. Whole controller have to be implemented into PLC Power Panel (B&R company). At the beginning of the thesis there is theoretical description of all implemented algorithms (discrete control algorithms derived from PID, smooth switch-over, antiwindup, identification algorithms). In the following there is designed program structure, which is state machine-shaped. All algorithms are implemented in ANSI C at first as s-function for Matlab/Simulink program, which enables to simulate and verify the controller. Implementation of controller into PLC Power Panel through the use of Automation Studio program from B&R company is described in the next part. Visualization is created in the same program. Simulations and verifications on mathematical and physical model demonstrates functionality of implemented algorithms, but also points out some problems associated with the use of identification algorithms in real world (noise, quantization in A/D and D/A converter).
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Model robotic table soccer
Bubeník, Ľubomír ; Dokoupil, Jakub (referee) ; Pivoňka, Petr (advisor)
This thesis deals with design of lighting scenes for the robotic table football. It consists mainly of analysis of what are the lighting options and selecting the most appropriate. It also deals with creating algorithm that can detect the position of the ball at the board of table football with great reliability and with approaching to real time. Thesis also includes data processing from the camera in the system PLC.
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Modeling of system motors with flexible component
Lebeda, Aleš ; Dvořáček, Martin (referee) ; Pivoňka, Petr (advisor)
This thesis deals with problem of experimental identification using principles of artificial intelligence and development of nonlinear models. It shows how to estimate parameters of nonlinear models and it compares different types of nonlinear models based on analytical analysis which were developed from measured data in simulation and real system motors with flexible component.
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Adaptive Controllers with Elements of Artificial Intelligence
Šulová, Markéta ; Šeda, Miloš (referee) ; Bobál, Vladimír (referee) ; Pivoňka, Petr (advisor)
The aim of the thesis is to improve the control quality of the adaptive systems (Self Tuning Controllers). The thesis mainly deals with problematical identification part of the adaptive system. This part demonstrates a weak point for existing adaptive systems. Paradoxically, the quality of the adaptive system depends mainly on the identification part because on the basis of the process model obtained by identification are worked out parameters of a control part, afterwards the control action plan is established. Knowledge of the modern control methods is used and a new identification algorithm for closed loop identification is proposed. This simple, fast and efficient algorithm overcomes all disadvantages of current classical identification methods based on least mean-square algorithms. The possibility of the choice of a short sample time, one tuning parameter ability to adjust the control process, the ability to identify processes in real use belong to its main goals. This algorithm was built in the adaptive system and then it was tested on a set of simulation and real models with surprisingly excellent results. The successful implementation of the algorithm into the programmable logic controller was also realized. One part of the thesis introduces a new universal graphics environment for testing and verifying control algorithms.
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