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Adaptive controllers with principles of artificial intelligence and its comparison with classical identifications methods
Vaňková, Tereza ; Dokoupil, Jakub (referee) ; Pivoňka, Petr (advisor)
Master’s thesis is focused on the adaptive controllers. The first theoretic part mainly describes the parametric identification, which belongs to the most important part of the adaptive controller’s structure. Classical identification methods (the recursive least squares methods) are firstly mentioned and afterwards the identification methods based on the neural network (the Marquardt-Levenberg algorithm and the new identification algorithm NIA inspired by the neural networks) are described. At the conclusion of the theoretic part there are mentioned the algorithm of the adaptive controller’s tuning which uses the identification parameters (the modified Z-N method) and the tested types of adaptive controllers. Particular results, which were found out by verifying of the adaptive controllers on the simulation and real models, are contained in second, the practical, part of the thesis. Finally, achieved results are compared with the classical discrete PID controller and with the adaptive controller of the B&R company.
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Industrial PID controller with autotuning and visualisation
Vávra, Pavel ; Dvořáček, Martin (referee) ; Pivoňka, Petr (advisor)
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.
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Adaptive controllers with principles of artificial intelligence and its comparison with classical identifications methods
Vaňková, Tereza ; Dokoupil, Jakub (referee) ; Pivoňka, Petr (advisor)
Master’s thesis is focused on the adaptive controllers. The first theoretic part mainly describes the parametric identification, which belongs to the most important part of the adaptive controller’s structure. Classical identification methods (the recursive least squares methods) are firstly mentioned and afterwards the identification methods based on the neural network (the Marquardt-Levenberg algorithm and the new identification algorithm NIA inspired by the neural networks) are described. At the conclusion of the theoretic part there are mentioned the algorithm of the adaptive controller’s tuning which uses the identification parameters (the modified Z-N method) and the tested types of adaptive controllers. Particular results, which were found out by verifying of the adaptive controllers on the simulation and real models, are contained in second, the practical, part of the thesis. Finally, achieved results are compared with the classical discrete PID controller and with the adaptive controller of the B&R company.
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Industrial PID controller with autotuning and visualisation
Vávra, Pavel ; Dvořáček, Martin (referee) ; Pivoňka, Petr (advisor)
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.
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