Fakulta elektrotechniky a informatiky / Faculty of Electrical Engineering and Informatics
Stálý URI pro tuto komunituhttps://hdl.handle.net/10195/3847
Práce obhájené před rokem 2008 jsou uloženy pouze v kolekci Vysokoškolské kvalifikační práce
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Článekpeer-reviewedpostprint Omezený přístup Generalized first-principle model of magnetic levitation(2023) Dušek, František; Tuček, Jiří; Novotný, Aleš; Honc, DanielSince its first demonstration more than a half century ago, magnetic levitation (MagLev) has gained eminent scientific attention from both the fundamental and applied points of view. In essence, MagLev shows highly nonlinear dynamics, described with nonlinear differential equations. Thus, in order to exploit the MagLev phenomenon, both mathematical models and control algorithms must be constructed. Frequently authors use simplifications of the model, and in doing so, limit the application of the MagLev model around a nominal operating point. In these simplified cases, the MagLev models may contain parameters that are not represented by proper physical quantities. Thus, in this work, we revised the issue of MagLev modelling from the first-principle approach. More specifically, we theoretically derived expressions for the interaction between the magnetic fields of the solenoid and a small magnetic object. The behaviour of the inductance on a distance from the solenoid was then described. The suggested MagLev modelling concept was verified experimentally, confirming the validity and correctness of the proposed MagLev mathematical model. The results presented here could thus be regarded as highly beneficial for formulating more complex MagLev designs exploitable in the field of model predictive control of the position of a levitating object.Konferenční objektpeer-reviewedpostprint Otevřený přístup Application of Model Predictive Controller to Magnetic Levitation(IEEE (Institute of Electrical and Electronics Engineers), 2023) Novotný, Aleš; Honc, DanielModel Predictive Control (MPC) is an advanced process control method that is widely used for controlling both linear and under some modifications for non-linear systems. The aim of this work is to show a way how to apply MPC to a non-linear Magnetic Levitation System (MLS) and its capability of stabilization and closed-loop performance. This work is a continuation of the previous article where the laboratory plant CE 152 MLS was identified, and a non-linear model was designed. This paper proposes a control circuit consisting of linearized discretized non-linear MLS model, Extended Kalman Filter (EKF) algorithm for state estimation and linear MPC. The results are verified in simulation and real-world experiment.Konferenční objektpeer-reviewedpostprint Otevřený přístup RCDue - experimental identification of continuous- and discrete-time models(IEEE (Institute of Electrical and Electronics Engineers), 2023) Dušek, František; Honc, Daniel; Novotný, AlešThe paper is devoted to the education and teaching of process control and automation. Various laboratory equipment is used to explain and better understand the theory and to gain practical experience. The authors have designed and developed a simple electrical dynamical system RCDue (dynamic model with passive RC components and Arduino Due as measurement and communication unit) that allows students to perform various laboratory experiments – e.g. static and dynamic characteristics measurements, modeling, experimental identification, control design and application of from the simplest strategies to advanced methods. Specifically, in this paper, the authors focus on experimental identification.Konferenční objektpeer-reviewedpostprint (accepted version) Omezený přístup Explanation of the predictive controller and the effect of its tuning on the control quality(Springer Nature Switzerland AG, 2022) Honc, Daniel; Novotný, Aleš; Kupka, LiborThe Model Predictive Control (MPC) concept and its realization is explained together with some real-world laboratory application examples. Usually, future control errors and control action changes are penalized in the cost function (objective) by predictive controllers. The cost function can be seen as a function of future control actions utilizing the process model in a form of the predictor. A derivation of the predictors for the transfer function (external) and state-space (internal) model is indicated in the paper. An analytical solution to the given optimization problem is possible in an unconstrained case. A quadratic programming strategy must be used in case of the occurrence of the process constraints that should be respected by the controller. The authors apply both algorithms to two types of dynamical systems – to proportional (stable) system and to integrating (unstable) system and they demonstrate the influence of the penalization parameters (weights) in the cost function on the control quality. The authors aim to high-light the MPC strategy and its potential, and on the other hand, mention some bottlenecks and risks associated with model-optimisation-based methods.Konferenční objektpeer-reviewedpostprint (accepted version) Omezený přístup Process Control Laboratory(Springer Nature Switzerland AG, 2022) Honc, Daniel; Novotný, Aleš; Havlíček, LiborThe authors are presenting Process Control Laboratory at the Faculty of Electrical Engineering and Informatics, University of Pardubice. The laboratory is equipped with six GUNT training systems covering common technological variables such as level, flow, pressure, temperature, speed, and position. The authors created SW support for MATLAB and Simulink environment. An internal part of the GUNT training systems is the LabJack U12 data acquisition card. LabJack Dynamic Link Library (DLL) is used to operate training systems from MATLAB. Authors created the M-S function to allow experimenting from Simulink. The possibilities of the proposed solution are demonstrated in several control applications.