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 Otevřený přístup Desired Terminal State Concept in Model Predictive Control: A Case Study(Hindawi limited, 2019) Dušek, František; Honc, DanielThe paper deals with an online optimization control method for dynamical processes called Model Predictive Control (MPC). It is a popular control method in industry and frequently treated in academic areas as well. The standard predictive controllers usually do not guarantee stability especially for the case of short horizons and large control error penalization. Terminal state is one way to ensure stability or at least increase the controller robustness. In the paper, deviation of the predicted terminal state from the desired terminal state is considered as one term of the cost function. Effect of the stability and control quality is demonstrated in the simulated experiments. The application area for online optimization methods is very broad including various logistics and transport problems. If the dynamics of the controlled processes cannot be neglected, the optimization problem must be solved not only for steady state but also for transient behaviour, e.g., by MPC.Konferenční objektpeer-reviewedpostprint Otevřený přístup Convolutional Neural Network for Sound Processing - Study of Deployed Application(IEEE (Institute of Electrical and Electronics Engineers), 2019) Doležel, Petr; Štursa, Dominik; Honc, DanielPest birds are considered as a special kind of vermin, since, in most of countries, their legal position does not enable their direct extermination. Therefore, in order to protect the agricultural areas indirectly from pest birds, the robust and highly selective pest bird sensor is necessary to design. In this contribution, the pest bird detection unit, based on a convolutional neural network, is presented. The convolutional neural network itself is used for the decision making about the pest bird occurrence, while sound recordings are used as input data. The testings, presented at the end of the contribution, proved a very high accuracy of the detection unit, with the results indispensably improved in comparison to previously presented approaches.Konferenční objektpeer-reviewedpostprint Omezený přístup Predictive Controller Based on Feedforward Neural Network with Rectified Linear Units(Springer Nature Switzerland AG, 2019) Doležel, Petr; Honc, Daniel; Štursa, DominikThis paper deals with a nonlinear Model Predictive Control with a special form of the process model. Controller uses for the prediction purposes a locally valid linear sub-models. The sub-models are obtained from a neural model with the rectifier activation function in hidden neurons. Simulation example is given to demonstrate proposed solution - neural model design and predictive controller application.Konferenční objektpeer-reviewedpostprint Omezený přístup Neural Network for Smart Adjustment of Industrial Camera - Study of Deployed Application(Springer, 2018) Doležel, Petr; Honc, DanielSince machine vision is gaining more and more interest lately, it is necessary to deal with correct approaches to visual data acquisition in industry. As a particular part of this complex problematics, a technique for the industrial camera exposure time and image sensor gain tuning is presented in this contribution. In comparison to other approaches, a human expert photographer is used instead of explicitly defined cost function. His knowledge is transformed into an artificial expert system represented by a feedforward neural network. The expert system then provides the suitable exposure time and image sensor gain to gather sharp and balanced images.Konferenční objektpeer-reviewedpostprint Omezený přístup Thermal Process Control Using Neural Model and Genetic Algorithm(Springer Nature Switzerland AG, 2019) Honc, Daniel; Doležel, Petr; Merta, JanPredictive Controller of a laboratory thermal process is presented in the paper. Process model is approximated by a neural network. On-line optimization is done by a genetic algorithm. Control algorithm is tested on the laboratory thermal process and compared to the standard control methods like predictive controller with the transfer and state-space linear model and the quadratic programming optimization method or a PI controller.Konferenční objektpeer-reviewedpostprint Omezený přístup Static Compensator for Decentralized Control of Nonsquare Systems(Springer Nature Switzerland AG, 2019) Dušek, František; Honc, Daniel; Merta, JanThe paper deals with the decentralized control problem for linear multivariable systems with the number of manipulated variables equal or greater than the number of controlled variables. Proposed static compensator ensures automatic creation of input/output pairs for individual control loops. The compensator provides steady state autonomy and unit gain for the control loops. Steady state gain matrix of the controlled system and vector of offsets are sufficient infor-mation for the compensator design. Estimation of the gain matrix and offsets from the measured data is also proposed in the paper.Konferenční objektpeer-reviewedpostprint Otevřený přístup Software for Thermogravimeter(IEEE (Institute of Electrical and Electronics Engineers), 2019) Dušek, František; Honc, Daniel; Havlíček, Libor; Merta, JanSoftware for thermogravimeter constructed at the Department of Inorganic Technology, University of Pardubice is presented in the paper. Used hardware and design of the experiment is described briefly. Main part of the paper focusses to the software solution in MATLAB environment. Except control, plotting and data exporting tasks it was necessary to communicate with Eurotherm nanodac Recorder / Controller through the TCP/IP Modbus protocol and with Sartorius weigh cell through the serial USB ASCII-based protocol. Simple example of Constant Rate Thermal Analysis experiment is given at the end of the paper.Konferenční objektpeer-reviewedpostprint Otevřený přístup Analytic model predictive controller in simple symbolic form(Springer International Publishing AG, 2019) Honc, Daniel; Jičínský, MilanPaper deals with an analytic solution of Model Predictive Controller in simple symbolic form. Process is approximated with a first order dynamical model. Special choice of prediction and control horizons is considered, so the symbolic solution is still applicable, and the controller has interesting “predictive” feature in case of known future set-point course. Such a controller can be used in simple devices like PLCs or microcontrollers without need of matrix operations. Its advantage is that the controller reacts to the process model parameters and penalty parameter change so the control can be very fast and efficient even in adaptive manner.Článekpeer-reviewedpostprint Otevřený přístup Reduced order modelling and predictive control of multivariable nonlinear process(Indian Academy of Sciences, 2018) Abraham, Anuj; Pappa, N.; Honc, Daniel; Sharma, RahulIn this paper, an efficient model-predictive control strategy that can be applied to complex multivariable process is presented. A reduced order generalized predictive algorithm is proposed for online applications with reduction in complexity and time elapsed. The complex multivariable process considered in this work is a binary distillation column. The reduced order model is developed with a recently proposed hybrid algorithm known as Clustering Dominant Pole Algorithm and is able to compute the full set of dominant poles and their cluster centre efficiently. The controller calculates the optimal control action based on the future reference signals, current state and constraints on manipulated and controlled variables for a high-order dynamic simulated model of nonlinear multivariable binary distillation column process. The predictive control algorithm uses controlled auto-regressive integrated moving average model. The performance of constraint generalized predictive control scheme is found to be superior to that of the conventional PID controller in terms of overshoot, settling time and performance indices, mainly ISE, IAE and MSE.Konferenční objektpeer-reviewedpostprint Otevřený přístup Modelling and identification of magnetic levitation model CE 152/revised(Springer International Publishing AG, 2019) Honc, DanielPaper describes procedure of first principle modelling and experimental identification of Magnetic Levitation Model CE 152. Author optimized and simplified dynamical model to a minimum what is needed to characterize given system for the simulation and control design purposes. Only few experiments are needed to estimate the unknown parameters. Model quality is verified in the feedback control loop where the real and simulated data are compared. © 2019, Springer International Publishing AG, part of Springer Nature.
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