Wyniki wyszukiwania - BazTech

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Modelowanie matematyczne i badania symulacyjne bioreaktora z wymuszonym napowietrzaniem

Przysiężnik Michał, Bartecki Krzysztof

Pomiary Automatyka Robotyka

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2023

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R. 27, nr 2

77--88

PL

Proces kompostowania jest powszechnie stosowany w gospodarce odpadami jako metoda przekształcania lub stabilizacji odpadów organicznych. Ze względu na złożony, nieliniowy charakter zachodzących w nim zjawisk biologicznych oraz fizykochemicznych, jest on stosunkowo trudny z punktu widzenia predykcji oraz sterowania. Sterowanie procesem ma tu na celu uzyskiwanie w określonym horyzoncie czasowym produktu finalnego, czyli zwykle kompostu spełniającego określone wymagania jakościowe. W artykule zaprezentowano prosty model matematyczny procesu kompostowania z wymuszonym napowietrzaniem, potencjalnie umożliwiającym realizację wspomnianego celu sterowania. Opracowano model drugiego rzędu, z dwiema wielkościami wejściowymi reprezentującymi zewnętrzne oddziaływania na proces. Na podstawie modelu matematycznego przekształconego do postaci równań stanu, zbudowano w środowisku MATLAB/Simulink model komputerowy bioreaktora, który następnie wykorzystano do przeprowadzenia badań symulacyjnych. Pokazano, że możliwe jest oddziaływanie na proces za pomocą wymuszonego napowietrzania, bezpośrednio wpływającego na zmianę temperatury w bioreaktorze, a w konsekwencji również na czas otrzymania końcowego produktu reakcji. Wyniki analizy właściwości dynamicznych procesu, przeprowadzonej z wykorzystaniem modelu zlinearyzowanego wzdłuż wybranej, nominalnej trajektorii stanu, wskazują na zmienny charakter jego stabilności - począwszy od niestabilności w początkowych fazach reakcji, przez stabilizację w fazie pośredniej, aż do stabilności asymptotycznej, zakończonej osiągnięciem stanu równowagi.

EN

The composting process is commonly used in waste management as a method of converting or stabilizing organic waste. Due to the complex, non-linear nature of biological and physicochemical phenomena involved, this process is relatively difficult to predict and control. The control is usually aimed at obtaining the final product, that is, the compost that meets legal standards. The article presents a simple mathematical model of the composting process with forced aeration, which will potentially facilitate the control task. A second order model was developed, with two inputs signals. Based on the mathematical model in the form of the state equations, the computer model of the bioreactor was built in the MATLAB/Simulink environment, which was then used to conduct different simulation tests. It was shown that it is possible to control the process using forced aeration, directly influencing the temperature changes in the bioreactor, and consequently also the time of obtaining the final product of the reaction. The analysis of the dynamic properties of the process performed using its model linearized about some nominal state trajectory shows the changes in its internal stability - starting from the unstable character in the initial phases of the reaction, through stabilization in its intermediate phase, up to the asymptotic stability, ending in the stable equilibrium state.

2

Model Predictive Control of the ship’s motion in presence of wind disturbances

Miller A.

Zeszyty Naukowe / Akademia Morska w Szczecinie

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2014

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nr 39 (111)

107--115

EN

Model Predictive Control is a control strategy which can be used for ships guidance and trajectory tracking problems. Linear multidimensional MPC controller is used to control the transversal, longitudinal and rotational velocities of a ship. Control system based on the MPC algorithms is robust to wind disturbances and thus can be used in real sailing conditions. It is proved by the computer simulations results and described in detail in this publication. Whole control system was designed and simulation studies were carried out on the basis of the real floating training ship model. A Model Predictive Controller synthesis steps, including linearization of the nonlinear ship model in the vicinity of operating point, are shown.

3

Model Based Diagnostics of Servo-Hydraulic System Using Quasi-Adaptive System Identification Approach

Czop P.

Machine Dynamics Problems

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2007

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Vol. 31, No. 4

15-33

EN

The aim of this paper is to provide a feasibility study of model based diagnostics using a "black-box" model approach. A moderately complex first principle model of a servo-hydraulic system was proposed to understand the diagnostic symptoms. Performance of a steam turbine control system is one of key factors for proper management of power plant assets. To achieve quality goals more advanced approach to diagnostic needs to be implemented. This paper presents model-based approach to diagnostics of hydraulic actuator performance monitoring eignefrequency and damping ratio variability. The feasibility study presented in this paper confirmed correctness of the proposed approach using quasi-adaptive system identification technique involving an ARX model. The results can also be utilized for optimal adjustment of the controller settings considering the load and variable stiffness of the actuator dependent on the piston-rod position.

4

Nonlinear Approarch to Model-Based Diagnostics of a Rotor Supported on Hydrodynamic Bearings

Czop P.

Machine Dynamics Problems

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2005

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Vol. 29, No. 2

23-34

EN

This paper presents numerical analyzes of a hydrodynamically supported rotor for purpose of fault detection with use of a parametric model-based approach. The significant increase of bearing load is considered as a faulty condition. The nonlinear and time varying diagnostic model is identified with use of Levenberg-Marquardt method. The transfer function model is instantaneously extracted from the considering nonlinear diagnostic model. The extraction is conducted based on the instantaneous linearization method for each discrete time interval. In the next step parameters are transformed into functions of natural frequencies and damping ratios vs. time. This method allows tracking changes of model parameters providing more sensitive detection of feasible malfunctions. The simulation of rotor-support model was conducted to generate numerical data for the experiment.