Design of a Dispensing CNC Device

This article deals with the design and practical realization of a CNC device designed for the application of viscous materials, such as a thermal conducting paste. Paste is used for effective heat transfer what is essential in switched mode power supplies. However, its application on surface can be an issue. Designed CNC device serves for easier and more accurate application in production process using standard tubes

State Observer for Optimal Control using White-box Building Models

In order to improve the energy efficiency of buildings, optimal control strategies, such as model predictive control (MPC), have proven to be potential techniques for intelligent operation of energy systems in buildings. However, in order to perform well, MPC needs an accurate controller model of the building to make correct predictions of the building thermal needs (feedforward) and the algorithm should ideally use measurement data to update the model to the actual state of the building (feedback). In this paper, a white-box approach is used to develop the controller model for an office building, leading to a model with more than 1000 states. As these states are not directly measurable, a state observer needs to be developed. In this paper, we compare three different state estimation techniques commonly applied to optimal control in buildings by applying them on a simulation model of the office building but fed with real measurement data. The considered observers are stationary Kalman Filter, time-varying Kalman Filter, and Moving Horizon Estimation. Summarizing the results, all estimators can achieve low output estimation error, but on the other hand only Moving Horizon Estimation is capable to keep the state trajectories within the limits thanks to the constraints at expenses of the computational time. As a first step towards real implementation of white-box MPC, in this paper, we have compared different state estimation techniques commonly applied to optimal control in buildings. We selected three different state observers available from the literature and compared their estimation error and robustness against initial conditions and noise in a numerical case study by using a virtual test bed model of a real building

Fluid temperature predictions of geothermal borefields using load estimations via state observers

Fluid temperature predictions of geothermal borefields usually involve temporal superposition of its characteristic g-function, using load aggregation schemes to reduce computational times. Assuming that the ground has linear properties, it can be modelled as a linear state-space system where the states are the aggregated loads. However, the application and accuracy of these models is compromised when the borefield is already operating and its load history is not registered or there are gaps in the data. This paper assesses the performance of state observers to estimate the borefield load history to obtain accurate fluid predictions. Results show that both Time-Varying Kalman Filter (TVKF) and Moving Horizon Estimator (MHE) provide predictions with average and maximum errors below 0.1∘C and 1∘C, respectively. MHE outperforms TVKF in terms of n-step ahead output predictions and load history profile estimates at the expense of about five times more computational time

Constructing Neural Network-Based Models for Simulating Dynamical Systems

Dynamical systems see widespread use in natural sciences like physics, biology, chemistry, as well as engineering disciplines such as circuit analysis, computational fluid dynamics, and control. For simple systems, the differential equations governing the dynamics can be derived by applying fundamental physical laws. However, for more complex systems, this approach becomes exceedingly difficult. Data-driven modeling is an alternative paradigm that seeks to learn an approximation of the dynamics of a system using observations of the true system. In recent years, there has been an increased interest in data-driven modeling techniques, in particular neural networks have proven to provide an effective framework for solving a wide range of tasks. This paper provides a survey of the different ways to construct models of dynamical systems using neural networks. In addition to the basic overview, we review the related literature and outline the most significant challenges from numerical simulations that this modeling paradigm must overcome. Based on the reviewed literature and identified challenges, we provide a discussion on promising research areas

Experimental Analysis of Communitation Process of Power Semiconductor Transistor’s Structures

The paper deals with testing device designed for experimental examination of processes in power electronics devices during various switching modes is described. Through the use of auxiliary circuits additional switching modes (ZVS, ZCS) are realized except hard switching, and turning-off with reduced current respectively. The device´s advantage is possibility of fine dead time setting, allowing us analyzing the effects of phenomenon noted above, on measurements of commutation losses

Servosystem elektryczny dla urządzenia zasilającego pasażenia turbowego

This paper deals with electric compensation servo system which serves as an upgrade for existing turbocharger vacuum pressure regulation, particularly for low-volume engines. Proposed servosystem is suitable for variable geometry turbocharger (VGT) or variable nozzle turbocharger (VNT). Servo system comprises from control unit which is attached to the signal conditioner and to the microprocessor. The microprocessor controls the servo drive through the output amplifier and servo drive is mechanically connected to the turbocharger. Advantage of this upgrade is in better response to torque requirements from driver, especially in low engine speed.W pracy przedstawiono możliwość wymiany standardowego siłownika próżniowego dla siłownika o zmiennej dyszy / geometrii za pomocą elektrycznego serwomechanizmu za pomocą mikroprocesora. Korzystanie z tego serwosu w nowym algorytmie sterowania zmniejsza emisje z silnika, zwiększa moc silnika i eliminuje siłownik podciśnieniowy. Inną zaletą tego systemu jest wyeliminowanie źródła ujemnego ciśnienia z systemu turbodoładowania (proponowany serwoster jest zasilany standardową siecią 12V). Jedyną wadą proponowanego elektrycznego serwosysu jest konieczność kalibracji pomiędzy systemem sterowania (mikroprocesorem) a turbosprężarką