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predictive-controllers
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Total 271 records
Distributed Robust Model Predictive Control for Multi-zone Air Conditioning Systems
, M.Sc. Thesis Sharif University of Technology ; Moradi, Hamed (Supervisor)
Abstract
Optimizing the energy consumption of air conditioning systems has gained great importance in recent years. In addition, maintaining thermal comfort and air quality in buildings is important. The multi-evaporator air conditioning system, which is a direct expansion system, shows the complex and distributed structure of air conditioning systems due to the thermal connection between zones and its large scale. The modeling of these systems is associated with uncertainties. Therefore, designing a suitable control structure for multi-zone systems is very important to achieve optimal energy consumption and maintain comfort conditions in the presence of uncertainty. Model predictive control has been...
Finite-Control-Set Model Predictive Control for Doubly Fed Induction Generator of a Floating Offshore Wind Turbine
, M.Sc. Thesis Sharif University of Technology ; Sadati, Naser (Supervisor)
Abstract
The purpose of this project is designing a controller for a floating offshore wind turbine to exctract maximum power from wind energy in the first operating region of wind turbine. The NREL 5 MW OC3-Hywind floating wind turbine with BARGE platform will be used for this project. By using Turbsim software, proper wind profile for the first operating region of wind turbine will be produced. This profile will be excecuted for the FAST software that is simulates the mechanical part of wind turbine. By implementing the doubly fed induction generator in Simulink enviroment and designing the controller for doubly fed induction generator, the desired torque for maximizing the exctraction power of...
Multiple-Model Predictive Control for a Fed-Batch Bioreactor of Ethanol Production
, M.Sc. Thesis Sharif University of Technology ; Pishvaie, Mahmoud Reza (Supervisor)
Abstract
Bioethanol is an alcohol that is produced by microbial fermentation from carbohydrates produced in sugar-containing plants such as corn, sugarcane, or lignocellulosic biomass. Bioethanol is mostly used as an additive to gasoline. Cars can run on a 15% blend of bioethanol and gasoline and need to be modified to use pure bioethanol. Ethanol in vehicles is beneficial for the environment Because ethanol pollutants are cleaner than greenhouse gases. Ethanol is also used to produce ethyl acetate, which is a widely used solvent in the printing and packaging industries. In this research, fed-batch bioethanol reactor was investigated. First, the modeling of the bioreactor was done and the behavior of...
A new method to control heat and mass transfer to work piece in a GMAW process
, Article Journal of Process Control ; Volume 22, Issue 6 , 2012 , Pages 1087-1102 ; 09591524 (ISSN) ; Haeri, M ; Sharif University of Technology
2012
Abstract
It is proposed to employ melting rate, heat input, and detaching droplet diameter as controlled variables to control heat and mass transfer to work piece in a gas metal arc welding process. A two-layer architecture with cascade configuration of PI and MPC controllers is implemented to incorporate existing constraints on the process variables, improve transient behavior of the closed-loop responses and reduce interaction level. Computer simulation results are presented to indicate usefulness of the proposed controlled variables selection and applying two-layer control architecture to control heat and mass transfer to work piece
Adaptive nonlinear control of pH neutralization processes using fuzzy approximators
, Article Control Engineering Practice ; Volume 17, Issue 11 , 2009 , Pages 1329-1337 ; 09670661 (ISSN) ; Shahrokhi, M ; Nejati, A ; Sharif University of Technology
2009
Abstract
In this paper, an adaptive control scheme, based on fuzzy logic systems, for pH control is addressed. For implementation of the proposed scheme no composition measurement is required. Stability of the closed-loop system is established and it is shown that the solution of the closed-loop system is uniformly ultimately bounded and under a certain condition, asymptotical stability is achieved. Effectiveness of the proposed controller is tested through simulation and experimental studies. Results indicate that the proposed controller has good performances in set-point tracking and load rejection and much better than that of a tuned PI controller. © 2009 Elsevier Ltd. All rights reserved
A general analytical approach to reach maximum grid support by PMSG-based wind turbines under various grid faults
, Article Journal of Central South University ; Volume 26, Issue 10 , 2019 , Pages 2833-2844 ; 20952899 (ISSN) ; Ajami, A ; Mokhtari, H ; Hojabri, H ; Sharif University of Technology
Central South University of Technology
2019
Abstract
A novel fault ride-through strategy for wind turbines, based on permanent magnet synchronous generator, has been proposed. The proposed strategy analytically formulates the reference current signals, disregarding grid fault type and utilizes the whole system capacity to inject the reactive current required by grid codes and deliver maximum possible active power to support grid frequency and avoid generation loss. All this has been reached by taking the grid-side converter’s phase current limit into account. The strategy is compatible with different countries’ grid codes and prevents pulsating active power injection, in an unbalanced grid condition. Model predictive current controller is...
Adaptive online prediction of operator position in teleoperation with unknown time-varying delay: simulation and experiments
, Article Neural Computing and Applications ; 2020 ; Yazdankhoo, B ; Beigzadeh, B ; Meghdari, A ; Sharif University of Technology
Springer Science and Business Media Deutschland GmbH
2020
Abstract
One of the most important problems in teleoperation systems is time delay and packet loss in the communication channel, which can affect transparency and stability. One way to overcome the time delay effects in a teleoperation system is to predict the master-side motion. In this way, when data is received in the slave side, it will be considered as the current position of the master robot and, thus, complete transparency could be achieved. The majority of the previous works regarding operator position prediction have considered known and constant time delay in the system; however, in the real applications, time delay is unknown and variable. In this paper, an adaptive online prediction...
Controlling the depth of anesthesia by using extended DMC
, Article 2008 Cairo International Biomedical Engineering Conference, CIBEC 2008, Cairo, 18 December 2008 through 20 December 2008 ; 2008 ; 9781424426959 (ISBN) ; Towhidkhah, F ; Marami, B ; Sharif University of Technology
2008
Abstract
Monitoring and controlling the depth of anesthesia is really important, since over dosing and under dosing can be dangerous for the patients. Pharmacokinetic-Pharmacodynamic models vastly used for describing the relationship between input anesthetic agents and output patient endpoint variables. As there is a large variety between the patients so for controlling the depth of anesthesia we need a controller which should be robust enough and also because the anesthesia process is nonlinear and contains time delay, among them all the proposed methods for controlling the depth of anesthesia, model predictive controllers (MPCs) are good choices. Extended dynamic matrix control (EDMC) can be...
Quantitative Structure - Retention Relationship study of benzodiazepines using adaptive neuro fuzzy inference system as feature selection method
, Article QSAR and Combinatorial Science ; Volume 27, Issue 4 , 2008 , Pages 407-416 ; 1611020X (ISSN) ; Kyani, A ; Afsari Mamaghani, S ; Ghadiri Bidhendi, A ; Sharif University of Technology
2008
Abstract
A Quantitative Structure-Retention Relationship (QSRR) study of 32 benzodiazepines is performed in this work. Two feature selection methods of Adaptive Neuro Fuzzy Inference System (ANFIS) and a stepwise regression approach adopted for the Multiple Linear Regressions (MLR) were used to predict the Liquid Chromatography-Mass Spectrometry (LC-MS) Retention Time (RT) of these compounds on a Xterra MS C-18 stationary phase. ANFIS and MLR methods were used as variable selection tools and a neural network was employed for predicting the RTs. Tbree descriptors of 3D-MoRSE-signal 06/weighted by atomic polarizabilities (Mor06p), Radial Distribution Function-1.0/weighted by atomic van der Waals...
Reduced multiple model predictive control of an heating, ventilating, and air conditioning system using gap metric and stability margin
, Article Building Services Engineering Research and Technology ; Volume 43, Issue 5 , 2022 , Pages 589-603 ; 01436244 (ISSN) ; Haeri, M ; Sharif University of Technology
SAGE Publications Ltd
2022
Abstract
In this paper, a reduced multiple-model predictive controller based on gap metric and stability margin is presented to control heating, ventilating, and air conditioning (HVAC) systems. To tackle the strong nonlinearity and large number of degrees of freedom in HVAC system, two approaches, called Reduced Order Model Bank-Multiple Model (ROMB-MM) and Multiple Model-Reduced Order Model (MM-ROM), are introduced. In the first approach, the order reduction is performed prior to multiple models selection and in the second one multiple models selection is implemented before the model order reduction. Furthermore, soft switching is employed to enhance the closed-loop performance as well as to gain...
Adaptive neuro-fuzzy algorithm applied to predict and control multi-phase flow rates through wellhead chokes
, Article Flow Measurement and Instrumentation ; Volume 76 , 2020 ; Wood, D. A ; Mohamadian, N ; Rashidi, S ; Davoodi, S ; Soleimanian, A ; Kiani Shahvand, A ; Mehrad, M ; Sharif University of Technology
Elsevier Ltd
2020
Abstract
A Takagi-Sugeno adaptive neuro-fuzzy inference system (TSFIS) model is developed and applied to a dataset of wellhead flow-test data for the Resalat oil field located offshore southern Iran, the objective is to assist in the prediction and control of multi-phase flow rates of oil and gas through the wellhead chokes. For this purpose, 182 test data points (Appendix 1) related to the Resalat field are evaluated. In order to predict production flow rate (QL) expressed as stock-tank barrels per day (STB/D), this dataset includes four selected input variables: upstream pressure (Pwh); wellhead choke sizes (D64); gas to liquid ratio (GLR); and, base solids and water including some water-soluble...