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A predictive control based on neural network for proton exchange membrane fuel cell
, Article World Academy of Science, Engineering and Technology ; Volume 50 , 2011 , Pages 456-460 ; 2010376X (ISSN) ; Rezaei, M ; Najmi, V ; Sharif University of Technology
Abstract
The Proton Exchange Membrane Fuel Cell (PEMFC) control system has an important effect on operation of cell. Traditional controllers couldn't lead to acceptable responses because of time- change, long- hysteresis, uncertainty, strong- coupling and nonlinear characteristics of PEMFCs, so an intelligent or adaptive controller is needed. In this paper a neural network predictive controller have been designed to control the voltage of at the presence of fluctuations of temperature. The results of implementation of this designed NN Predictive controller on a dynamic electrochemical model of a small size 5 KW, PEM fuel cell have been simulated by MATLAB/SIMULINK
A novel correlation approach for viscosity prediction of water based nanofluids of Al2O3, TiO2, SiO2 and CuO
, Article Journal of the Taiwan Institute of Chemical Engineers ; Volume 58 , 2016 , Pages 19-27 ; 18761070 (ISSN) ; Daryasafar, A ; MoradiKoochi, M ; Moghadasi, J ; BabaeiMeybodi, R ; KhorramGhahfarokhi, A ; Sharif University of Technology
Taiwan Institute of Chemical Engineers
2016
Abstract
Nanofluids viscosity is one of the most important thermophysical properties in nanofluids usage especially in chemical and petroleum engineering applications. So it is highly desirable to predict the viscosity of nanofluids accurately. Experimental measurements are impossible in most situations and present models are not comprehensive and efficient especially for high temperature, high volume concentration and high viscosity values. In this study, a new correlation has been developed based on the comprehensive database of water based Al2O3, TiO2, SiO2 and CuO nanofluids viscosity data found in literature. The proposed correlation uses temperature, nanoparticle size, nanoparticle volumetric...
Online path planning for Surena III humanoid robot using model predictive control scheme
, Article 4th RSI International Conference on Robotics and Mechatronics, ICRoM 2016, 26 October 2016 through 28 October 2016 ; 2017 , Pages 416-421 ; 9781509032228 (ISBN) ; Yousefi Koma, A ; Shirazi, F. A ; Mansouri, S ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2017
Abstract
In this paper, two online path planning methods are presented for SURENA III humanoid robot by using model predictive control scheme. The methods are general control schemes which can generate the online motions for walking of a humanoid robot. For lowering computational costs a three dimensional linear inverted pendulum model is used instead of the full dynamical model of the robot. The generated trajectories are then used for computing the zero-moment point (ZMP) of the robot and the joint torques. The resulted joint torques of the two methods are compared to torques obtained from Genetic Algorithm (GA) path planning method presented for SURENA III humanoid robot in previous studies. The...
Prediction of current-induced local scour around complex piers: Review, revisit, and integration
, Article Coastal Engineering ; Volume 133 , 2018 , Pages 43-58 ; 03783839 (ISSN) ; Ataie Ashtiani, B ; Beheshti, A ; Hadjzaman, M ; Jamali, M ; Sharif University of Technology
Elsevier B.V
2018
Abstract
Complex piers (CPs), consisting of a column, pile cap and pile group, are commonly built as foundations for hydraulic and marine structures. Scour-hole development around CPs is studied in this paper. A total of 52 tests is carried out on 4 CP models, with experiments durations ranging from 24 to 120 h. All of the available experimental data for clear-water scour around CPs including the collected data of the present study and those previously published are reviewed and combined into a database. A special case of bridge piers with deep foundation or caisson instead of pile caps is also considered, which is herein called compound piers. The database contains 367 experiments for CPs and 162...
Game theory meets distributed model predictive control in vehicle-to-grid systems
, Article 11th International Conference on Electrical and Electronics Engineering, ELECO 2019, 28 November 2019 through 30 November 2019 ; 2019 , Pages 764-768 ; 9786050112757 (ISBN) ; Haeri, M ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2019
Abstract
Electric Vehicles (EVs) will be used rampantly in future transportation system. Although the uncontrolled charging of these EVs will be threatening for the stability of the grid, a compatible energy trading policy may provide beneficial services to the grid as well as preserving the sustainability of the system. In this paper, by taking advantage of block rate tariff, a wholesale pricing policy is introduced. A multi-objective approach is utilized to address the cost reduction and load leveling services concurrently. Due to the high computational complexity of a centralized problem, a game theoretic approach is exerted in order to design decentralized controllers for EVs. Moreover, an MPC...
Improvement of operator position prediction in teleoperation systems with time delay: Simulation and experimental studies on Phantom Omni devices
, Article Jordan Journal of Mechanical and Industrial Engineering ; Volume 13, Issue 3 , 2019 , Pages 197-205 ; 19956665 (ISSN) ; Nikpour, M ; Beigzadeh, B ; Meghdari, A ; Sharif University of Technology
Hashemite University
2019
Abstract
An online operator position prediction approach based on artificial neural network for teleoperation systems is proposed in this paper, which predicts future position of operator's hand based on current available data. The neural network gathers inputs for some time at the beginning of the operation, then is trained, and is finally exploited through the rest of the operation. Superiority of the proposed approach can be investigated from two aspects. Firstly, no limiting assumption is required in this approach in contrast with the proposed methods in the literature. Secondly, unknown operator intention can be dealt with in real time if it is not too sudden and unpredictable. Two different...
Asteroid precision landing via Probabilistic Multiple-Horizon Multiple-Model Predictive Control
, Article Acta Astronautica ; Volume 161 , 2019 , Pages 531-541 ; 00945765 (ISSN) ; Assadian, N ; Sharif University of Technology
Elsevier Ltd
2019
Abstract
This paper seeks to provide a probabilistic control framework, named Probabilistic Multiple-Horizon Multiple-Model Predictive Control, for the soft and precise landing on an asteroid. The modified version of the Predictive Path Planning method is also introduced to generate a safe and smooth reference trajectory for landing. The Probabilistic Multiple-Horizon Multiple-Model Predictive Control is carried out in two phases; the offline phase to calculate the difference between models, and the online phase to use a probabilistic approach to track the reference trajectory. The difference of the dynamical models is utilized in the online control method to compensate the accuracy of the...
Predictive-reactive rescheduling for new order arrivals with optimal dynamic pegging
, Article 16th IEEE International Conference on Automation Science and Engineering, CASE 2020, 20 August 2020 through 21 August 2020 ; Volume 2020-August , 8 October , 2020 , Pages 710-715 ; Saitou, K ; Sharif University of Technology
IEEE Computer Society
2020
Abstract
This paper presents a new predictive-reactive rescheduling method for adjusting production schedules in response to the unplanned arrival of new orders in multi-level production. It is based on the concept of dynamic pegging, which enables the reassignment of the Work-In-Progress (WIP) to the existing or newly arrived orders at the time of rescheduling. Extending our previous work on reactive rescheduling with dynamic pegging, the new approach incorporates a probabilistic predictive model of new order arrival in the initial scheduling at the begging of the scheduling horizon. A Mixed Integer Programming (MIP) model is developed for two-phase, predictive-reactive scheduling before and after...
Improving quality of a post's set of answers in stack overflow
, Article 46th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2020, 26 August 2020 through 28 August 2020 ; 2020 , Pages 504-512 ; Izadi, M ; Heydarnoori, A ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2020
Abstract
Community Question Answering platforms such as Stack Overflow help a wide range of users solve their challenges on-line. As the popularity of these communities has grown over the years, both the number of members and posts have escalated. Also, due to the diverse backgrounds, skills, expertise, and viewpoints of users, each question may obtain more than one answer. Therefore, the focus has changed toward producing posts that have a set of answers more valuable for the community as a whole, not just one accepted-answer aimed at satisfying only the question-asker. Same as every universal community, a large number of low-quality posts on Stack Overflow require improvement. We call these posts...
An extended dynamic matrix control design for quasi-resonant converters
, Article 2008 IEEE 2nd International Power and Energy Conference, PECon 2008, Johor Baharu, 1 December 2008 through 3 December 2008 ; January , 2008 , Pages 1147-1151 ; 9781424424054 (ISBN) ; Ebad, M ; Sharif University of Technology
2008
Abstract
The Extended dynamic matrix control (EDMC) has been proved to extend the existing version of the linear model predictive control to control nonlinear systems. In this method, the control input is determined based on the linear model approximation of the system that is updated during each sampling interval. In this paper, by using this method, a new control scheme for quasi-resonant converters is described. This control offers an excellent transient response and a good tracking. © 2008 IEEE
Multiple modeling and fuzzy predictive control of a tubular heat exchanger system
, Article WSEAS Transactions on Systems and Control ; Volume 3, Issue 4 , 2008 , Pages 249-258 ; 19918763 (ISSN) ; Sadati, N ; Sharif University of Technology
2008
Abstract
In this paper, a novel generalized predictive control (GPC) strategy using multiple models approach has been presented. The proposed strategy is realized based on the Takagi-Sugeno-Kang (TSK) fuzzy-based modeling for control of a tubular heat exchanger system. In this strategy, different operating environments of the system with varying parameters are first identified. Then for each environment, a linear model and its corresponding fuzzy predictive controller are designed. For demonstrating the effectiveness of the proposed approach, simulations are done and the results are compared with those obtained using the single model predictive control approach. The results can verify the validity of...
Modeling, estimation, and model predictive control for Covid-19 pandemic with finite security duration vaccine
, Article 30th International Conference on Electrical Engineering, ICEE 2022, 17 May 2022 through 19 May 2022 ; 2022 , Pages 78-83 ; 9781665480871 (ISBN) ; Baghbadorani, R. R ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2022
Abstract
Spreading Covid19 has significantly impacted humans' affairs worldwide, either economically or in a sanitary manner. Besides social distance and hospitalization, making and introducing different vaccines help us ameliorate infection and mortality rates. In this research, we use a nonlinear dynamic model for Covid19, with eight states named susceptible, exposed, infected, quarantined, hospitalized, recovered, deceased, and insusceptible populations. Also, we use social distancing, hospitalization, and vaccination rate as three control inputs. This research aims to stop the Covid-19 from spreading worldwide and minimize exposed, infected and deceased populations using model predictive control....
A Robust MPC method for post-disaster distribution system reconfiguration based on repair crew routing
, Article 17th International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2022, 12 June 2022 through 15 June 2022 ; 2022 ; 9781665412117 (ISBN) ; Fotuhi Firuzabad, M ; Mazaheri, H ; Lehtonen, M ; Moeini Aghtaie, M ; Peyghami, S ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2022
Abstract
Distribution system reconfiguration is an effective solution to reduce the consequences of a disaster through transferring loads to another feeder via automatic switches. Meanwhile, an optimal sequence of damage components repairments provides the operator with the opportunity to utilize components that play a critical role in restoring loads sooner. Motivated by the rise in penetration of renewable distributed generators in modern distribution systems, this paper aims to develop a robust reconfiguration and crew routing co-optimization method to cope with renewable and demand uncertainties while recovering from a disaster. The method optimizes the grid recovery process for the worst...
Fuzzy Predictive Control of a Continuous Polymerization Stirred Tank Reactor
,
M.Sc. Thesis
Sharif University of Technology
;
Pishvaie, Mahmoud Reza
(Supervisor)
Abstract
In industries there are many nonlinear processes which cannot be easily controlled with classical methods. Model predictive control is a useful method for nonlinear processes which not only has high efficiency, but also extension of this control to interferential multi variable case, with constraint on the controlled and manipulated variables and other problematic dynamic specifications such as slow dynamics and inverse response is very simple. Industrial polymerization processes are regarded as significant nonlinear processes. Optimization and control of polymerization reactors have considerable importance in process applicability and in economics. The molecular structure of polymer such as...
Predicting Research Trends by Using Link Prediction in Keywords Network
, M.Sc. Thesis Sharif University of Technology ; Hajsadeghi, Khosrow (Supervisor) ; Kavousi, Kaveh (Co-Advisor)
Abstract
The rapid development of scientific areas in this modern era makes the process of finding new field of research slow and laborious for prospective scholars. Thus, having a vision of the future could be helpful to pick a right path for doing researches and ensuring that it is worth to invest in. This thesis seeks to predict research trends by using link prediction approaches on keywords network and discusses about the performance of various algorithms in different situations. Moreover, for the last part of the experiments, novel link prediction algorithms are proposed by the author, enhances the accuracy of prediction results. The data set collected from Sciencedirect and Scopus by a strong...
Statistical Labeling, Cluster-Based Approach for Improving Fraud Detection Classification Performance in Unbalanced Datasets
, M.Sc. Thesis Sharif University of Technology ; Shadrokh, Shahram (Supervisor) ; Khedmati, Majid (Co-Supervisor)
Abstract
Nowadays, researchers working on classifiers which are designed to predict minority class. In this work, we attempt to improve fraud detection performance, with minimum possible complexity. In this regard, by incrementing model sensitivity to minority class samples, we solve the problem of model ignorance to these instances. Moreover, by using clustering, we cluster similar inputs based on their features, and split each class to smaller bins. Then with considering the fact that, prediction probability threshold influences the final performance, we define statistical hypothesis testing exclusively for each cluster to evaluate predictions with expected range. In this method, model is not...
Application of artificial neural networks to prediction of chemical composition of electrodeposited Ni-Mo thin films
, Article ECS Transactions ; Volume 50, Issue 52 , Oct , 2012 , Pages 63-71 ; 19385862 (ISSN) ; Rouhaghdam, A. S ; Aliofkhazraie, M ; Shahrabi, T ; Ashrafi, A ; Seddighian, A ; Sharif University of Technology
2012
Abstract
Present research represents the application of artificial neural networks to predict the chemical composition of electrodeposited Ni-Mo thin films. Artificial neural networks commonly are utilized as a prediction tools so that these networks could approximately find kind of logic relationships between inputs and target; they fitted appropriate coefficient and weighting factors to the inputs which are proportional to their importance. In order to evaluate the model developed, experimental results were compared with the predicted ones. However, more data are required to train more reliable prediction models, presents study revealed an acceptable error less than 1% between predicted values and...
A model for traffic prediction in wireless ad-hoc networks
, Article Communications in Computer and Information Science ; Volume 241 CCIS , 2011 , Pages 328-335 ; 18650929 (ISSN) ; 9783642273360 (ISBN) ; Manzuri, M. T ; Latifi, N ; Sharif University of Technology
Abstract
In recent years, Wireless Ad-hoc networks have been considered as one of the most important technologies. The application domains of Wireless Ad-hoc Networks gain more and more importance in many areas. One of them is controlling and management the packet traffic. In this paper our goal is controlling the performance of every sections of pipeline of the factory by checking network periodically. Along the factory the traffic is modeled with a Poisson process. We present, with obtaining traffic packets at time (t) for each node in Wireless Ad-hoc Network, we can completely train a Neural Network and successfully predict the traffic at time (t+1) for each node. By this way we can recognize the...
Robust model predictive control of nonlinear processes represented by Wiener or Hammerstein models
, Article Chemical Engineering Science ; Volume 129 , 2015 , Pages 223-231 ; 00092509 (ISSN) ; Haeri, M ; Sharif University of Technology
Elsevier Ltd
2015
Abstract
Representing nonlinear systems by linear models along with structured or unstructured uncertainties and applying robust control strategies could reduce the computational complexity in comparison with implementing the nonlinear model predictive controllers. In this paper design of robust model predictive controllers which are based on special classes of nonlinear systems representations called Wiener and Hammerstein are presented. The proposed algorithms approximate the nonlinear systems by uncertain linear models and reduce online the computational demands in the control implementation. The advantages of the proposed approaches are illustrated by two examples
Uncertainty analysis of wind-wave predictions in Lake Michigan
, Article China Ocean Engineering ; Volume 30, Issue 5 , 2016 , Pages 811-820 ; 08905487 (ISSN) ; Ataie Ashtiani, B ; Hamidi, S. A ; Sharif University of Technology
Springer Verlag
Abstract
With all the improvement in wave and hydrodynamics numerical models, the question rises in our mind that how the accuracy of the forcing functions and their input can affect the results. In this paper, a commonly used numerical third-generation wave model, SWAN is applied to predict waves in Lake Michigan. Wind data are analyzed to determine wind variation frequency over Lake Michigan. Wave predictions uncertainty due to wind local effects are compared during a period where wind has a fairly constant speed and direction over the northern and southern basins. The study shows that despite model calibration in Lake Michigan area, the model deficiency arises from ignoring wind effects in small...