En
  • دکتری (1366)

    مهندسی برق-کنترل

    امپریال کالج، لندن، انگلستان

  • کارشناسی‌ارشد (1358)

    مهندسی برق-کنترل

    ویسکانسین، مدیسن، امریکا

  • کارشناسی (1356)

    مهندسی برق-کنترل

    صنعتی شریف، تهران، ایران

  • كنترل تطبیقی، کنترل مقاوم، شناسایی سیستمها، اتوماسیون، ابزار دقیق، سیستم‌های مرتبه کسری
  • ابزار دقیق و اتوماسیون صنعتی

حمیدرضا مومنی در سال 1333 در شهرستان خمین، ایران به دنیا آمد. ایشان مدارک تحصیلی کارشناسی ، کارشناسی ارشد ، و دکتری خود را در رشته مهندسی برق – گرایش کنترل به ترتیب در سال 1356 از دانشگاه صنعتی شریف – تهران ، در سال 1358 از دانشگاه ویسکانسین – مدیسن امریکا و در سال 1366 از دانشگاه امپریال کالج – لندن در انگلستان اخذ نموده است. علایق تحقیقاتی ایشان در زمینه : کنترل تطبیقی ، کنترل مقاوم ، سیستمهای حرکت از راه دور ، کنترل صنعتی ، ابزاردقیق و اتوماسیون صنعتی میباشد. ایشان چندین نوبت مدیر گروه کنترل و دو نوبت رییس دانشکده مهندسی برق و کامپیوتر بوده اند.

ارتباط

رزومه

Incorporating Coincidental Water Data into Non-intrusive Load Monitoring

Mohammad-Mehdi Keramati, Elnaz Azizi, Hamidreza Momeni, Sadegh Bolouki
Journal PapersarXiv preprint arXiv:2101.07190 , 2021 January 18, {Pages }

Abstract

Non-intrusive load monitoring (NILM) as the process of extracting the usage pattern of appliances from the aggregated power signal is among successful approaches aiding residential energy management. In recent years, high volume datasets on power profiles have become available, which has helped make classification methods employed for the NILM purpose more effective and more accurate. However, the presence of multi-mode appliances and appliances with close power values have remained influential in worsening the computational complexity and diminishing the accuracy of these algorithms. To tackle these challenges, we propose an event-based classification process, in the first phase of which the -nearest neighbors method, as a fast classificat

Stabilization Voltage of a DC-Microgrid Using ANFIS Controller Considering EVs, DERs, and Transient Storage

H Zolfaghari, A Ramezani, HR Momeni
Journal Papers , , {Pages }

Abstract

Robust tube-based MPC with enlarging the region of attraction for tracking of switched systems

Y Abbasi, HR Momeni, A Ramezani
Journal Papers , , {Pages }

Abstract

A Recursive Delay Estimation Algorithm for Linear Multivariable Systems with Time-varying Delays

I Shafikhani, HS Karimi, M Mohammadian, A Ramezani, HR Momeni
Journal Papers , , {Pages }

Abstract

A constrained distributed time-series neural network MPC approach for HVAC system energy saving in a medium-large building

O Asvadi-Kermani, H Momeni
Journal Papers , , {Pages }

Abstract

Seyed Mohammad Sadjad Sadough, University of Shahid beheshti Seyed Aliakbar Safavi, University of Shiraz Mohammad Reza Salehi, Shiraz University of Technology Hadi Seyedarabi …

A Abdipour, A Aghagolzadeh, V Ahmadi, MA Badamchizadeh, M Ehsan, ...
Journal Papers , , {Pages }

Abstract

Multi-Objective Optimization of Distribution Networks Via Daily Reconguration

M Razavi, H Momeni, MR Haghifam, S Bolouki
Journal Papers , , {Pages }

Abstract

A Bayesian Framework for Large-Scale Identification of Nonlinear Hybrid Systems

A Madary, HR Momeni, A Abate, KG Larsen
Journal Papers , , {Pages }

Abstract

P148 Faster recovery of stroke patients through alternative electrical stimulation and rehabilitation movement frequency matching

M Rostami, Z Nasimi, M Mehrpour, M Barzegar, K Masoumzadeh Khalkhali, A Ghorbani, H Momeni, H Saeedi, S Ozgoli
Journal PapersClinical Neurophysiology , Volume 131 , Issue 4, 2020 April 1, {Pages e97 }

Abstract

Objectives: In this work, we propose a unique non-invasive treatment method based on neuroplasticity and Transcranial Alternating Current Stimulation (tACS) combined with traditional physical therapy where we aim to match the tACS frequency with the mechanical movement frequency of the rehabilitation. This method is durable and reproducible and at the same time, provides faster recovery for stroke patients and ultimately reduces the medical costs.Method: In this study, we recruited and examined a total of 3 persons (72, 68, 59 years old) who were the subject of stroke within the past 6 months. We applied 3 types of therapy, the first patient only received traditional physical therapy. The second patient received tACS with arbitrary frequenc

Analyzing the Advantage of Combination of Density Forecasts in Tehran Stock Exchange

S Raheleh Shahrokhi, Hamid Khaloozadeh, HamidReza Momeni
Journal Papers???????????????????????????????????????????????????? ???????????????????????????? ???????? ???????????????????????????????????????? ????????????????????????????????????????????, ???????????????????????????? ???????????? ??????????????????????????????????? , 2020 May 30, {Pages }

Abstract

Today, stock market plays a key role in the economy of any country and is considered as one of the growth indicators of any economy. Gaining the skills of gathering and analyzing data simultaneously, as well as using this knowledge in economic investigations, make time and precision factors to be the drawcard of any investor in competition with others. Therefore, having a predictive approach with the lowest degree of error will lead to smarter management of resources. Due to the complex and stochastic nature of the stock market, conventional forecasting approaches in this field have usually faced serious challenges, most notably losing the robustness when the data type changed over time. Moreover, by focusing on point forecasting, some usef

Robust tube–based model predictive control of piecewise affine systems with enlarging the region of attraction

Yahay Abbasi, Hamidreza Momeni, Amin Ramezani
Journal PapersJournal of Vibration and Control , 2020 June 10, {Pages 1.0775463209e+15 }

Abstract

This study addresses robust regulation problem for piecewise affine systems with bounded additive disturbances. Robust tube–based model predictive control strategy is used to separate the nominal system from the uncertain system and then maintain the disturbed trajectory of the uncertain system in a tube around the nominal system trajectory. Accordingly, an algorithm is proposed based on robust tube–based model predictive control strategy to enlarge the region of attraction without increasing the prediction horizon by changing the terminal constraint set. This algorithm enlarges the region of attraction without computational complexity of increasing receding horizon. Simulation examples, including two different case studies, are given t

A Computationally Efficient Robust Tube-Based MPC for Tracking of Linear Systems

Y Abbasi, HR Momeni, A Ramezani
Journal PapersIranian Journal of Science and Technology, Transactions A: Science , 2020 August 29, {Pages 11-Jan }

Abstract

This paper addresses a computationally efficient robust tube-based model predictive control (RTBMPC) strategy of linear systems in the presence of bounded disturbance. In the RTBMPC strategy, a nominal system is introduced by ignoring the disturbances of uncertain system, and then the uncertain system will be controlled in a robust manner through its nominal system as well as an additional feedback term which rejects a bounded additive disturbance. In this paper, the tracking problem is converted into the regulation problem by introducing an extra system called regulation nominal system that its constraints are translated from tracking into regulation. It leads to a reduction in complexity of the objective function and simplification of dri

Multi-Objective Optimization of Distribution Networks via Daily Reconfiguration

Seyed-Mohammad Razavi, Hamid-Reza Momeni, Mahmoud-Reza Haghifam, Sadegh Bolouki
Journal PapersarXiv preprint arXiv:2009.09472 , 2020 September 20, {Pages }

Abstract

This paper presents a comprehensive approach to improve the daily performance of an active distribution network (ADN), which includes renewable resources and responsive load (RL), using distributed network reconfiguration (DNR). Optimization objectives in this work can be described as (i) reducing active losses,(ii) improving the voltage profile,(iii) improving the network reliability, and (iv) minimizing distribution network operation costs. The suggested approach takes into account the probability of renewable resource failure, given the information collected from their initial state at the beginning of every day, in solving the optimization problem. Furthermore, solar radiation variations are estimated based on past historical data and t

Switched Adaptive Observer for Structure Identification in Gene Regulatory Networks

Mohammad Mohammadian, Hamid Reza Momeni, Javad Zahiri, Hazhar Sufi Karimi
Conference Papers2020 28th Iranian Conference on Electrical Engineering (ICEE) , 2020 August 4, {Pages 05-Jan }

Abstract

Gene regulatory networks (GRNs) perform a pivotal task in conducting cellular functions. Reconstruction of these complex networks is necessary to understand underlying mechanisms directing cellular behavior. This paper deals with structure identification for gene regulatory networks. To do this end, adaptive observer is employed to estimate unknown parameters. In this method, convergence of parameter estimation to the true values depends on persistency of excitation condition. Since many real gene networks don't satisfy this condition, we propose a new method to derive these parameters. This approach is based on introducing a switching mechanism in gene networks by using biochemical perturbations. Moreover, an adaptive observer for switchin

Non-intrusive Load Monitoring Using Water Consumption Patterns

Mohammad Mehdi Keramati, Elnaz Azizi, Hamid Reza Momeni, Mohammad Taghi Hamidi Beheshti, Sadegh Bolouki
Conference Papers2020 28th Iranian Conference on Electrical Engineering (ICEE) , 2020 August 4, {Pages 06-Jan }

Abstract

In this paper, we tackle the problem of non-intrusive load monitoring (NILM). The purpose of algorithm NILM, is to disaggregate the total power consumption of a house-hold into individual consumption of appliances by analyzing changes in the power signal using analytical methods. One of the main challenges in this field is the existence of appliances consuming nearly-equal power. Different studies tried to extract and define specific features for these appliances to overcome this challenge. In this research, we incorporate the water consumption patterns of appliances into our analysis to separate otherwise-indistinguishable appliance. More precisely, we perform NILM via an event-based multi-label classification method in which water consump

Brain State-Space Model Parameters Estimation During Non-Invasive Stimulation

Maryam Kiakojouri, Hamidreza Momeni, Amin Ramezani
Conference Papers2020 27th National and 5th International Iranian Conference on Biomedical Engineering (ICBME) , 2020 November 26, {Pages 305-311 }

Abstract

Brain dynamic modeling is essential in understanding neural mechanisms and also developing neurotechnologies such as closed-loop brain stimulation systems that are used in a broad range of neurological disorders. In this paper, intending to model brain’s dynamic in the presence of non-invasive stimulation, we present a dynamic model of electroencephalography (EEG) activity under transcranial magnetic stimulation (TMS). In this regard, using collected data from the conducted TMS/EEG experiment and performing special preprocessing steps on that we build a multi-input multi-output (MIMO) linear state-space model (LSSM) for the temporal dynamics of EEG signal. To further investigate LSSM's performance, we also use a multilayer perceptron (MLP

Comparison Between Performance of ANN-based Models and AR in Predicting EEG-triggered-TMS Time series

Maryam Kiakojouri, Mohammadreza Vahedpour, Hamidreza Momeni, Amin Ramezani
Conference Papers2020 6th Iranian Conference on Signal Processing and Intelligent Systems (ICSPIS) , 2020 December 23, {Pages 05-Jan }

Abstract

closed-loop brain stimulation as an emerged concept in brain stimulation techniques includes a crucial prediction block to predict the upcoming activity of the brain. In this paper, we propose to evaluate different artificial neural network (ANN) structure's ability in predicting neural signal in the presence of non-invasive stimulation. For this purpose, we implemented a brain stimulation experiment using transcranial magnetic stimulation (TMS) technique with a concurrent recording of electroencephalography (EEG) signal from the brain activity. Using this EEG-triggered-TMS signal, the prediction performance of ANN-based networks including multilayer perceptron (MLP), recurrent neural network (RNN), and a long short-term memory (LSTM) neura

INTELLIGENT FUZZY IMPROVEMENT OF NON-SINGULAR TERMINAL SLIDING-MODE CONTROL

Ali Esmaeili Jajarm, Amir H Abolmasoumi, Hamid R Momeni
Journal PapersMECHATRONIC SYSTEMS AND CONTROL , Volume 47 , Issue 1, 2019 January 1, {Pages 17-Dec }

Abstract

Mechatronic Systems and Control, Vol. 47, No. 1, 2019 INTELLIGENT FUZZY IMPROVEMENT OF NON-SINGULAR TERMINAL SLIDING-MODE CONTROL Ali Esmaeili Jajarm,∗ Amir H. Abolmasoumi,∗∗ and Hamid R. Momeni∗∗∗ Abstract This paper presents a novel hybrid method for non-linear control using non-singular terminal sliding mode control (NTSMC) together with a fuzzy inference system. This work obtains the sliding surface exponents to decrease both convergence time and output tracking error. The NTSMC method is applied to deal with the uncertainties in system and to improve the finite-time convergence of states to equilibrium point. To determine error exponents in non-linear sliding surface optimally, Takagi–Sugeno (T–S) fuzzy inference syste

Controlling Megawatt Class WECS by ANFIS Network Trained with Modified Genetic Algorithm

Mostafa Malmir, Hamidreza Momeni, Amin Ramezani
Conference Papers2019 27th Iranian Conference on Electrical Engineering (ICEE) , 2019 April 30, {Pages 939-943 }

Abstract

The generated mechanical power from Wind Energy Conversion System (WECS) is highly susceptible on wind energy absorbed by turbine blades whereas they can cause fluctuations in generated power. Designing a controller for WECS that leads to smooth generated mechanical power as well as high efficiency even with the presence of low wind speeds can be a challenging problem. This paper addresses this challenge by applying a novel strategy for training ANFIS network as a controller to the WECS. We firstly introducing Genetic Algorithm and Modified Genetic Algorithm optimization methods for training the adaptive network and updating the parameters of ANFIS. Then we use this trained adaptive network as a pitch angle controller for wind turbine. Comp

An adaptive sliding mode approach for Markovian jump systems with uncertain mode-dependent time-varying delays and partly unknown transition probabilities

N Zohrabi, H Zakeri, AH Abolmasoumi, HR Momeni
Journal Papers , , {Pages }

Abstract

/pro/academic_staff/momeni_h/publication

دروس نیمسال جاری

  • كارشناسي ارشد
    كنترل چند متغيره ( واحد)
    دانشکده مهندسی برق و کامپیوتر، گروه كنترل
  • كارشناسي ارشد
    ابزار دقيق پيشرفته ( واحد)

دروس نیمسال قبل

  • كارشناسي ارشد
    شناسايي سيستم ( واحد)
    دانشکده مهندسی برق و کامپیوتر، گروه كنترل
  • كارشناسي ارشد
    اتوماسيون صنعتي ( واحد)
  • كارشناسي ارشد
    اتوماسيون صنعتي ( واحد)
  • 1399
    مهدوي راد, حميد
    اتوماسيون ساختمان با مصرف انرژي بهينه شده با استفاده از روش پيش بيني بار مصرفي منطبق بر يادگيري ژرف
  • رئیس دانشکده مهندسی برق و کامپیوتر
  • رئیس کمیسیون تخصصی هیات ممیزه در گروه مهندسی برق و کامپیوتر و صنایع
  • مدیر گروه کنترل
  • هیات تحریریه مجله برق مدرس
  • عضو ورئیس کمیسیون گروه مهندسی برق کامپیوتر،صنایع و رشته های مرتبط هیات ممیزه دانشگاه
  • عضو کمیسیون برنامه ریزی جامع آموزشی دانشگاه
  • مدیر گروه کنترل
  • رئیس بخش برق
  • استاد نمونه دانشگاه در سال 1387
  • برنده جایزه آموزشی جبه دار از طرف موسسه IEEE شاخه ایران

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