Khan, Muhammad Umer

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Profile URL
https://hdl.handle.net/20.500.14411/6656
Name Variants
Khan, Muhammad Umer
K.,Muhammad Umer
Muhammad Umer, Khan
Khan,Muhammad Umer
M.U.Khan
M., Khan
M.,Khan
Khan U.
Khan M.
Khan,M.U.
M. U. Khan
Umer Khan M.
K., Muhammad Umer
Muhammad Umer Khan
Khan, Umer
Khan, Muhammed Umer
Khan, M. U.
Khan, M.U
Job Title
Yardımcı Doçent
Email Address
umer.khan@atilim.edu.tr
Main Affiliation
Mechatronics Engineering
Status
Website
ORCID ID
0000-0002-9195-3477
Scopus Author ID
57209876827
Turkish CoHE Profile ID
277006
Google Scholar ID
8h-JrH8AAAAJ
WoS Researcher ID
N-5478-2016

Sustainable Development Goals

NO POVERTY1
NO POVERTY
0
Research Products
ZERO HUNGER2
ZERO HUNGER
4
Research Products
GOOD HEALTH AND WELL-BEING3
GOOD HEALTH AND WELL-BEING
1
Research Products
QUALITY EDUCATION4
QUALITY EDUCATION
0
Research Products
GENDER EQUALITY5
GENDER EQUALITY
0
Research Products
CLEAN WATER AND SANITATION6
CLEAN WATER AND SANITATION
0
Research Products
AFFORDABLE AND CLEAN ENERGY7
AFFORDABLE AND CLEAN ENERGY
4
Research Products
DECENT WORK AND ECONOMIC GROWTH8
DECENT WORK AND ECONOMIC GROWTH
0
Research Products
INDUSTRY, INNOVATION AND INFRASTRUCTURE9
INDUSTRY, INNOVATION AND INFRASTRUCTURE
1
Research Products
REDUCED INEQUALITIES10
REDUCED INEQUALITIES
0
Research Products
SUSTAINABLE CITIES AND COMMUNITIES11
SUSTAINABLE CITIES AND COMMUNITIES
0
Research Products
RESPONSIBLE CONSUMPTION AND PRODUCTION12
RESPONSIBLE CONSUMPTION AND PRODUCTION
0
Research Products
CLIMATE ACTION13
CLIMATE ACTION
0
Research Products
LIFE BELOW WATER14
LIFE BELOW WATER
0
Research Products
LIFE ON LAND15
LIFE ON LAND
0
Research Products
PEACE, JUSTICE AND STRONG INSTITUTIONS16
PEACE, JUSTICE AND STRONG INSTITUTIONS
0
Research Products
PARTNERSHIPS FOR THE GOALS17
PARTNERSHIPS FOR THE GOALS
1
Research Products
Documents

38

Citations

641

h-index

13

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Documents

30

Citations

476

Go to WoS profile
Scholarly Output

38

Articles

15

Views / Downloads

185/1662

Supervised MSc Theses

11

Supervised PhD Theses

0

WoS Citation Count

253

Scopus Citation Count

374

Patents

0

Projects

0

WoS Citations per Publication

6.66

Scopus Citations per Publication

9.84

Open Access Source

10

Supervised Theses

11

JournalCount
Applied Sciences2
2018 14th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications, MESA 2018 -- 14th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications, MESA 2018 -- 2 July 2018 through 4 July 2018 -- Oulu -- 1391112
2019 2nd International Conference on Communication, Computing and Digital Systems, C-CODE 2019 -- 2nd International Conference on Communication, Computing and Digital Systems, C-CODE 2019 -- 6 March 2019 through 7 March 2019 -- Islamabad -- 1469971
2020 7th International Conference on Electrical and Electronics Engineering, ICEEE 2020 -- 7th International Conference on Electrical and Electronics Engineering, ICEEE 2020 -- 14 April 2020 through 16 April 2020 -- Antalya -- 1604501
2021 IEEE International Conference on Robotics, Automation and Artificial Intelligence, RAAI 2021 -- 2021 IEEE International Conference on Robotics, Automation and Artificial Intelligence, RAAI 2021 -- 21 April 2021 through 23 April 2021 -- Virtual, Online -- 1767941
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Now showing 1 - 10 of 38
  • Thumbnail Image
    Article
    Citation - WoS: 1
    Citation - Scopus: 3
    Investigation of Harmonic Losses To Reduce Rotor Copper Loss in Induction Motors for Traction Applications
    (Multidisciplinary Digital Publishing Institute (MDPI), 2025) Siddique, M.S.; Ertan, H.B.; Alam, M.S.; Khan, M.U.
    The focus of this paper is to seek means of increasing induction motor efficiency to a comparable level to a permanent magnet motor. Harmonic and high-frequency losses increase the rotor core and copper loss, often limiting IM efficiency. The research in this study focuses on reducing rotor core and copper losses for this purpose. An accurate finite element model of a prototype motor is developed. The accuracy of this model in predicting the performance and losses of the prototype motor is verified with experiments over a 32 Hz–125 Hz supply frequency range. The verified model of the motor is used to identify the causes of the rotor core and copper losses of the motor. It is found that the air gap flux density of the motor contains many harmonics, and the slot harmonics are dominant. The distribution of the core loss and the copper loss is investigated on the rotor side. It is discovered that up to 35% of the rotor copper losses and 90% rotor core losses occur in the regions up to 4 mm from the airgap where the harmonics penetrate. To reduce these losses, one solution is to reduce the magnitude of the air gap flux density harmonics. For this purpose, placing a sleeve to cover the slot openings is investigated. The FEA indicates that this measure reduces the harmonic magnitudes and reduces the core and bar losses. However, its effect on efficiency is observed to be limited. This is attributed to the penetration depth of flux density harmonics inside the rotor conductors. To remedy this problem, several FEA-based modifications to the rotor slot shape are investigated to place rotor bars deeper than the harmonic penetration. It is found that placing the bars further away from the rotor surface is very effective. Using a 1 mm sleeve across the stator’s open slots combined with a rotor tapered slot lip positions the bars slightly deeper than the major harmonic penetration depth, making it the optimal solution. This reduces the bar loss by 70% and increases the motor efficiency by 1%. Similar loss reduction is observed over the tested supply frequency range. © 2025 by the authors.
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    Master Thesis
    Derin öğrenme ile orman yangını tespiti
    (2024) Özel, Berk; Khan, Muhammad Umer
    Yangın algılama sistemleri can güvenliği ve maddi hasarın en aza indirilmesi açısından kritik öneme sahiptir. Bu tür sistemlerin hayati önem taşıdığı alanlardan biri de orman yangınlarıdır. Son yıllarda büyüklük, süre ve tahribat açısından rekor sayıda orman yangını yaşandı. Duman veya ısı sensörleri gibi geleneksel yangın algılama yöntemlerinin sınırlamaları vardır ve bu da ileri teknolojilere dayalı yenilikçi yaklaşımların ortaya çıkmasına neden olur. Bu tez, orman yangını tespiti için bir derin öğrenme modeli olan ResNet ile birlikte Batch-Instance Normalizasyonunun uygulanmasını incelemektedir. Çalışma, Batch-Instance Normalizasyonunun performansını diğer normalleştirme yaklaşımlarıyla karşılaştırmaktadır. Bu çalışmada modelin eğitimi için orman yangını veri seti kullanılmıştır. Bu veri seti 4609 görsel içermektedir. Bu görseller 2120 Yangın, 2499 yangın içermeyen görselden oluşmaktadır. ResNet modeli sekiz farklı optimize edici ile test edilmiş ve en iyi sonuçları veren ile eğitilmiştir. Deneyler, normalizasyon tekniklerinin ve optimize edicilerin yangın tespitinin doğruluğu üzerindeki etkisini değerlendirmektedir. Sonuçlar, tek üstel düzeltmeyle Batch-Instance Normalizasyonunun modelin doğruluğunu önemli ölçüde artırdığını göstermektedir. Deneyde model, 96.14% F1 skoruna, 96.56% doğruluğa ve 99.49% kesinlik değerlerine ulaşmıştır. Diğer yaklaşımlardan minimum %1 doğruluk farkı, %0,6 F1 skor farkı, %1,05 kesinlik farkı elde edilmiştir. Derin öğrenmenin yeteneklerini Batch-Instance Normalizasyonunuyla birleştirmek, orman yangını tespiti için umut verici ve etkili bir çözüm ortaya koydu.
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    Article
    Citation - WoS: 5
    Citation - Scopus: 4
    Avoiding Contingent Incidents by Quadrotors Due To One or Two Propellers Failure
    (Public Library Science, 2023) Altinuc, Kemal Orcun; Khan, Muhammad Umer; Iqbal, Jamshed
    With the increasing impact of drones in our daily lives, safety issues have become a primary concern. In this study, a novel supervisor-based active fault-tolerant (FT) control system is presented for a rotary-wing quadrotor to maintain its pose in 3D space upon losing one or two propellers. Our approach allows the quadrotor to make controlled movements about a primary axis attached to the body-fixed frame. A multi-loop cascaded control architecture is designed to ensure robustness, stability, reference tracking, and safe landing. The altitude control is performed using a proportional-integral-derivative (PID) controller, whereas linear-quadratic-integral (LQI) and model-predictive-control (MPC) have been investigated for reduced attitude control and their performance is compared based on absolute and mean-squared error. The simulation results affirm that the quadrotor remains in a stable region, successfully performs the reference tracking, and ensures a safe landing while counteracting the effects of propeller(s) failures.
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    Master Thesis
    Derin Öğrenme ile Orman Yangını Tespiti
    (2024) Özel, Berk; Khan, Muhammad Umer
    Fire detection systems are critical for safeguarding lives and minimizing property damage. One of the key areas where such systems are vital are forest fires. In recent years, there have been several record-breaking forest fires in terms of size, duration, and destruction. Traditional methods of fire detection, such as smoke or heat sensors, have their limitations, leading to the emergence of innovative approaches based on advanced technologies. This thesis examines the application of Batch-Instance Normalization combined with ResNet, a deep learning model for wildfire detection. The study compares the performance of Batch-Instance Normalization with other normalization approaches. In this study, a forest fire dataset is used which is taken from the Kaggle for training the model. The Dataset includes 4609 images, 2120 Fire and 2499 Non-Fire images. The ResNet model is tested with eight different optimizers and trained with the one that gives the best results. The experiments evaluate the impact of normalization techniques and optimizers on the accuracy of wildfire detection. The results show that Batch-Instance Normalization with single exponential smoothing significantly improves the accuracy of the model. It attains F1-score of 96.14%, accuracy of 96.56%, and precision of 99.49%. A minimum 1%, accuracy difference, %0.6 F1 score difference, %1.05 precision difference were obtained from other normalization methods. Combining the capabilities of deep learning with the innovative Batch-Instance Normalization has demonstrated a promising and effective solution for wildfire detection.
  • Thumbnail Image
    Conference Object
    Citation - Scopus: 10
    Biomechanical Design and Control of Lower Limb Exoskeleton for Sit-To and Stand-To Movements
    (Institute of Electrical and Electronics Engineers Inc., 2018) Qureshi,M.H.; Masood,Z.; Rehman,L.; Owais,M.; Khan,M.U.
    In this paper, we present design and development phase of lower limb robotic exoskeleton that can assist paralyzed individuals. Motion of the human wearing exoskeleton is introduced by actuators. Both exoskeleton legs are attached to the supporting frame by passive universal joints. The exoskeleton provides 3 DOFs per limb of which two joints are active and one passive. The control actions i.e., sit-to-stand and stand-to-sit movements are triggered using Double Pole Double Throw (DPDT) toggle switch. The control scheme is implement using Switch control method and the feedback is provided by means of current measurement. This assistive device can be utilized for the disabled persons. The simulation results are provided that evaluates the performance of the control actions on exoskeleton. © 2018 IEEE.
  • Thumbnail Image
    Article
    Utilization of Robotics for Solar Panel Cleaning and Maintenance
    (2019) Park, Haon; Öztürk, Abdullah; Park, Hajun; Khan, Muhammed Umer
    In this study, a portable and low-cost solar panel cleaning robot with a functioning to blowaway dust was designed and built to incur labor costs.The robot is service effective, environmentallyfriendly, energy independent, self-automated, long durable, and cost-effective. After cleaning operation,output voltage and current in solar panel increased by 8.02% and 18.78%, respectively. Moreover, theimage processing with the photos taken by a camera fixed on the robot made classification according tocolor changes in the solar panel. Therefore, it can be concluded that the automated and multifunctionalrobot may facilitate the solar panel surface cleaning and be an applicable maintenance method throughremote monitoring of the surface conditions.
  • Thumbnail Image
    Conference Object
    Citation - Scopus: 9
    Attitude Control of Quad-Copter Using Deterministic Policy Gradient Algorithms (dpga)
    (Institute of Electrical and Electronics Engineers Inc., 2019) Ghouri,U.H.; Zafar,M.U.; Bari,S.; Khan,H.; Khan,M.U.
    In aerial robotics, intelligent control has been a buzz for the past few years. Extensive research efforts can be witnessed to produce control algorithms for stable flight operation of aerial robots using machine learning. Supervised learning has the tendency but training an agent using supervised learning can be a tedious task. Moreover, the data gathering could be expensive and always prone to inaccuracies due to parametric variations and system dynamics. An alternative approach is to ensure the stability of the aerial robots with the help of Deep Re-inforcement Learning (DRL). This paper deals with the intelligent control of quad-copter using deterministic policy gradient algorithms. In this research, state of the art Deep Deterministic Policy Gradient (DDPG) and Distributed Distributional Deep Deterministic Policy Gradient (D4PG) algorithms are employed for attitude control of quad-copter. An open source simulation environment GymFC is used for training of quad-copter. The results for comparative analysis of DDPG D4PG algorithms are also presented, highlighting the attitude control performance. © 2019 IEEE.
  • Thumbnail Image
    Article
    Citation - WoS: 2
    Citation - Scopus: 1
    Autonomous Landing of a Quadrotor on a Moving Platform Using Motion Capture System
    (Springer, 2024) Qassab, Ayman; Khan, Muhammad Umer; Irfanoglu, Bulent
    This paper investigates the challenging problem of the autonomous landing of a quadrotor on a moving platform in a non-cooperative environment. The limited sensing ability of quadrotors often hampers their utilization for autonomous landing, especially in GPS-denied areas. The performance of motion capture systems (MCSs) in many application areas is the motivation to utilize them for the autonomous take-off and landing of the quadrotor in this research. An autonomous closed-loop vision-based navigation, tracking, and control system is proposed for quadrotors to perform landing based upon Model Predictive Control (MPC) by utilizing multi-objective functions. The entire process is posed as a constrained tracking problem to minimize energy consumption and ensure smooth maneuvers. The proposed approach is fully autonomous from take-off to landing; whereas, the movements of the landing platform are pre-defined but still unknown to the quadrotor. The landing performance of the quadrotor is tested and evaluated for three different movement patterns: static, square-shaped, and circular-shaped. Through experimental results, the pose error between the quadrotor and the platform is measured and found to be less than 30 cm. Introducing a holistic vision system for quadrotor navigation, tracking, and landing on stationary/moving platforms. Proposing an energy-efficient, smooth, and stable MPC controller validated by Lyapunov analysis. Validating the adept tracking and safe landings of the quadrotor on stationary/moving platforms through three diverse experiments.
  • Thumbnail Image
    Article
    Citation - WoS: 25
    Citation - Scopus: 33
    Hybrid Eeg-Fnirs Bci Fusion Using Multi-Resolution Singular Value Decomposition (msvd)
    (Frontiers Media Sa, 2020) Khan, Muhammad Umer; Hasan, Mustafa A. H.
    Brain-computer interface (BCI) multi-modal fusion has the potential to generate multiple commands in a highly reliable manner by alleviating the drawbacks associated with single modality. In the present work, a hybrid EEG-fNIRS BCI system-achieved through a fusion of concurrently recorded electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) signals-is used to overcome the limitations of uni-modality and to achieve higher tasks classification. Although the hybrid approach enhances the performance of the system, the improvements are still modest due to the lack of availability of computational approaches to fuse the two modalities. To overcome this, a novel approach is proposed using Multi-resolution singular value decomposition (MSVD) to achieve system- and feature-based fusion. The two approaches based up different features set are compared using the KNN and Tree classifiers. The results obtained through multiple datasets show that the proposed approach can effectively fuse both modalities with improvement in the classification accuracy.
  • Thumbnail Image
    Master Thesis
    Pervane Arızası Durumunda Kuadrotorun Stabilitesini Sağlamak
    (2021) Altınuç, Kemal Orçun; Khan, Muhammad Umer
    Bu tezde, sabit kanatlı bir kuadrotorun, yalpalama hareketinden feragat ederek bir veya iki zıt pervanesini kaybetmesine rağmen 3 boyutlu uzayda konumunu koruması için bir çözüm sunulmaktadır. Bu kontrol stratejisinde, kuadrotor, araca göre sabitlenmiş bir birincil eksen etrafında döner ve bu ekseni ötelenme hareketi gerçekleştirmek için değiştirir. Bir pervane veya iki karşıt pervane kaybetmesine rağmen kuadrotorun tutumunu ve konumunu stabilize etmek için çok döngülü bir kademeli kontrol kanunu geliştirilmiştir. İlk olarak, motor arıza senaryoları için denge çözümleri hesaplanır. Daha sonra, bir referans ve bir özel kuadrotor için doğrusallaştırılmış sistem etrafında bir azaltılmış durum denetleyicisi ve konum denetleyicisi tasarlanır. Matlab/Simulink ve Matlab/Simscape üzerinde simülasyonlar yapılarak sonuçlar karşılaştırılır. Son olarak, özel yapım bir kuadrotorun CAD çizimleri, kuadrotorun eylemsizlik momentini hesaplamak için kullanılır ve sonuçlar Çift Telli Pendulum deneyi ile doğrulanır. Sonuçlar, kuadrotorun pervane arızası durumunda stabiliteye ulaştığını göstermektedir.