Osama Ali Awad
@coie-nahrain.edu.iq
Systems engineering department/ college of Information Engineering
Nahrain University
EDUCATION
Ph.D in Control and Automation 2005 UOT
MSc in Control and Instrumentation 1982 UOT
BSc in Control and Systems 1978 UOT
RESEARCH INTERESTS
NCS
Soft Computing
Nonlinear Control
WSN
Scopus Publications
Scopus Publications
Israa Laith Salim, Osama Ali Awad, and Ali Sadeq Abdulhadi
IEEE
Affective Computing plays a crucial role in the Human-Computer Interaction (HCI) field by enabling computers to recognize, interpret, process, and simulate emotions evoked by positive/negative events, objects, or situations. It presents new avenues for applications ranging from personalized user interfaces to mental health monitoring. In this study, an affective computing system for human emotion recognition is developed by measuring the electrical activity of brain, Electroencephalogram (EEG) signals for 15 participants were recorded. Using Machine Learning (ML) algorithms to classify emotional states into three emotion dimensions: valence, arousal, and dominance. Two ML algorithms, Naïve Bayes (NB) and Artificial Neural Network (ANN) are exploited. The system also validated with EEG data from the public DREAMER dataset and compared with recorded data. Results demonstrate the feasibility and effectiveness of the proposed EEG-based affective computing system in accurately identifying and categorizing emotions, leveraging the designed ANN classifier; a maximum accuracy of 95.61% is achieved.
Yousif Safaa Alobaidy and Osama Ali Awad
Institute of Advanced Engineering and Science
In this paper, we present a real-time optimized fuzzy fuzzy proportional integral derivative (FPID)-controlled wireless networked system for a high-torque direct current (DC) motor. The main challenge faced by such systems is the delay in the wireless networked control system (WNCS). We employed a powerful FPID controller tuned using particle swarm optimization (PSO) technique to compensate for the delay. The system is tested on a network using the TrueTime simulator with different parameters. The results show that the system exhibits a very stable response, with the FPID controller compensating for the delay effectively. Increasing the number of nodes negatively impacts the system's performance, resulting in higher overshoot, longer settling time, and longer rise time. Moreover, the choice of bandwidth share and sampling time significantly affects the system's stability and real-time response. The use of transmission control protocol/internet protocol (TCP/IP) or user datagram protocol (UDP) protocols with Node MCU is necessary to transfer data from the Arduino Microcontroller to MATLAB, as MATLAB TrueTime simulator does not support direct serial communication. In conclusion, this study highlights valuable insights into the performance of the proposed system, demonstrating the need for further improvements in the system's design and control algorithms to achieve stable operation.
Israa Laith Salim, Osama Ali Awad, and Ali Sadeq Abdulhadi Jalal
IEEE
Autism Spectrum Disorder (ASD) impacts brain development, leading to social communication challenges and interaction. Researchers are increasingly exploring using Artificial Intelligence (AI) to diagnose ASD, interpret their emotions, and search for effective change interventions. This study investigates computer-aided ASD emotion recognition using electroencephalography (EEG) signals. The proposed method implements a four-level Discrete Wavelet Transform (DWT) for feature extraction and an Artificial Neural Network (ANN) to classify three dimensions of emotions: valence, arousal, and dominance. The model achieved 83% accuracy for valence and 96% for arousal and dominance. These findings hold potential for developing an adaptable closed-loop ASD intervention system. In conclusion, EEG-based emotion recognition using DWT and ANN appears promising for identifying emotional challenges in autism. However, further research is needed, considering limitations like sample size and static stimuli.
Yousif Safaa Sadi and Osama Ali Awad
IEEE
Real-Time wireless networked control systems (WNCS) are commonly used in various applications, including wheelchairs. However, these systems often suffer from a delay issue caused by the randomly generated delay accompanying the network, which can make the system response sluggish and unstable in some cases. This delay issue is a significant problem that needs to be addressed because it affects the system's performance and reliability. Therefore, this paper proposes a solution to the delay issue by utilizing a Fuzzy Proportional-Integral-Derivative (PID) controller to control a high-torque Real-Time Direct Current motor, commonly used in wheelchairs while also checking for wireless network connectivity. To transfer the data from Arduino Microcontroller to MATLAB, Transmission Control Protocol/Internet Protocol (TCP/IP) or User Datagram Protocol (UDP) with Node MCU will be used since MATLAB Truetime, which will be used to simulate Wireless Network, does not work with Direct Serial Communication. The simulation results show that the proposed system can efficiently control the Real-Time DC motor in real-time with the best settling time of 0.5371 for 0.01 sec sampling time and 0.5371-sec settling time with 0.001 sampling time. The proposed solution addresses a significant problem in WNCS and can contribute to developing more reliable and efficient Real-Time wireless networked control systems.
Osama Ali Awad and Isra'a Laith Salim
University of Baghdad College of Science
The use of a communication network in the closed loop control systems has many advantages such as remotely controlling equipment, low cost, easy to maintenance, efficient information transmission, etc. However, the Networked Control System (NCS) has many drawbacks, such as network-induce end-to-end time delay and packet loss, which lead to significant degradation in controller performance and may result in instability. Aiming at solving performance degradation in NCS, this paper propose to take the advantages and strength of the conventional Proportional-Integral-Derivative (PID), Fuzzy Logic (FL), and Gain Scheduling (GS) fundamentals to design a Fuzzy-PID like-Gain Scheduling (F-PID-GS) control technique, which has been proved to be effective in obtaining better performance. The True Time toolbox is used to establish the simulation model of the NCS. Ethernet as a communication network is simulated for different load conditions and random packet loss. The design approach is tested on a second order stepper motor. The results obtained show the effectiveness of the proposed approach in improving the overall system performance.
O. A. Awad and Mais Monqith
Zeyad Abdulwahid Karam and Osama A. Awad
Periodica Polytechnica Budapest University of Technology and Economics
Improving the dynamic performance of an automobile suspension system is considered as the main demand for comfortable and safe passenger travelling. From all previously proposed and implemented works, it is noticed that there are other factors that need to be considered to raising the car holding and stability in the road for improved passenger comfort when travelling. The minimization of car body displacement and oscillation time after exposure to road disturbances have been adopted in this work due to their contribution in raising the car holding and stability. The improvement in these features was maintained via a robust control methodology. The Fractional Order PID controller tuned by the Whales Optimization Algorithm (WOA) and Particle Swarm Optimization (PSO) algorithm is suggested in this work as a robust controller to reduce the effect of these demerits. In this paper, an active quarter car suspension nonlinear system is designed for the presented goals using a robust controller. Minimizing the displacement of the car body and reducing the damping frequency are achieved via a nonlinear control strategy using the fractional order PID controller, which can maintain the required characteristics. Tuning the parameters of the FOPID controller is performed by using the Whales Optimization Algorithm (WOA). Robustness of the FOPID controller is examined and proved to withstand a system parameter variation of ±12 % in all system parameters and a maximum of ±80 % in controller parameter variation. Simulation outcomes also indicate a considerably improved performance of the active suspension system with the fractional order PID controller over the traditional PID.
Subhi Aswad Mohammed, Osama Ali Awad, and Abdulkareem Merhej Radhi
Institute of Advanced Engineering and Science
This paper presents a design, simulation and performance evaluation of an optimized model for the Heating, Ventilation and Air-Conditioning (HVAC) systems using intelligent control algorithm. Fanger’s comfort method and genetic algorithms were used to obtain the optimal and initial values. The heat transmission coefficient between internal and external environments were determined depending on several inputs and factors acquired via supervisory control and data acquisition (SCADA) system sensors. The main feature of the real-time model is the prediction of the internal buildings environment, in order to control HVAC system for indoor environment and to utilize the optimum power consumed depending on optimized air temperature value. The predicted air temperature value and Predictive Mean Vote (PMV) value was applied using intelligent algorithm to obtain an optimal comfort level of the air temperature. The optimized air temperature value can be used in HVAC system controller to ensure that the temperature of indoor can reach a specific value after a known period of time. The use of genetic algorithm (GE) ensures that the used power is well below its peak value and maintains the comfort of the user’s environment.
Osama A. Awad and Israa Laith
Springer International Publishing
The use of a communication network in the closed-loop control systems has many advantages such as remotely controlling equipment, low cost, easy to maintenance, efficient information transmission, etc. However, the Distributed or Networked Control Systems (NCS) has many drawbacks, such as network-induce end-to-end time delay and packet loss, which lead to a significant degradation in controller performance and may result in instability. Aiming at solving performance degradation in NCS, this paper propose to take the advantages and strength of the conventional Proportional-Integral-Derivative (PID), Fuzzy Logic (FL), and Gain Scheduling (GS) fundamentals to design a Fuzzy-PID like-Gain Scheduling (F-PID-GS) control technique, which has been proved to be effective in obtaining better performance. The TrueTime toolbox is used to establish the simulation model of the NCS. Ethernet as a communication network is simulated for different load conditions and random packet loss. The design approach is tested on a second-order stepper motor. The results obtained show the effectiveness of the proposed approach in improving the overall system performance.
Ali Mustafa, Mohammed I. A al-Nouman, and Osama A. Awad
IEEE
The cases of kidnapping and vehicle theft is increasing continuously. Therefore the need for mobile applications to track the vehicle in real-time become very important, so the user can track and monitor the vehicle using the mobile phone. This type of system sends large data to the server/cloud every day, which will increase the expenses every month for transmitting the data to this cloud/server. This paper introduced an embedded system that designed and implemented for vehicle tracking based on an android application, the main contribution of this paper is to reduce the data that sent from the embedded system in the vehicle to the cloud server via picking only necessary data for vehicle tracking from Global Position System GPS and decreasing the number of Hypertext Transfer Protocol HTTP request that transmitted to the cloud server by construing the transmission of information with the movement of vehicles. This system is divided into three parts: embedded system that is attached with the vehicle, cloud/server part which has the database of every single move every car did, and the monitoring part which is the main user interface so they can monitor the vehicle.