Dr Ali Marzoughi :Engineering Institute of Technology

Dr Ali Marzoughi is a professional engineer with a PhD in robotics and automatic control from the University of New South Wales. He joined the oil and gas industry after finishing his undergraduate as an instrumentation engineer and after a few years, he was promoted to project manager of electrical and instrumentation in several EPC projects. He has been actively involved in R&D and academics while he was working in the industry. Ali has been working in several companies nationally and internationally in different positions for more than 20 years and he has been cooperating with EIT as unit coordinator, lecturer, and thesis supervisor since 2019.

Arithmetic mean-based decision-making algorithm for obstacle avoidance and multiple intruder detection

21 January, 2021

This paper demonstrates a decentralized strategy of an arithmetic mean-based navigation algorithm for a group of mobile robots. The aim is to have them navigate through an unknown environment surrounded by obstacles to detect and follow multiple invading intruders. The suggested navigation strategy ensures that the mobile robots safely manoeuvre...Read More

Autonomous Navigation of a Team of Unmanned Surface Vehicles for Intercepting Intruders on a Region Boundary

4 January, 2021

We study problems of intercepting single and multiple invasive intruders on a boundary of a planar region by employing a team of autonomous unmanned surface vehicles. First, the problem of intercepting a single intruder has been studied and then the proposed strategy has been applied to intercepting multiple intruders on...Read More

Switching Navigation for a Fleet of Mobile Robots in Multi-Obstacle Regions

26 January, 2019

This paper presents a collision-free navigation control algorithm for a fleet of mobile robots to traverse an unknown obstacle-ridden environment. The proposed leader-follower-based navigation rule guarantees that the robots maintain the minimum-allowed distance from the obstacles while in motion. In this algorithm, the leader plans the safest path based on...Read More

Decentralised Navigation Control of a Multi-Robot Team to Minimising Energy Consumption in an Unknown Obstacle-Ridden Area

7 October, 2018

This study presents a decentralised navigation algorithm for a team of mobile robots to traverse an unknown obstacle-ridden environment to detect and trap a target located in the region. The proposed navigational strategy guarantees that the robots maintain the minimum distance allowed to the obstacles while avoiding them to trap...Read More

Collision Free Navigation of a Multi-Robot Team for Intruder Interception

7 September, 2018

In this report, we propose a decentralised motion control algorithm for the mobile robots to intercept an intruder entering (k-intercepting) or escaping (e-intercepting) a protected region. In continuation, we propose a decentralized navigation strategy (dynamic-intercepting) for a multi-robot team known as predators to intercept the intruders or in the other...Read More

Distributed control of a robotic network for protection of a region from intruders

26 March, 2018

This paper addresses a problem of intruder interception on the boundary of a protected region through the use of a network of mobile robots. A necessary and sufficient condition for the existence of a solution of this problem is obtained. We propose a decentralized motion control algorithm for the mobile...Read More

Navigating a mobile robot to avoid moving obstacles using virtual source/sink force field

26 March, 2018

This paper proposes a novel navigation strategy for a unicycle mobile robot in a cluttered area with moving obstacles based on the virtual field force algorithm. We consider each obstacle as a virtual source and each obstacle free area between every two obstacles as a virtual sink, which exert repulsive...Read More

A decentralized position estimation switching algorithm to avoid a convex obstacle

11 September, 2017

We proposed a decentralized formation control method and a path planning for a mobile robotic network to avoid an obstacle in an environment without the possibility of collision between the teammates. We applied the leader-follower pattern where the leader estimates the safest path to maintain the minimum allowable distance with...Read More

Maximizing the probability of intrusion detection by a fleet of mobile robots using an intelligent game theoretic approach

11 September, 2017

This paper presents an intelligent game based decision-making algorithm (IGD) for a fleet of mobile robots to maximize the probability of detection in a limited area. The agents have the minimum communication or even no communication result from a jamming attack by a given hostile. Thus, we proved that the...Read More

Optimized proportional integral derivative (PID) controller for the exhaust temperature control of a gas turbine system using particle swarm optimization

16 January, 2012

In this paper, the particle swarm optimization (PSO) technique is used in optimising the proportional integral derivative (PID) controller parameters for the exhaust temperature control of a gas turbine system. The performance of the PID controller whose parameters are tuned based on the PSO method (PSO-PID) is compared with the...Read More

PERFORMANCE IMPROVEMENT OF A SINGLE SHAFT GAS TURBINE SYSTEM TEMPERATURE CONTROL USING PARTICLE SWARM OPTIMIZATION

27 March, 2011

Gas turbine has become increasingly popular in different areas of industry due to their lower greenhouse emission and higher efficiency compared to other types of engine such as diesel engines, especially when connected in a combined cycle setup. The control of gas turbine system, particularly its exhaust temperature control, is...Read More

A Decision Model for Estimating the Effort of Software Projects using Bayesian Theory

25 October, 2010

Usability of the e-government portal is a crucial factor that Function Point Analysis (FPA) is most used technique for estimating the size of a computerized business information system which was developed by Allan Albrecht. Various studies proposed new methods to extent FPA algorithm; mainly they tried to make it more...Read More

Professional Memberships	IEEE Member (Control system society, power electronics, robotics, and automation) Member of Institute of Instrumentation, Control and Automation (IICA)
Industry Affiliations	Dr. Ali Marzoughi was responsible for Electrical and Instrumentation engineering, electrical and instrumentation project manager, quality control and technical inspector, service engineer, and production supervisor in different national and international companies.
Administrative Responsibilities	UC/UL

DEng	Data-driven dynamic systems modelling and simulation ANN in dynamic systems performance prediction On application of neuromorphic control in computing, sensing, and actuating.
Master’s (completed):	Optimisation of energy consumption in Automated Guided Vehicles Biomimetic underwater robots using smart actuators (Modelling and Navigation Control) Reinforcement learning in robotics Improvement of control performance of a system
Recent Publications	Marzoughi, A. & Savkin, A. V. Autonomous Navigation of a Team of Unmanned Surface Vehicles for Intercepting Intruders on a Region Boundary. sensors 21, 16 (2021). Arif, M. U. & Marzoughi, A. Arithmetic mean-based decision-making algorithm for obstacle avoidance and multiple intruder detection. in 2020 Australian and New Zealand Control Conference, ANZCC 2020 (2020). doi:10.1109/ANZCC50923.2020.9318343. Marzoughi, A. Switching navigation for a fleet of mobile robots in multi-obstacle regions. Int. J. Mech. Eng. Robot. Res. 8, (2019). Marzoughi, A. Collision Free Navigation of a MultiRobot Team for Intruder Interception. https://arxiv.org/abs/1809.02319 (2018). Marzoughi, A. Decentralised Navigation Control of a Multi-Robot Team to Minimising Energy Consumption in an Unknown Obstacle-Ridden Area. in 2018 37th Chinese Control Conference (CCC) 4922–4927 (IEEE, 2018). Savkin, A. V et al. 2017 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND BIOMIMETICS, ROBIO 2017. Optimization 252, 257 (2018). Marzoughi, A. Maximizing the probability of intrusion detection by a fleet of mobile robots using an intelligent game theoretic approach. in 2017 36th Chinese Control Conference (CCC) 8342–8348 (IEEE, 2017). doi:10.23919/ChiCC.2017.8028678. Marzoughi, A. A decentralized position estimation switching algorithm to avoid a convex obstacle. in 2017 36th Chinese Control Conference (CCC) 6031–6036 (IEEE, 2017). doi:10.23919/ChiCC.2017.8028316. Marzoughi, A. Navigating a mobile robot to avoid moving obstacles using virtual source/sink force field. in 2017 IEEE International Conference on Robotics and Biomimetics (ROBIO) 344–349 (IEEE, 2017). doi:10.1109/ROBIO.2017.8324441. Savkin, A. V & Marzoughi, A. Distributed control of a robotic network for protection of a region from intruders. in 2017 IEEE International Conference on Robotics and Biomimetics (ROBIO) vol. 1 804–808 (IEEE, 2017). Marzoughi, A., Selamat, H., Fuarsquo, M. & Rahim, H. A. Optimized proportional integral derivative (PID) controller for the exhaust temperature control of a gas turbine system using particle swarm optimization. Int. J. Phys. Sci. 7, 720–729 (2012). Marzoughi, A., Salamat, H., Rahmat, M. & AbdulRahim, H. Optimized PID controller for the exhaust temperature control of a gas turbine system using particle swarm optimization. Int. J. Phys. Sci. 7, 720–729 (2012). Marzoughi, A. & Selamat, H. Performance improvement of a single shaft gas turbine system temperature control using particle swarm optimization. in Control design & optimization techniques: Series 1 81–105 (Penerbit Universiti Teknologi Malaysia, 2011). Rahim, H. A. et al. Control Design & Optimization Techniques: Series 1. (2011). Marzoughi, A. Optimization of Automatic Controller Design Coefficients. (2010). Marzoughi, F., Farhangian, M. M., Marzoughi, A. & Sim, A. T. H. A decision model for estimating the effort of software projects using Bayesian theory. in ICSTE 2010 – 2010 2nd International Conference on Software Technology and Engineering, Proceedings vol. 2 (2010). Marzoughi, A., Selamat, H. & Marzoughi, F. Application of particle swarm optimization approach to improve PID performance for a gas turbine temperature control system. in Proceeding, 2010 IEEE Student Conference on Research and Development – Engineering: Innovation and Beyond, SCOReD 2010 (2010). doi:10.1109/SCORED.2010.5704006.

Dr Ali Marzoughi

Biography

Publications and News