Group Research on Electrical, Electronic and Mechanical Engineering (GREEME)

About us

The Group Research on Electrical, Electronic and Mechanical Engineering (GREEME) combines the renowned professors and the selected, young scientists at Thai Nguyen University of Technology with the aim to promote the teaching, research, globalization and other academic activities of the university to be alive, up-to-date and more competitive not only within the country but also worldwide. With about fifteen professors and faculty members from different departments, the primary objective of GREEME is to provide the in-depth analysis and solutions of the practical problems in diverse fields, including electric energy systems, electronics and control systems, integrated circuits, and mechanics, etc. The members of GREEME are conducting multi-disciplinary research projects both within and across the boundary of the country.

GREEME also creates a dynamic environment and supports students within the university to pursue their ambition of study, and be informed of the state-of-the-art technologies and brings them to the current engineering problems in the real world. In addition, GREEME is expected to encourage the global collaboration with oversea universities, international professors and researchers around the world.

The members of GREEME will not stop exploring new frontiers in research and performing an excellent education.

Division of Electronics and Control Systems

Research areas

Our research areas mainly include:

Control theory

Despite widely used in industry, PID controller poses many drawbacks in modern control systems. Our research is to develop an advanced controller which is able to overcome the limitations of the conventional PID controller, e.g. trading-off between regulation and response time and particularly, to provide optimal control which usually cannot be obtained with PID.

Adaptive control

Adaptive control employs various techniques into the conventional PID controller in order to provide knowledge and information of the controlled system, by thus, improving the performance of the controller particularly with non-linearity, uncertainty and/or time-varying parameters.

System models and estimation theory are commonly used in adaptive controller, e.g. Linear Quadratic Gaussian (LQG), Neural Network (NN), Model Reference Adaptive System (MRAS) and Learning Feed-Forward Controller (LFFC). Our research has been applied to various industrial control systems in diverse fields such as load sharing of DC motors, electromechanical motion, and robotics, etc.

Machine learning

Machine learning, a part of Artificial Intelligence (AI), has got many scientific attentions today. The core of machine learning is dealing with the representation of data instances and the generalization which performs on unseen data instances. Several approaches for machine learning considered include artificial Neural Network, support vector machines, clustering, etc. Our research on machine learning has been applied in various problems of engineering, e.g. selection and recognition systems, etc.

Power electronics

Power electronics which are mainly based on semiconductor device are used ubiquitously in the modern life, ranging from small electric appliances such as computer, TV, fluorescent lamp, etc. to very large applications in power systems: DC/DC converter, DC/AC inverter in renewable energy systems or power quality device, e.g. Static Var Compensator (SVC) and Static Compensator (STATCOM), etc. Managing and controlling these devices to mitigate its consequence, particularly related to the quality and problems are of significant concern.

 

Division of Electric Energy Systems

Research areas

Our aim from the start was to provide theoretical solutions to build our energy system clean, stable, and economic. Our main research areas include:

Smartgrid

Smartgrid applies information and communications technology into existing grid in order to improve the reliability and economics of the production and consumption of electricity.

A new market structure and automated metering system are essential to implement Smartgrid in a real world. Also, various pricing programs and demand response need to be designed for fully achieving the potential benefits of Smartgrid.

Demand response

Demand Response can be implemented based on advanced metering systems (e.g. AMI). Under new market environments, end-used customers are offered choices to pay for their electricity usage.

For example, customers with real-time pricing program consume electricity based on the corresponding wholesale hourly market price. Thus, demand response (DR) is dynamic mechanisms to manage customer consumption of electricity in response to supply conditions.

Renewable energy

Renewable energy resources are widely integrated into electric power systems around the world. These resources are certain to have significant impacts on the system performance and efficiency and to necessitate advances in the planning and operation of the electric grid. The penetration of renewable resources to the electric grid produces technical challenges and provides opportunities to achieve higher level of reliability and efficiency.

Distributed generation and Microgrid

Distributed generation is active power sources placed near end-used customers to provide electricity with high quality, reliability and efficiency. irectly ts of Smartgridscs  power systemst Distributed generation encompasses various types of prime-movers into electricity, e.g. microturbines, fuel cells, small wind turbine or solar panels, etc.

Microgrid is small power systems comprised of microsources, aggregate loads and energy storage. In some senses, the concept of Microgrid is to utilize distributed generation in the distribution level that fully achieves its potential benefits while to reduce the negative impacts.

Division of Mechanical Engineering

Research areas

Our research relates to the use of analytical methods to solve engineering problems. In particular, numerical methods to facilitate design, and the associated issues of control are of interests. Experimental investigations are often a key feature of the research activities, and complement the theoretical analyses performed. The major research areas cover:

Nonlinear mechanical vibrations

Vibration phenomena can be modeled using linear vibration theory, however, the behavior of practical systems always associates with nonlinearity. Nonlinear system models can display behaviors that linear system cannot in the following points: (1) multiple steady state solutions; (2) jump phenomena; (3) response at frequencies other than forcing frequency, (4) internal resonance, and so on.

Vibro-impact dynamics

Vibro-impact dynamics get attention of dynamicists, physicists, and mathematicians nowadays; particularly, the focus is modeling, mapping and applications. The main techniques used in modeling of vibro-impact systems are phenomenological modeling, Hertzian models, and non-smooth coordinate transformations, etc. While discontinuity mapping techniques are common for grazing bifurcation which is one of the most critical situations impeded in vibro-impaction systems.

Computer-aided design

Computer-aided design (CAD) is a software program which uses computer systems to assist in the creation, modification, analysis, and/or optimization of a design. CAD also increases the conductivity of the designer; improves the quality of design and communications through documentations, and creates a database for manufacturing. CAD is applied in many fields: electronic design automation, mechanical design automation, etc.

 Computer-aided manufacturing

In some sense, computer-aided manufacturing (CAM) is a subsequent process of computer-aided engineering (CAE) after computer-aided design (CAD). CAM is the use of computer to control machine tools and related machinery in the manufacturing of workpieces. Its primary purpose is to create a faster production process and components and tooling with more precise dimensions and material consistency.

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