Truong X. Nghiem

Research Interests

Currently I am interested in two main areas of research.

Control and scheduling of dynamical systems for peak demand management

Many practical engineering systems consist of a demand side and a supply side. Well-known examples can be found in energy systems, for instance: electric grids, HVAC (Heating, Cooling and Air Conditioning) systems, and electric vehicles. However this characteristic is also present in non-energy-related systems such as traffic systems. In these systems, peaks in the demand are usually bad because they can cause undesirable effects on the supply, either technically or economically. For example, peaks in the electricity demand result in oversized power plants as well as the construction of back-up plants; otherwise they can cause grid instability and power outages. Because of this reason, large electricity customers are often charged at very high rates for their peak demand to discourage them from using electricity during critical time. In battery-powered electric vehicles, peaks in the power drawn from the battery cause the battery to heat up quickly, eventually decrease its lifetime. Peaks in traffic demand often cause traffic jams.

Many approaches, in various applications, have been proposed to reduce peak demand (known as peak demand management). A popular technical approach to tackle this problem is to utilize optimization (dynamic programming, model predictive control) to calculate optimal schedules for the operation of the systems. However, this approach usually requires an accurate model of the system (which might be very difficult to obtain), accurate forecasts of the demand and disturbances (again, might be very difficult to obtain), and high computational capability (to solve large and complex optimization programs). Another approach to the peak demand reduction problem is to introduce some flexibility into the systems, typically via some direct or indirect form of storage, and exploit this flexibility to reduce and smooth out the demand. For example, thermal energy storage can be added to HVAC systems, or the room temperature can be fluctuated within a comfort range, or super-capacitors are used with batteries. In this line of research, I study the control and scheduling of these dynamical systems for peak demand reduction via direct/indirect storage. The goals are to develop control and scheduling architectures and algorithms that

  1. effectively reduce the peak demand for the supply side, while maintaining certain operational or safety constraints of the system; and

  2. does not require highly accurate system model and forecasts; and

  3. does not require high computational capability (particularly for systems with fast dynamics).

For my publications related to this research area, please visit this page.

Cyber-Physical Systems (CPS)

Cyber-Physical Systems (CPS) integrate physical processes with computation and networks. They can be found in almost every complex system in practice, from as small as biological systems and embedded medical devices, to as large as airplanes, space shuttles, and the electric grid. I have started pursuing a research interest in CPS, particularly real-time and embedded control systems and hybrid systems. With the proliferation of embedded computing components and software components in modern control systems, there have been new challenges such as automatic synthesis and verification of control software, and secure and high-confidence control systems. These directions are also within my research focus.

For my publications related to this research area, please visit this page.