Control and Estimation

Applications of control and estimation at LEES occur in a variety of contexts, but our research on these topics is primarily in connection with electrical machine systems, power electronics, and power systems. Much of this research involves recognizing and exploiting fundamental features of electromechanical or energy systems. Although results may be developed for particular machines or power converters or power system components and configurations, the underlying objective of the research is almost always to generalize: to develop results, approaches, and methodologies that are likely to be applicable over a broad range of systems. The particular systems that we study at LEES tend to suggest distinctive questions and to shape the answers in special ways, but these questions and answers are usually of broader applicability and interest to the control and estimation communities.

A few consistent themes run through the research in control and estimation at LEES. In the area of motor control, this research is distinguished by the way it couples issues of motor design to control tasks. Thus, whether considering control for high-efficiency energy conversion, for low acoustic noise, for precision motion control or torque actuation, we approach the problem in a way that integrates the machine design with the control. Such integration across traditional boundaries is typical for much of our work, and it provides both students and faculty with unique opportunities and perspectives.

Another important theme in work on machines is the use of actuators as sensors--or estimators--of their own "health" and environment. The results of the estimation are used for feedback control of the actuators (based on position, speed, and current observers), for adaptive control (based on load and parameter estimation), and for failure analysis of the actuator. More generally, this theme involves the use of model-based estimation, and we apply it in a broader range of contexts. Typical applications include transformer monitoring, nonintrusive monitoring of residential and industrial loads, voltage control and excitation control in power systems, and adaptive control of power converters.

Power electronic converters present special challenges in dynamic modeling and analysis for control and estimation. At the fastest time scale, control decisions are limited to picking the times at which particular switches are opened or closed. Typically, however, structured switching disciplines are imposed, and the control design is carried out at a higher level, selecting the various parameters of the switching discipline. Our research addresses the development of sampled-data models and averaged models at various time or frequency scales. These developments are essential for hierarchical modeling, analysis, and simulation of power converters. Our current research activity focuses on providing an analytical basis for understanding complex behavior in power converters operating with randomized modulation, or in chaotic regimes, or in situations that admit a large number of operating modes.

Electric power systems are prototypical large-scale and complex systems. Therefore, LEES research in this area directly confronts issues that are of increasing concern in many other domains as well. These issues include aggregation, localization, time scales, spatial scales, and coordination. Many traditional questions in control and estimation take on a new flavor in this setting. For instance, questions of on-line identification, model hierarchies and model validation, stability evaluation, and so on, have to be approached completely differently in view of the size and complexity of power systems. Research at LEES continues to make contributions in these directions.

Students who become involved in research in this area would naturally take courses in electromechanics (6.601), power electronics and nonlinear circuits (6.334, 6.335), and/or power systems (6.061, 6.686, 6.687), as well as courses in systems (6.011, 6.241), control (6.302, 6.233, 6.234, 2.152, 6.242, 6.243), and estimation (6.432, 6.433, 6.435). The subject 6.238 is specially designed to provide an entry to LEES research in control and estimation.

Current Projects:

None available

Back to Top

About LEES Faculty Staff Students Projects Program Areas