• Research Interests
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  • Software: DECK
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    Research Interests

    My research group's activities lie in the area of Systems and Control. We study:

  • Supervisory control
  • Fault diagnosis
  • Modeling and analysis of biological systems.

    The main tools of our analysis (and the link among the above three topics) are Discrete-Event models. Examples of Discrete-Event Systems (DES) are finite-state automata and Petri nets. DES models are used in the study of a wide range of problems in aerospace, process control, software engineering, automated manufacturing and biological systems. Compared with continuous-variable models (such as differential equations), DES models are coarser and provide less detail. Therefore, they are typically used where studying systems at higher levels of abstraction is desired. The use of finite-state machines in the design of logic circuits is one example. Another example can be found in Control Hierarchies.

    Control systems usually have a hierarchical organization. A typical control hierarchy has three levels. The lowest level involves continuous-variable feedback loops (e.g, PID control loops). The next level up deals with sequencing and supervisory control (e.g., plant start-up and shutdown sequences, enablement/disablement of control loops). DES models are suitable tools for the analysis and design of these command sequences. At the highest level of the hierarchy, controllers are concerned with longer-term planning and production scheduling tasks.

    Our research primarily focuses on the following topics.

  • Supervisory control: We develop methods for designing supervisory control systems that are robust with respect to plant model uncertainties or changes. Plant model changes can be, for instance, the result of a component failure. In such cases, the controller is expected to be able to meet the design specifications of both normal and faulty modes of operation of the plant. Therefore robustness plays an important role in developing fault recovery procedures.
  • Fault diagnosis:A significant portion of "control" code in real-world systems (up to 80% in some cases) is dedicated to test and diagnosis. DES models are suitable for designing monitoring systems that diagnose drastic failures such as "valve stuck-closed" or "sensor short-circuited". The resulting diagnosis systems, in combination with fault recovery procedures, could serve: (1) to enhance the level of autonomy of unmanned systems, and (2) to assist human operators (in manned systems) with handling failures.
  • Modeling biological systems: Over the past decade or so, obtaining experimental data for biological systems has become to some extent easier and less expensive. Many methods of analysis in engineeering and computer science are applied (or adapted for application) to these data to better understand the underlying biological phenomena. Biological systems, similar to many control systems, have a hierarchical organization. Various types of models, such as differential equations and DES models, are used to study these hierarchies. We develop algorithms for analysis, assessment and comparison of various models of the protein interactions and methobolic pathways in cells.
  • Software tools: We have developed Discrete Event Control Kit (DECK), a toolbox (set of M-file functions) written in the programming language of MATLAB for the analysis and design of supervisory control systems based on discrete-event models. DECK has been developed in the familiar environment of MATLAB as an educational tool, and provides a convenient setup for implementing new algorithms to assist in research.

    Last updated April 8, 2014.