Chemical Engineering, IIT Bombay
Kannan M Moudgalya
Full Name: Kannan M Moudgalya
Room No: 311,
+91 (22) 2576 7213 (O)
+91 (22) 2576 8213 (R)
+91 (22) 2572 6895 (Fax)
Email Contact Form
Detailed Information / Research Group Web-Page
B.Tech in Chemical Engineering, IIT Madras, June 1980
Master of Electrical Engineering, Rice University, May 1985
Ph.D, Chemical Engineering, Rice University, May 1985
Best Poster Award for the paper ``An Integrated Simulation Environment'' by S. H. Rao, K. Moudgalya, K. V. Nori.
G. Sivakumar, International Conference on Advances in Chemical Engineering, 11-13 Dec. 1996, IIT Madras.
National Merit List, Government of India, May 1974.
Awards & Fellowships
Best Paper Presentation Award for "Control of a high index DAE system through a linear control law" by P. Vora,
K. Moudgalya and A. K. Pani, American Contro Conference, Anchorage, 8 May 2002.
Lovraj Kumar Industry-Academia Exchange Fellowship, April 1997
A complete list of publications is available in this link.
We are studying discontinuous dynamical systems that exhibit the property of sliding.? A large number of systems, including large industrial polymer reactors and modelled by differential algebraic equations (DAEs) have been shown to exhibit this behaviour. The concept of equivalent dynamics has been shown to speed up sliding DAE systems by 10,000 times.
We are looking at the control of chemical processes, especially reactors. We have effectively controlled reactors that exhibit nonlinearities and modelled by DAEs through simple controllers, such as, lead and PID.We have also successfully applied control techniques in network related applications.? We have shown that a combination of ARX modelling strategy and an adaptively detuned proportional controller chould help reduce the network traffic substantially without affecting the fidelity. We have also looked at control of systems, such as, aninverted pendulum through internet. Handling of performance deterioration through network delays is being studied.
We have worked on the topic of simulation methodologies and simulation environments through modern computing tools.? This approach hasbeen applied to simulation of neuro transmission in muscle cells.Automatic model derivation from first principles and data driven modelgeneration are some focus areas.
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