9.110[J] Nonlinear Control
Introduction to nonlinear control and estimation in physical and biological systems. Nonlinear stability theory, Lyapunov analysis, Barbalat's lemma. Feedback linearization, differential flatness, internal dynamics. Sliding surfaces. Adaptive nonlinear control and estimation. Multiresolution bases, nonlinear system identification. Contraction analysis, differential stability theory. Nonlinear observers. Asynchronous distributed computation and learning. Concurrent synchronization, polyrhythms. Monotone nonlinear systems. Emphasizws application to physical systems (robots, aircraft, spacecraft, underwater vehicles, reaction-diffusion processes, machine vision, oscillators, internet), machine learning, computational neuroscience, and systems biology. Includes term projects.
9.110[J] will not be offered this semester. It will be instructed by J.-J. E. Slotine.
This class counts for a total of 12 credits. This is a graduate-level class.
In the Spring 2016 Subject Evaluations, 9.110[J] was rated 6.2 out of 7.0. You can find more information on MIT OpenCourseWare at the Neurology, Neuropsychology, and Neurobiology of Aging site or on the 9.110[J] Stellar site.
© Copyright 2015 Yasyf Mohamedali