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. Emphasizes 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.
Doctor of Philosophy (PhD) in Mechanical Engineering
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| content serial | Description |
|---|
| 1 | Introduction to nonlinear control and estimation in physical and biological systems. |
| 2 | Nonlinear stability theory |
| 3 | Nonlinear stability theory |
| 4 | Feedback linearization, differential flatness, internal dynamics |
| 5 | Feedback linearization, differential flatness, internal dynamics |
| 6 | Sliding surfaces |
| 7 | Adaptive nonlinear control |
| 8 | Adaptive nonlinear control |
| 9 | Nonlinear system identification. |
| 10 | Nonlinear observers |
| 11 | Asynchronous distributed computation and learning |
| 12 | Asynchronous distributed computation and learning |
| 13 | Application to physical systems |
| 14 | Application to physical systems |
| 15 | Application to physical systems |
| 16 | Final Examination |
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