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DCL Seminar: Todd D. Murphey - Computational Control Engines for Robotic Systems

Event Type
Decision and Control Laboratory. Coordinated Science Laboratory
CSL Auditorium, Room B02
Feb 24, 2016   3:00 pm  
Todd D. Murphey, Ph.D.Northwestern University
Linda Meccoli
Originating Calendar
CSL Decision and Control Group

Decision and Control Lecture Series

Coordinated Science Laboratory


 “Computational Control Engines For Robotic Systems”


Todd D. Murphey, Ph.D.

Northwestern University

Wednesday, February 24, 2016

3:00 p.m. to 4:00 p.m.

CSL Auditorium (B02)



“Computational Control Engines For Robotic Systems” 


Robotic applications require real-time control for high-dimensional, nonlinear/nonsmooth systems operating in an uncertain environment, often with limited actuation, poor quality sensors, and low bandwidth. Computational simulation tools have evolved in the last two decades to efficiently meet robotics needs, whereas computational control and estimation tools largely have not.

This talk will focus on substantial progress towards bringing fully automated nonlinear control synthesis in software to robotics and other nonlinear applications. The first part of this talk will focus on the use of variational integrators in real-time, low-bandwidth systems. These integrators enable simulation and control synthesis for mechanical systems with closed kinematic chains, generally requiring special-purpose techniques for differential algebraic equations. The second part of the talk will focus on sequential action control (SAC), a control formulation with an analytic feedback solution for general affine nonlinear systems. Moreover, SAC provides continuous-time control that is globally well-posed, inherits stability properties from classical linear and model-predictive techniques, and admits both control saturation and unilateral state constraints. Successful SAC examples include many of the nonlinear benchmark systems used both in robotics and controls, including inversion of the cart-pendulum, the acrobot, the pendubot, and legged locomotion. SAC scales to systems with many degrees of freedom. Importantly, some of these examples can be executed on a mobile phone, indicating that real-time nonlinear control is feasible for many more systems than previously believed.

Lastly, SAC can be computationally automated, making a computational control engine for any nonlinear system plausible.



Dr. Todd D. Murphey is an Associate Professor of Mechanical Engineering at Northwestern University. He received his B.S. degree in mathematics from the University of Arizona and the Ph.D. degree in Control and Dynamical Systems from the California Institute of Technology. His laboratory is part of the Neuroscience and Robotics Laboratory, and his research interests include computational methods for mechanics and real-time optimal control, physical networks, and information theory in physical systems. Honors include the National Science Foundation CAREER award in 2006, membership in the 2014-2015 DARPA/IDA Defense Science Study Group, and Northwestern's Charles Deering McCormick Professorship of Teaching Excellence. He is a Senior Editor of the IEEE Transactions on Robotics.

link for robots only