Faculty DirectoryTodd Murphey
Charles Deering McCormick Professor in Teaching Excellence
Associate Professor of Mechanical Engineering
Contact2145 Sheridan Road
Evanston, IL 60208-3109
Email Todd Murphey
Ph.D. Control and Dynamical Systems, California Institute of Technology, Pasadena, CA
B.S. Mathematics (summa cum laude), University of Arizona, Tucson, AZ
Professor Murphey's research focuses on computational methods in dynamics and control. The group focuses on computational models of embedded control, biomechanical simulation, dynamic exploration, and hybrid control. Much of the work uses structured integration (numerical techniques specifically suited to mechanical systems) to ensure stability and robustness of the numerical technique. Example projects include simulation and control synthesis for a biomechanical model of the human hand, real-time control of robotic systems using structured integration, stabilization of large-scale power network models using a single bit of control authority, mechanical simulation of rat whiskers, numerical modeling of contact in locomotion, and dynamic search for underwater vehicles using electrosense for localization and mapping. His group's work on robotic marionettes has been featured at the Museum of Science and Industry, Chicago.
- National Science Foundation CAREER award (2006)
- Defense Science Study Group 2014-2015
Significant Professional Service
- Associate Editor for IEEE Transactions on Automation Science and Engineering
- Editor for IEEE Transactions on Robotics
A. Ansari and T. D. Murphey, “Sequential Action Control: Closed-form optimal control for nonlinear and hybrid systems,” IEEE Transactions on Robotics, vol. 32, no. 5, pp. 1196–1214, 2016.
A. Mavrommati, J. Schultz, and T. D. Murphey, “Real-time mode scheduling using single-integration hybrid optimization for linear time-varying systems,” IEEE Transactions on Automation Science and Engineering, vol. 13, no. 3, pp. 1385–1398, 2016.
E. Tzorakoleftherakis, T. D. Murphey, and R. A. Scheidt, “Augmenting sensorimotor control using goal-aware vibrotactile stimulation during reaching and manipulation behaviors,” Experimental Brain Research, vol. 234, no. 8, pp. 2403–2414, 2016.
A. Ansari and T. D. Murphey, “Minimum sensitivity control for planning with parametric and hybrid uncertainty,” International Journal of Robotics Research, vol. 35, no. 7, pp. 823–839, 2016.
E. Tzorakoleftherakis, A. Ansari, A. Wilson, J. Schultz, and T. D. Murphey, “Model-based reactive control for hybrid and high-dimensional robotic systems,” IEEE Robotics and Automation Letters, vol. 1, no. 1, pp. 431–438, 2016.
T. Caldwell and T. D. Murphey, “Sufficient descent and backtracking for optimal mode scheduling,” Nonlinear Analysis: Hybrid Systems, vol. 21, pp. 59–83, 2016.
L. Miller, Y. Silverman, M. A. MacIver, and T. Murphey, “Ergodic exploration of distributed information,” IEEE Transactions on Robotics, vol. 32, no. 1, pp. 36–52, 2016.
D. Pekarek and T. D. Murphey, “Discrete Lagrangian mechanics for nonsmooth nonseparable systems,” International Journal for Numerical Methods in Engineering, vol. 105, pp. 440–463, 2016.
In the Classroom
Professor Murphey developed the Coursera Massive Open Online Course (MOOC) "Everything Is the Same: Modeling Engineered Systems" and had over 18,000 students enroll in Autumn, 2013. The course was based on one of the core undergraduate classes in systems analysis (EA3), a class he has innovated through development of classroom experiments. Moreover, he has developed the ME 314 Machine Dynamics course, focusing on the application of variational analysis to simulation and design of mechanisms. He has additionally developed ME 454, an introduction to numerical methods in optimal control. In all these courses, Professor Murphey focuses on project-based learning.