The Nonlinear Systems Laboratory studies general mathematical principles of nonlinear system stability, adaptation, and learning, and how they apply to robots and to models of biological control. We are particularly interested in how stability and performance constraints shape system architecture, representation, and algorithms in robots, and in whether similar constraints may in some cases lead to similar mechanisms in biological systems. Tools from nonlinear control, such as sliding variables, wave variables, and contraction theory also suggest a number of simple models of physiological motor control, which may help understand the specific roles of hierarchies, motor primitives, and nerve transmission delays. See our web site at for further information.

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