Lindsey Andrews

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This brief paper provides an approximate online adaptive solution to the infinite-horizon optimal tracking problem for control-affine continuous-time nonlinear systems with unknown drift dynamics. To relax the persistence of excitation condition, model-based reinforcement learning is implemented using a concurrent-learning-based system identifier to(More)
Online approximation of an infinite horizon optimal path-following strategy for a unicycle-type mobile robot is considered. An approximate solution to the optimal control problem is obtained by using an adaptive dynamic programming technique that uses adaptive update laws to estimate the unknown value function. The developed controller overcomes challenges(More)
Introduction On 26 April 2013, the Wall Street Journal published an essay by neurocriminologist Adrian Raine promoting his newest book, The Anatomy of Violence: The Biological Roots of Crime. On the newspaper’s website, an image of a black-andwhite brain scan overlaid with handcuffs headed the essay. Clicking ‘play’ turned the image into a video fi lled(More)
Online approximation of an infinite horizon optimal path-following strategy for a kinematic unicycle is considered. The solution to the optimal control problem is approximated using an approximate dynamic programming technique that uses concurrent-learning-based adaptive update laws to estimate the unknown value function. The developed controller overcomes(More)
Robustness to parametric uncertainty is fundamental to successful control system design and as such it has been at the core of many design methods developed over the decades. Despite its prominence, most of the work on robust control design has focused on linear models and uncertainties that are non-probabilistic in nature. Recently, researchers have(More)
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