232 citations · 1.8k across the 63 of their papers we have counts for
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Concurrent learning-based online approximate feedback-Nash equilibrium solution of N-player nonzero-sum differential games
Rushikesh Kamalapurkar, Justin Klotz, Warren E. Dixon
This paper presents a concurrent learning-based actor-critic-identifier architecture to obtain an approximate feedback-Nash equilibrium solution to an infinite horizon N-player non…
Online Approximate Optimal Station Keeping of an Autonomous Underwater Vehicle
Patrick Walters, Warren E. Dixon
Online approximation of an optimal station keeping strategy for a fully actuated six degrees-of-freedom autonomous underwater vehicle is considered. The developed controller is an…
Online Approximate Optimal Path-Following for a Kinematic Unicycle
Patrick Walters, Rushikesh Kamalapurkar, Lindsey Andrews +1
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 usin…
Supporting Lemmas for RISE-based Control Methods
Rushikesh Kamalapurkar, Joel A. Rosenfeld, Justin Klotz +2
A class of continuous controllers termed Robust Integral of the Signum of the Error (RISE) have been published over the last decade as a means to yield asymptotic convergence of th…
Approximate optimal cooperative decentralized control for consensus in a topological network of agents with uncertain nonlinear dynamics
Rushikesh Kamalapurkar, Huyen Dinh, Patrick Walters +1
Efforts in this paper seek to combine graph theory with adaptive dynamic programming (ADP) as a reinforcement learning (RL) framework to determine forward-in-time, real-time, appro…
Concurrent learning-based approximate optimal regulation
Rushikesh Kamalapurkar, Patrick Walters, Warren Dixon
In deterministic systems, reinforcement learning-based online approximate optimal control methods typically require a restrictive persistence of excitation (PE) condition for conve…
Approximate Optimal Trajectory Tracking for Continuous Time Nonlinear Systems
Rushikesh Kamalapurkar, Huyen Dinh, Shubhendu Bhasin +1
Approximate dynamic programming has been investigated and used as a method to approximately solve optimal regulation problems. However, the extension of this technique to optimal t…