232 citations · 1.5k across the 29 of their papers we have counts for
5 papers · 1 filter
Concurrent learning for parameter estimation using dynamic state-derivative estimators
Rushikesh Kamalapurkar, Ben Reish, Girish Chowdhary +1
A concurrent learning (CL)-based parameter estimator is developed to identify the unknown parameters in a linearly parameterized uncertain control-affine nonlinear system. Unlike s…
Model-based reinforcement learning for infinite-horizon approximate optimal tracking
Rushikesh Kamalapurkar, Lindsey Andrews, Patrick Walters +1
This paper provides an approximate online adaptive solution to the infinite-horizon optimal tracking problem for control-affine continuous-time nonlinear systems with unknown drift…
State Following (StaF) Kernel Functions for Function Approximation
Joel A. Rosenfeld, Rushikesh Kamalapurkar, Warren E. Dixon
A function approximation method is developed that aims to approximate a function in a small neighborhood of a state that travels within a compact set. The development is based on t…
Efficient model-based reinforcement learning for approximate online optimal
Rushikesh Kamalapurkar, Joel A. Rosenfeld, Warren E. Dixon
In this paper the infinite horizon optimal regulation problem is solved online for a deterministic control-affine nonlinear dynamical system using the state following (StaF) kernel…
Time-Varying Input and State Delay Compensation for Uncertain Nonlinear Systems
Rushikesh Kamalapurkar, Nicholas Fischer, Serhat Obuz +1
A robust controller is developed for uncertain, second-order nonlinear systems subject to simultaneous unknown, time-varying state delays and known, time-varying input delays in ad…