232 citations · 1.8k across the 63 of their papers we have counts for
13 papers · 1 filter
A Dynamic Mode Decomposition Approach to Parameter Identification
Moad Abudia, Opeyemi Owolabi, Joel A. Rosenfeld +1
This paper develops a data-driven algorithm for simultaneous system and parameter identification in control-affine nonlinear systems. Parameter identification is achieved by traini…
Adaptive Control with Sparse Identification of Nonlinear Dynamics
Trivikram Satharasi, Tochukwu E. Ogri, Muzaffar Qureshi +2
This paper develops a sparsity-promoting integral concurrent learning (SP-ICL) adaptation law for a linearly parametrized uncertain nonlinear control-affine systems. The unknown pa…
Safe Adaptive Feedback Control via Barrier States
Trivikram Satharasi, Tochukwu E. Ogri, Muzaffar Qureshi +2
This paper presents a safe feedback control framework for nonlinear control-affine systems with parametric uncertainty by leveraging adaptive dynamic programming (ADP) with barrier…
Switched Optimal Control with Dwell Time Constraints
Masoud S. Sakha, Rushikesh Kamalapurkar
This paper presents an embedding-based approach for solving switched optimal control problems (SOCPs) with dwell time constraints. At first, an embedded optimal control problem (EO…
Dynamic Mode Decomposition of Control-Affine Nonlinear Systems using Discrete Control Liouville Operators
Zachary Morrison, Moad Abudia, Joel Rosenfeld +1
Representation of nonlinear dynamical systems as infinite-dimensional linear operators over Hilbert spaces enables analysis of nonlinear systems via pseudo-spectral operator analys…
An occupation kernel approach to optimal control
Rushikesh Kamalapurkar, Joel A. Rosenfeld
In this effort, a novel operator theoretic framework is developed for data-driven solution of optimal control problems. The developed methods focus on the use of trajectories (i.e.…
Control Occupation Kernel Regression for Nonlinear Control-Affine Systems
Moad Abudia, Tejasvi Channagiri, Joel A. Rosenfeld +1
This manuscript presents an algorithm for obtaining an approximation of a nonlinear high order control affine dynamical system. Controlled trajectories of the system are leveraged…
Motion Tomography via Occupation Kernels
Benjamin P. Russo, Rushikesh Kamalapurkar, Dongsik Chang +1
The goal of motion tomography is to recover a description of a vector flow field using information on the trajectory of a sensing unit. In this paper, we develop a predictor correc…
Theoretical Foundations for the Dynamic Mode Decomposition of High Order Dynamical Systems
Joel A. Rosenfeld, Benjamin P. Russo, Rushikesh Kamalapurkar
Conventionally, data driven identification and control problems for higher order dynamical systems are solved by augmenting the system state by the derivatives of the output to for…
Dynamic Mode Decomposition with Control Liouville Operators
Joel A. Rosenfeld, Rushikesh Kamalapurkar
This paper builds the theoretical foundations for dynamic mode decomposition (DMD) of control-affine dynamical systems by leveraging the theory of vector-valued reproducing kernel…
The Occupation Kernel Method for Nonlinear System Identification
Joel A. Rosenfeld, Benjamin Russo, Rushikesh Kamalapurkar +1
This manuscript presents a novel approach to nonlinear system identification leveraging densely defined Liouville operators and a new "kernel" function that represents an integrati…
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…
A Corollary for Nonsmooth Systems
N. Fischer, R. Kamalapurkar, W. E. Dixon
In this note, two generalized corollaries to the LaSalle-Yoshizawa Theorem are presented for nonautonomous systems described by nonlinear differential equations with discontinuous…