5 citations · 5 across the 5 of their papers we have counts for
5 papers
Discrete-Time High Order Tuner With A Time-Varying Learning Rate
Yingnan Cui, Anuradha M. Annaswamy
We propose a new discrete-time online parameter estimation algorithm that combines two different aspects, one that adds momentum, and another that includes a time-varying learning…
Accelerated Performance and Accelerated Learning with Discrete-Time High-Order Tuners
Yingnan Cui, Anuradha M. Annaswamy
We consider two high-order tuners that have been shown to have accelerated performance, one based on Polyak's heavy ball method and another based on Nesterov's acceleration method.…
Online Algorithms and Policies Using Adaptive and Machine Learning Approaches
Anuradha M. Annaswamy, Anubhav Guha, Yingnan Cui +3
This paper considers the problem of real-time control and learning in dynamic systems subjected to parametric uncertainties. We propose a combination of a Reinforcement Learning (R…
A High-order Tuner for Accelerated Learning and Control
Spencer McDonald, Yingnan Cui, Joseph E. Gaudio +1
Gradient-descent based iterative algorithms pervade a variety of problems in estimation, prediction, learning, control, and optimization. Recently iterative algorithms based on hig…
New Algorithms for Discrete-Time Parameter Estimation
Yingnan Cui, Joseph E. Gaudio, Anuradha M. Annaswamy
We propose two algorithms for discrete-time parameter estimation, one for time-varying parameters under persistent excitation (PE) condition, another for constant parameters under…