5 papers
Lyapunov-based Adaptive Transformer (LyAT) for Control of Stochastic Nonlinear Systems
Saiedeh Akbari, Xuehui Shen, Wenqian Xue +2
This paper presents a novel Lyapunov-based Adaptive Transformer (LyAT) controller for stochastic nonlinear systems. While transformers have shown promise in various control applica…
Effective Model Pruning: Measure The Redundancy of Model Components
Yixuan Wang, Dan P. Guralnik, Saiedeh Akbari +1
This article initiates the study of a basic question about model pruning. Given a vector of importance scores assigned to model components, how many of the scored components co…
LyLA-Therm: Lyapunov-based Langevin Adaptive Thermodynamic Neural Network Controller
Saiedeh Akbari, Omkar Sudhir Patil, Warren E. Dixon
Thermodynamic principles can be employed to design parameter update laws that address challenges such as the exploration vs. exploitation dilemma. In this paper, inspired by the La…
Lyapunov-Based Deep Neural Networks for Adaptive Control of Stochastic Nonlinear Systems
Saiedeh Akbari, Cristian F. Nino, Omkar Sudhir Patil +1
Controlling nonlinear stochastic dynamical systems involves substantial challenges when the dynamics contain unknown and unstructured nonlinear state-dependent terms. For such comp…
Lyapunov-Based Dropout Deep Neural Network (Lb-DDNN) Controller
Saiedeh Akbari, Emily J. Griffis, Omkar Sudhir Patil +1
Deep neural network (DNN)-based adaptive controllers can be used to compensate for unstructured uncertainties in nonlinear dynamic systems. However, DNNs are also very susceptible…