activity
20152023
most citedIntegrating Physics-Based Modeling with Machine Learning for Lithium-Ion Batteries

188 citations · 489 across the 18 of their papers we have counts for

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Showing 2022Show all

6 papers · 1 filter

eess.SY2022★ 1 cited

BattX: An Equivalent Circuit Model for Lithium-Ion Batteries Over Broad Current Ranges

Nikhil Biju, Huazhen Fang

Advanced battery management is to lithium-ion battery systems as the brain is to the human body. Its performance rests on the use of battery models that are both fast and accurate.…

cs.RO2022

Model Predictive Control of Nonlinear Latent Force Models: A Scenario-Based Approach

Thomas Woodruff, Iman Askari, Guanghui Wang +1

Control of nonlinear uncertain systems is a common challenge in the robotics field. Nonlinear latent force models, which incorporate latent uncertainty characterized as Gaussian pr…

eess.SY2022

High-Order Leader-Follower Tracking Control under Limited Information Availability

Chuan Yan, Tao Yang, Huazhen Fang

Limited information availability represents a fundamental challenge for control of multi-agent systems, since an agent often lacks sensing capabilities to measure certain states of…

cs.RO2022

Sampling-Based Nonlinear MPC of Neural Network Dynamics with Application to Autonomous Vehicle Motion Planning

Iman Askari, Babak Badnava, Thomas Woodruff +2

Control of machine learning models has emerged as an important paradigm for a broad range of robotics applications. In this paper, we present a sampling-based nonlinear model predi…

eess.SY2022★ 16 cited

Nonlinear Model Predictive Control Based on Constraint-Aware Particle Filtering/Smoothing

Iman Askari, Shen Zeng, Huazhen Fang

Nonlinear model predictive control (NMPC) has gained widespread use in many applications. Its formulation traditionally involves repetitively solving a nonlinear constrained optimi…

eess.SY2022★ 12 cited

Implicit Particle Filtering via a Bank of Nonlinear Kalman Filters

Iman Askari, Mulugeta A. Haile, Xuemin Tu +1

The implicit particle filter seeks to mitigate particle degeneracy by identifying particles in the target distribution's high-probability regions. This study is motivated by the ne…