11 citations · 21 across the 17 of their papers we have counts for
10 papers · 1 filter
Structured Koopman Lifted Finite Memory Identification via Truncated Grunwald Letnikov Kernels
Navid Mojahed, Mahdis Rabbani, Shima Nazari
Nonlinear hereditary systems combine nonlinear state dependence with memory. Koopman lifting provides linear predictors for nonlinear dynamics, but standard formulations are Markov…
Fleet Size and Mix Capacitated Vehicle Routing Problem with Time Windows for Mobile Fast Chargers
Farhang Motallebi Araghi, Armin Abdolmohammadi, Navid Mojahed +1
The electrification of off-road heavy equipment presents operational challenges for agencies serving remote sites with limited fixed charging infrastructure. Existing mobile fast c…
Predictive Compensation in Finite-Horizon LQ Games under Gauss-Markov Deviations
Navid Mojahed, Mahdis Rabbani, Shima Nazari
This paper develops a predictive compensation framework for finite-horizon, discrete-time linear quadratic dynamic games subject to Gauss-Markov execution deviations from feedback…
Optimal Path Planning for Wheel Loader Automation Enabled by Efficient Soil-Tool Interaction Modeling
Armin Abdolmohammadi, Navid Mojahed, Bahram Ravani +1
Earthmoving operations with wheel loaders require substantial power and incur high operational costs. This work presents an efficient automation framework based on the Fundamental…
Deep Bilinear Koopman Model for Real-Time Vehicle Control in Frenet Frame
Mohammad Abtahi, Farhang Motallebi Araghi, Navid Mojahed +1
Accurate modeling and control of autonomous vehicles remain a fundamental challenge due to the nonlinear and coupled nature of vehicle dynamics. While Koopman operator theory offer…
Data-Efficient Excavation Force Estimation for Wheel Loaders
Armin Abdolmohammadi, Navid Mojahed, Shima Nazari +1
Accurate prediction of excavation forces is critical for enabling autonomous operation and optimizing control strategies in earthmoving machinery. Conventional approaches often dep…
Inverted Gaussian Process Optimization for Probabilistic Koopman Operator Discovery
Abhigyan Majumdar, Navid Mojahed, Shima Nazari
Koopman Operator Theory has opened the doors to data-driven learning of globally linear representations of complex nonlinear systems. However, current methodologies for Koopman Ope…
Multi-Step Deep Koopman Network (MDK-Net) for Vehicle Control in Frenet Frame
Mohammad Abtahi, Mahdis Rabbani, Armin Abdolmohammadi +1
The highly nonlinear dynamics of vehicles present a major challenge for the practical implementation of optimal and Model Predictive Control (MPC) approaches in path planning and f…
Powertrain Hybridization for Autonomous Vehicles
Shima Nazari, Norma Gowans, Mohammad Abtahi
The powertrains of today's hybrid electric vehicles (HEVs) are developed for human drivers and, therefore, may not be the optimum choice for future Autonomous vehicles (AVs), given…
Safe Adaptive Cruise Control with Road Grade Preview and V2V Communication
Roya Firoozi, Shima Nazari, Jacopo Guanetti +2
We present the design of a safe Adaptive Cruise Control (ACC) which uses road grade and lead vehicle motion preview. The ACC controller is designed by using a Model Predictive Cont…