[HTML][HTML] Analysis and design of model predictive control frameworks for dynamic operation—An overview
This article provides an overview of model predictive control (MPC) frameworks for dynamic
operation of nonlinear constrained systems. Dynamic operation is often an integral part of …
operation of nonlinear constrained systems. Dynamic operation is often an integral part of …
Active Exploration in Iterative Gaussian Process Regression for Uncertainty Modeling in Autonomous Racing
Autonomous racing creates challenging control problems, but model predictive control
(MPC) has made promising steps toward solving both the minimum lap-time problem and …
(MPC) has made promising steps toward solving both the minimum lap-time problem and …
[HTML][HTML] Optimized Longitudinal and Lateral Control Strategy of Intelligent Vehicles Based on Adaptive Sliding Mode Control
Y Wang, Z Wang, D Shi, F Chu, J Guo… - World Electric Vehicle …, 2024 - mdpi.com
To improve the tracking accuracy and robustness of the path-tracking control model for
intelligent vehicles under longitudinal and lateral coupling constraints, this paper utilizes the …
intelligent vehicles under longitudinal and lateral coupling constraints, this paper utilizes the …
Model predictive control for tracking using artificial references: Fundamentals, recent results and practical implementation
This paper provides a comprehensive tutorial on a family of Model Predictive Control (MPC)
formulations, known as MPC for tracking, which are characterized by including an artificial …
formulations, known as MPC for tracking, which are characterized by including an artificial …
Optimization-Based System Identification and Moving Horizon Estimation Using Low-Cost Sensors for a Miniature Car-Like Robot
S Bodmer, L Vogel, S Muntwiler, A Hansson… - arXiv preprint arXiv …, 2024 - arxiv.org
This paper presents an open-source miniature car-like robot with low-cost sensing and a
pipeline for optimization-based system identification, state estimation, and control. The …
pipeline for optimization-based system identification, state estimation, and control. The …