Next Article in Journal
Extenics Coordinated Torque Distribution Control for Distributed Drive Electric Vehicles Considering Stability and Energy Efficiency
Previous Article in Journal
A Hybrid Piezoelectric and Photovoltaic Energy Harvester for Power Line Monitoring
Previous Article in Special Issue
Safe Reinforcement Learning for Competitive Autonomous Racing: Integrated State–Action Mapping and Exploration Guidance Framework
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Actuators
Volume 15
Issue 1
10.3390/act15010002
actuators-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Bridging Regimes: A State-Dependent Blending Methodology for Parsimonious and Robust Heavy Vehicle Dynamics Modeling

by
Ozgur Unsal
1,* and
Hakan Yavuz
2
1
TEMSA, 01110 Adana, Türkiye
2
Cukurova University, Engineering Faculty, Mechanical Engineering Department, 01330 Adana, Türkiye
*
Author to whom correspondence should be addressed.
Actuators 2026, 15(1), 2; https://doi.org/10.3390/act15010002
Submission received: 17 November 2025 / Revised: 8 December 2025 / Accepted: 17 December 2025 / Published: 19 December 2025
(This article belongs to the Special Issue Data-Driven Control for Vehicle Dynamics)
Review Reports Versions Notes

Abstract

Data-driven gray-box models for vehicle control often fail to generalize across distinct physical regimes. This study tackles the critical, yet often-overlooked, challenge of robustly blending model parameters between these regimes. The vehicle’s “expert poles” are defined using physically distinct maneuvers (steady state vs. transient). A three-way benchmark is used to prove that the blending method is more critical than the concept itself. Three architectures are compared: (1) a baseline single-parameter “Static Model”, (2) a common literature “Heuristic Model” that blends using lateral acceleration (<!-- MathType@Translator@5@5@MathML2 (no namespace).tdl@MathML 2.0 (no namespace)@ -->

Share and Cite

MDPI and ACS Style

Unsal, O.; Yavuz, H. Bridging Regimes: A State-Dependent Blending Methodology for Parsimonious and Robust Heavy Vehicle Dynamics Modeling. Actuators 2026, 15, 2. https://doi.org/10.3390/act15010002

AMA Style

Unsal O, Yavuz H. Bridging Regimes: A State-Dependent Blending Methodology for Parsimonious and Robust Heavy Vehicle Dynamics Modeling. Actuators. 2026; 15(1):2. https://doi.org/10.3390/act15010002

Chicago/Turabian Style

Unsal, Ozgur, and Hakan Yavuz. 2026. "Bridging Regimes: A State-Dependent Blending Methodology for Parsimonious and Robust Heavy Vehicle Dynamics Modeling" Actuators 15, no. 1: 2. https://doi.org/10.3390/act15010002

APA Style

Unsal, O., & Yavuz, H. (2026). Bridging Regimes: A State-Dependent Blending Methodology for Parsimonious and Robust Heavy Vehicle Dynamics Modeling. Actuators, 15(1), 2. https://doi.org/10.3390/act15010002

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop