Tamas Hegedus

About Tamas Hegedus

Tamas Hegedus, With an exceptional h-index of 7 and a recent h-index of 7 (since 2020), a distinguished researcher at Budapesti Muszaki és Gazdaságtudományi Egyetem, specializes in the field of Automotive Systems Engineering.

His recent articles reflect a diverse array of research interests and contributions to the field:

Implementation and design of ultra-local model-based control strategy for autonomous vehicles

Cooperation Strategy for Optimal Motion of Aerial and Ground Vehicles

An Observer Design Method Using Ultra-Local Model for Autonomous Vehicles

Lateral Control for Automated Vehicles Based on Model Predictive Control and Error-Based Ultra-Local Model

Combined LPV and ultra-local model-based control design approach for autonomous vehicles

Robust control design using ultra-local model-based approach for vehicle-oriented control problems

Combined observer design for road vehicles using LPV-based and learning-based methods

Design of Model Free Control with tuning method on ultra-local model for lateral vehicle control purposes

Tamas Hegedus Information

University

Position

___

Citations(all)

136

Citations(since 2020)

136

Cited By

26

hIndex(all)

7

hIndex(since 2020)

7

i10Index(all)

4

i10Index(since 2020)

4

Email

University Profile Page

Google Scholar

Tamas Hegedus Skills & Research Interests

Automotive Systems Engineering

Top articles of Tamas Hegedus

Implementation and design of ultra-local model-based control strategy for autonomous vehicles

Vehicle System Dynamics

2023/8/1

Cooperation Strategy for Optimal Motion of Aerial and Ground Vehicles

2023/6/26

An Observer Design Method Using Ultra-Local Model for Autonomous Vehicles

2023

Lateral Control for Automated Vehicles Based on Model Predictive Control and Error-Based Ultra-Local Model

2023

Combined LPV and ultra-local model-based control design approach for autonomous vehicles

2022/12/6

Robust control design using ultra-local model-based approach for vehicle-oriented control problems

2022/7/12

Combined observer design for road vehicles using LPV-based and learning-based methods

2022/6/28

Design of Model Free Control with tuning method on ultra-local model for lateral vehicle control purposes

2022/6/8

Decision and control methods for overtaking strategies of autonomous vehicles

2022

LPV control design based on ultra-local model for trajectory tracking problem

IFAC-PapersOnLine

2022/1/1

Coordinated control design for steering and torque-vectoring in Model-Free Control structure

IFAC-PapersOnLine

2022/1/1

Control Design Framework for Automated Vehicles Using an Advanced Feedback Linearization

2021/8/17

Observer design with performance guarantees for vehicle control purposes via the integration of learning-based and LPV approaches

2021/7/11

Design framework for achieving guarantees with learning-based observers

Energies

2021/4/7

Robust control design for autonomous vehicles using neural network-based model-matching approach

Energies

2021/11/8

Improving sustainable safe transport via automated vehicle control with closed-loop matching

Sustainability

2021/10/13

Mpc based semi-active suspension control for overtaking maneuvers

Periodica Polytechnica Transportation Engineering

2021/9/1

Design of a low-complexity graph-based motion-planning algorithm for autonomous vehicles

Applied Sciences

2020/10/31

LPV control for autonomous vehicles using a machine learning-based tire pressure estimation

2020/9/15

Challenges and possibilities of overtaking strategies for autonomous vehicles

Periodica Polytechnica Transportation Engineering

2020/8/7

See List of Professors in Tamas Hegedus University(Budapesti Muszaki és Gazdaságtudományi Egyetem)