@article{MTMT:34735212,
	title = {Internal Model-Based Robust Path-Following Control for Autonomous Vehicles},
	url = {https://m2.mtmt.hu/api/publication/34735212},
	author = {Kovács, Adorján and Vajk, István},
	doi = {10.1007/s12239-024-00003-z},
	journal-iso = {INT J AUTOMOT TECHN},
	journal = {INTERNATIONAL JOURNAL OF AUTOMOTIVE TECHNOLOGY},
	volume = {25},
	unique-id = {34735212},
	issn = {1229-9138},
	abstract = {The paper presents a new internal model control (IMC) based control technique for lateral trajectory tracking of autonomous vehicles. The controller’s proposed structure employs a robust, fault-tolerant nonlinear internal servo control with optimal reference generation concerning vehicle yaw stability and physical limitations. The presented inscription of the reference generation creates a convex optimization task that can be used in real-time applications. Improvements in yaw-rate stability of vehicle motion control are first shown through simulation results performed in a Simulink environment. The controller structure was also implemented in a real-time model and was examined in a Mercedes C-Class vehicle. In this article, the simulation results and the real-time measurements are presented. The results show that the proposed controller has high efficiency in disturbance rejection and lower sensitivity towards parameter changes compared to a model predictive control (MPC) structure.},
	keywords = {CONTROLLERS; Nonlinear control; Robust control; Control techniques; Model predictive control; Predictive control systems; Convex optimization; Model-based OPC; Internal model control; C (programming language); Non linear control; Internal models; Autonomous Vehicles; disturbance rejection; Path tracking control; Convex optimisation; path following control; Path-tracking control; Reference Generation},
	year = {2024},
	eissn = {1976-3832},
	pages = {249-260},
	orcid-numbers = {Vajk, István/0000-0002-2818-9162}
}

@book{MTMT:34051102,
	title = {Proceedings of the Automation and Applied Computer Science Workshop 2023 (AACS'23)},
	url = {https://m2.mtmt.hu/api/publication/34051102},
	isbn = {9789634219262},
	editor = {Vajk, István and Dunaev, Dmitriy},
	publisher = {BME Department of Automation and Applied Informatics},
	unique-id = {34051102},
	year = {2023},
	orcid-numbers = {Vajk, István/0000-0002-2818-9162}
}

@{MTMT:34048337,
	title = {Linear Control Theory for Automation},
	url = {https://m2.mtmt.hu/api/publication/34048337},
	author = {Vajk, István and Hetthéssy, Jenő and Bars, Ruth},
	booktitle = {Springer Handbook of Automation},
	doi = {10.1007/978-3-030-96729-1_6},
	volume = {Part F674},
	unique-id = {34048337},
	year = {2023},
	pages = {121-161},
	orcid-numbers = {Vajk, István/0000-0002-2818-9162; Bars, Ruth/0000-0002-3467-0235}
}

@article{MTMT:33603748,
	title = {Tuning Parameter-free Model Predictive Control with Nonlinear Internal Model Control Structure for Vehicle Lateral Control},
	url = {https://m2.mtmt.hu/api/publication/33603748},
	author = {Kovács, Adorján and Vajk, István},
	doi = {10.12700/APH.20.2.2023.2.10},
	journal-iso = {ACTA POLYTECH HUNG},
	journal = {ACTA POLYTECHNICA HUNGARICA},
	volume = {20},
	unique-id = {33603748},
	issn = {1785-8860},
	year = {2023},
	eissn = {1785-8860},
	pages = {185-204},
	orcid-numbers = {Vajk, István/0000-0002-2818-9162}
}

@article{MTMT:32791606,
	title = {Optimization-based Model Predictive Tube Control for Autonomous Ground Vehicles with Minimal Tuning Parameters},
	url = {https://m2.mtmt.hu/api/publication/32791606},
	author = {Kovács, Adorján and Vajk, István},
	doi = {10.1142/S230138502350005X},
	journal-iso = {UNMANN SYST},
	journal = {UNMANNED SYSTEMS},
	volume = {11},
	unique-id = {32791606},
	issn = {2301-3850},
	abstract = {The trajectory planning and tracking problem are critical points of intelligent vehicles concerning their safety and stability. If these parts are separated, interactions should be made between them, especially when sudden changes and disturbances appear. This paper presents a method that integrates the two parts using a cascade structure. Additionally, the proposed method deals with the interaction between the lateral and the longitudinal trajectory based on dynamical considerations. The whole problem is handled using the model predictive method based on online optimization. This system receives the path borders as input and generates the control requests for the actuators on its output. The configuration space of the system can be maximized to gain stability by handling the lateral-longitudinal parts and the trajectory planning and tracking in one complex system. The main advantage of the proposed approach is that the optimization problem in the predictive method is formulated so that the path and dynamics are considered equality and inequality constraints, and the cost function includes only a physical phenomenon to be minimized without tuning parameters. The evaluation of the proposed algorithm is presented in this paper based on simulation and real-time measurements results.},
	year = {2023},
	eissn = {2301-3869},
	pages = {93-108},
	orcid-numbers = {Vajk, István/0000-0002-2818-9162}
}

@book{MTMT:32902177,
	title = {Proceedings of the Automation and Applied Computer Science Workshop 2022 (AACS'22)},
	url = {https://m2.mtmt.hu/api/publication/32902177},
	isbn = {9789634218753},
	editor = {Dunaev, Dmitriy and Vajk, István},
	publisher = {BME Department of Automation and Applied Informatics},
	unique-id = {32902177},
	year = {2022},
	orcid-numbers = {Vajk, István/0000-0002-2818-9162}
}

@inproceedings{MTMT:32583201,
	title = {Integrated Path Planning and Lateral-Longitudinal Control for Autonomous Electric Vehicles},
	url = {https://m2.mtmt.hu/api/publication/32583201},
	author = {Kovács, Adorján and Vajk, István},
	booktitle = {2021 AEIT International Conference on Electrical and Electronic Technologies for Automotive (AEIT AUTOMOTIVE)},
	doi = {10.23919/AEITAUTOMOTIVE52815.2021.9662798},
	unique-id = {32583201},
	year = {2021},
	pages = {1-6},
	orcid-numbers = {Vajk, István/0000-0002-2818-9162}
}

@article{MTMT:32514363,
	title = {Integrated Lateral and Longitudinal Control with Optimization-Based Allocation Strategy for Autonomous Electric Vehicles},
	url = {https://m2.mtmt.hu/api/publication/32514363},
	author = {Kovács, Adorján and Vajk, István},
	doi = {10.1155/2021/1444396},
	journal-iso = {J ADV TRANSPORT},
	journal = {JOURNAL OF ADVANCED TRANSPORTATION},
	volume = {2021},
	unique-id = {32514363},
	issn = {0197-6729},
	abstract = {This paper presents a novel approach for path-following control of a four-wheeled autonomous vehicle. The rear wheels of the vehicle are driven independently, all four wheels can be braked independently, and the front wheels are steered together. The proposed cascade structure consists of two convex optimization-based parts: one for path-following and another for the control allocation problem of the actuators. The control algorithm presents cost functions for the allocation problem focusing on safety. The proposed cost functions were examined and compared to former ones in a simulation environment. After all, the controller was tested in real-time test on a Lotus Evora test vehicle developed by ThyssenKrupp.},
	year = {2021},
	eissn = {2042-3195},
	orcid-numbers = {Vajk, István/0000-0002-2818-9162}
}

@inproceedings{MTMT:32452379,
	title = {Internal Model-Based Lateral and Longitudinal Control for Autonomous Electric Vehicles},
	url = {https://m2.mtmt.hu/api/publication/32452379},
	author = {Kovács, Adorján and Vajk, István},
	booktitle = {2021 25th International Conference on Methods and Models in Automation and Robotics (MMAR)},
	doi = {10.1109/MMAR49549.2021.9528430},
	unique-id = {32452379},
	year = {2021},
	pages = {360-365},
	orcid-numbers = {Vajk, István/0000-0002-2818-9162}
}

@inproceedings{MTMT:32452366,
	title = {Optimization-based Multi-actuator Control for Autonomous Vehicles},
	url = {https://m2.mtmt.hu/api/publication/32452366},
	author = {Kovács, Adorján and Vajk, István},
	booktitle = {2021 IEEE 25th International Conference on Intelligent Engineering Systems (INES)},
	doi = {10.1109/INES52918.2021.9512906},
	unique-id = {32452366},
	year = {2021},
	pages = {000049-000054},
	orcid-numbers = {Vajk, István/0000-0002-2818-9162}
}