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Optimal trajectory generation using MPC in robotino and its implementation with ROS system

Research output: Contributions to collected editions/works › Contributions to collected editions/anthologies › Research › peer-review

Standard

Optimal trajectory generation using MPC in robotino and its implementation with ROS system. / Mercorelli, Paolo; Voss, Thomas; Straßberger, Daniel et al.
Proceedings - 2017 IEEE International Symposium on Industrial Electronics, ISIE 2017: Proceedings. Piscataway: IEEE - Institute of Electrical and Electronics Engineers Inc., 2017. p. 1642-1647 8001493 (IEEE International Symposium on Industrial Electronics).

Research output: Contributions to collected editions/works › Contributions to collected editions/anthologies › Research › peer-review

Harvard

Mercorelli, P, Voss, T, Straßberger, D, Sergiyenko, O & Lindner, L 2017, Optimal trajectory generation using MPC in robotino and its implementation with ROS system. in Proceedings - 2017 IEEE International Symposium on Industrial Electronics, ISIE 2017: Proceedings., 8001493, IEEE International Symposium on Industrial Electronics, IEEE - Institute of Electrical and Electronics Engineers Inc., Piscataway, pp. 1642-1647. https://doi.org/10.1109/ISIE.2017.8001493

APA

Mercorelli, P., Voss, T., Straßberger, D., Sergiyenko, O., & Lindner, L. (2017). Optimal trajectory generation using MPC in robotino and its implementation with ROS system. In Proceedings - 2017 IEEE International Symposium on Industrial Electronics, ISIE 2017: Proceedings (pp. 1642-1647). Article 8001493 (IEEE International Symposium on Industrial Electronics). IEEE - Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISIE.2017.8001493

Vancouver

Mercorelli P, Voss T, Straßberger D, Sergiyenko O, Lindner L. Optimal trajectory generation using MPC in robotino and its implementation with ROS system. In Proceedings - 2017 IEEE International Symposium on Industrial Electronics, ISIE 2017: Proceedings. Piscataway: IEEE - Institute of Electrical and Electronics Engineers Inc. 2017. p. 1642-1647. 8001493. (IEEE International Symposium on Industrial Electronics). doi: 10.1109/ISIE.2017.8001493

Bibtex

@inbook{d32322056593489abc7b0821c9be41c5,
title = "Optimal trajectory generation using MPC in robotino and its implementation with ROS system",
abstract = "Mobile robots are remarkable cases of high development technology and systems. Robot community developed a complex analysis to meet the increased demands for the control challenges for the movement of Robot. A model predictive control (MPC) approach is used in combination with feedforward Controller in a context of decoupling controller. Implementation of this algorithm in the ROS system is presented at the end of the contribution.",
keywords = "Engineering, Controllers, ndustrial electronics, Motion control, Predictive control systems, Robots, Model predictive control, motion control, ROS",
author = "Paolo Mercorelli and Thomas Voss and Daniel Stra{\ss}berger and Oleg Sergiyenko and Lars Lindner",
year = "2017",
month = aug,
day = "3",
doi = "10.1109/ISIE.2017.8001493",
language = "English",
series = "IEEE International Symposium on Industrial Electronics",
publisher = "IEEE - Institute of Electrical and Electronics Engineers Inc.",
pages = "1642--1647",
booktitle = "Proceedings - 2017 IEEE International Symposium on Industrial Electronics, ISIE 2017",
address = "United States",

}

RIS

TY - CHAP

T1 - Optimal trajectory generation using MPC in robotino and its implementation with ROS system

AU - Mercorelli, Paolo

AU - Voss, Thomas

AU - Straßberger, Daniel

AU - Sergiyenko, Oleg

AU - Lindner, Lars

PY - 2017/8/3

Y1 - 2017/8/3

N2 - Mobile robots are remarkable cases of high development technology and systems. Robot community developed a complex analysis to meet the increased demands for the control challenges for the movement of Robot. A model predictive control (MPC) approach is used in combination with feedforward Controller in a context of decoupling controller. Implementation of this algorithm in the ROS system is presented at the end of the contribution.

AB - Mobile robots are remarkable cases of high development technology and systems. Robot community developed a complex analysis to meet the increased demands for the control challenges for the movement of Robot. A model predictive control (MPC) approach is used in combination with feedforward Controller in a context of decoupling controller. Implementation of this algorithm in the ROS system is presented at the end of the contribution.

KW - Engineering

KW - Controllers

KW - ndustrial electronics

KW - Motion control

KW - Predictive control systems

KW - Robots

KW - Model predictive control

KW - motion control

KW - ROS

UR - http://ieeexplore.ieee.org/abstract/document/8001493/

UR - http://www.scopus.com/inward/record.url?scp=85029897635&partnerID=8YFLogxK

U2 - 10.1109/ISIE.2017.8001493

DO - 10.1109/ISIE.2017.8001493

M3 - Contributions to collected editions/anthologies

T3 - IEEE International Symposium on Industrial Electronics

SP - 1642

EP - 1647

BT - Proceedings - 2017 IEEE International Symposium on Industrial Electronics, ISIE 2017

PB - IEEE - Institute of Electrical and Electronics Engineers Inc.

CY - Piscataway

ER -

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An Over-Actuated Hexacopter Tilt-Rotor UAV Prototype for Agriculture of Precision: Modeling and Control

Pimentel, G. O., Santos, M. F. D., Lima, J., Mercorelli, P. & Fernandes, F. M., 15.01.2025, In: Sensors. 25, 2, 27 p., 479.

Research output: Journal contributions › Journal articles › Research › peer-review

Automatic Tuning of Extended Kalman Filter in Synchronous Reluctance Motor Drives with a Master-Slave Configuration

Rigon, S., Haus, B., Mercorelli, P. & Zigliotto, M., 27.02.2025, (E-pub ahead of print) In: IEEE Open Journal of Power Electronics. 14 p.

Research output: Journal contributions › Journal articles › Research › peer-review

Dynamic Performance Analysis and Fault Ride-Through Enhancement by a Modified Fault Current Protection Scheme of a Grid-Connected Doubly Fed Induction Generator

Talani, R. A., Kaloi, G. S., Ali, A., Bijarani, M. A., Abbas, G., Hatatah, M., Mercorelli, P. & Touti, E., 02.2025, In: Machines. 13, 2, 20 p., 110.

Research output: Journal contributions › Journal articles › Research › peer-review

Inner loop model predictive control and outer loop PI reference governor for PMSMs with input and state saturation for torque control

Zwerger, T. & Mercorelli, P., 01.02.2025, In: Mathematics and Computers in Simulation. 228, p. 178-201 24 p.

Research output: Journal contributions › Journal articles › Research › peer-review

Neural Network-Based Finite-Time Control for Stochastic Nonlinear Systems with Input Dead-Zone and Saturation

Kharrat, M., Krichen, M., Alhazmi, H. & Mercorelli, P., 11.01.2025, (E-pub ahead of print) In: Arabian Journal for Science and Engineering. 11 p.

Research output: Journal contributions › Journal articles › Research › peer-review

DOI

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