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Glad, T., Ljung, L. & Enqvist, M. (2024). Reglerteknik: grundläggande teori (5ed.). Lund: Studentlitteratur AB
Open this publication in new window or tab >>Reglerteknik: grundläggande teori
2024 (English)Book (Other academic)
Abstract [sv]

Reglerteknik förekommer numera i de flesta tekniska system: motorstyrning, antisladdsystem och farthållare i bilar; effektstyrning för mobiltelefoner; banföljning i industrirobotar; styrautomater i flygplan; styrning av allehanda kvalitetsvariabler i processindustrin liksom många tillämpningar inom konsumentelektronik...[Bokinfo]

Place, publisher, year, edition, pages
Lund: Studentlitteratur AB, 2024. p. 258 Edition: 5
Keywords
Reglerteknik
National Category
Control Engineering
Identifiers
urn:nbn:se:liu:diva-200628 (URN)9789144182155 (ISBN)
Available from: 2024-02-02 Created: 2024-02-02 Last updated: 2024-02-02Bibliographically approved
Zimmermann, S. A., Enqvist, M., Gunnarsson, S., Moberg, S. & Norrlöf, M. (2023). Experimental evaluation of a method for improving experiment design in robot identification. In: Marcia K. O'Malley (Ed.), 2023 IEEE International Conference on Robotics and Automation (ICRA): . Paper presented at IEEE International Conference on Robotics and Automation (ICRA), 29th May - 2nd June 2023, ExCel London (pp. 11432-11438). IEEE
Open this publication in new window or tab >>Experimental evaluation of a method for improving experiment design in robot identification
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2023 (English)In: 2023 IEEE International Conference on Robotics and Automation (ICRA) / [ed] Marcia K. O'Malley, IEEE , 2023, p. 11432-11438Conference paper, Published paper (Refereed)
Abstract [en]

The control system of industrial robots is often model-based, and the quality of the model of high importance. Therefore, a fast and easy-to-use process for finding the model parameters from a combination of prior knowledge and measurement data is required. It has been shown that the experiment design can be improved in terms of short experiment times and an accurate parameter estimate if the robot configurations for the identification experiments are selected carefully. Estimates of the information matrix can be generated based on simulations for a number of candidate configurations, and an optimization problem can be solved for finding the optimal configurations. This work shows that the proposed method for improved experiment design works with a real manipulator, i.e. it is demonstrated that the experiment time is reduced significantly and the accuracy of the parameter estimate can be maintained or reduced if experiments are conducted only in the optimal manipulator configurations. It is also shown that the model improvement is relevant for realizing accurate control. Finally, the experimental data reveals that, in order to further improve the model accuracy, a more advanced model structure is needed for taking into account the commonly present nonlinear transmission stiffness of the robotic joints.

Place, publisher, year, edition, pages
IEEE, 2023
National Category
Control Engineering
Identifiers
urn:nbn:se:liu:diva-196489 (URN)10.1109/icra48891.2023.10161092 (DOI)001048371103078 ()9798350323658 (ISBN)9798350323665 (ISBN)
Conference
IEEE International Conference on Robotics and Automation (ICRA), 29th May - 2nd June 2023, ExCel London
Note

Funding: Vinnova competence center LINK-SIC

Available from: 2023-08-09 Created: 2023-08-09 Last updated: 2023-10-11
Zimmermann, S. A., Enqvist, M., Gunnarsson, S., Moberg, S. & Norrlöf, M. (2022). Improving experiment design for frequency-domain identification of industrial robots. In: IFAC-PapersOnLine: . Paper presented at 2nd Modeling, Estimation and Control Conference MECC 2022: Jersey City, NJ, USA, 2–5 October 2022 (pp. 475-480). ELSEVIER, 55
Open this publication in new window or tab >>Improving experiment design for frequency-domain identification of industrial robots
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2022 (English)In: IFAC-PapersOnLine, ELSEVIER , 2022, Vol. 55, p. 475-480Conference paper, Published paper (Refereed)
Abstract [en]

For accurate control of industrial robots, a fast and easy-to-use method to estimate the model parameters based on experimental data is desired. This publication is about optimal experiment design in terms of short experiment times and an accurate parameter estimate. An optimization problem that is based on information matrices is solved for finding the optimal robot configurations for the identification experiment. A simulation study shows that the experiment time can be reduced significantly and the accuracy of the parameter estimate can be increased if experiments are conducted only in the optimal manipulator configurations. Furthermore, it is shown that a realistic estimate of the uncertainty in the frequency response function is crucial for successful experiment design.

Place, publisher, year, edition, pages
ELSEVIER, 2022
Keywords
Closed-loop identification, frequency-domain, nonlinear systems, industrial robots, optimal experiment design, covariance matrices
National Category
Robotics Control Engineering
Identifiers
urn:nbn:se:liu:diva-190387 (URN)10.1016/j.ifacol.2022.11.228 (DOI)000904629000077 ()
Conference
2nd Modeling, Estimation and Control Conference MECC 2022: Jersey City, NJ, USA, 2–5 October 2022
Available from: 2022-12-06 Created: 2022-12-06 Last updated: 2023-05-04Bibliographically approved
Ho, D., Hendeby, G. & Enqvist, M. (2020). A sensor-to-sensor model-based change detection approach for quadcopters. In: Proceedings of the 21st IFAC World Congress, 2020: . Paper presented at IFAC World Congress 2020, July 11-17, Germany (pp. 712-717). Elsevier, 53, Article ID 2.
Open this publication in new window or tab >>A sensor-to-sensor model-based change detection approach for quadcopters
2020 (English)In: Proceedings of the 21st IFAC World Congress, 2020, Elsevier, 2020, Vol. 53, p. 712-717, article id 2Conference paper, Published paper (Refereed)
Abstract [en]

This paper addresses the problem of change detection for a quadcopter in the presence ofwind disturbances. Different aspects of the quadcopter dynamics and various flight conditions have beeninvestigated. First, the wind is modeled using the Dryden wind model as a sum of a low-frequent and aturbulent part. Since the closed-loop control can compensate for system changes and disturbances andthe effect of the wind disturbance is significant, the residuals obtained from a standard simulation modelcan be misleading. Instead, a sensor-to-sensor submodel of the quadcopter is selected to detect a changein the payload using the Instrumental Variables (IV) cost function. It is shown that the mass variationcan be detected using the IV cost function in different flight scenarios.

Place, publisher, year, edition, pages
Elsevier, 2020
Series
IFAC PapersOnline
Keywords
sensor-to-sensor model, change detection, quadcopter, instrumental variables
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:liu:diva-170123 (URN)10.1016/j.ifacol.2020.12.820 (DOI)000652592500116 ()
Conference
IFAC World Congress 2020, July 11-17, Germany
Note

Funding: VINNOVA Competence Center LINK-SIC

Available from: 2020-09-29 Created: 2020-09-29 Last updated: 2021-10-04
Ho, D. & Enqvist, M. (2018). On the equivalence of inverse and forward IV estimators with application to quadcopter modeling. In: 18th IFAC Symposium on System Identification (SYSID), Proceedings: . Paper presented at 18th IFAC Symposium on System Identification (SYSID), Stockholm, Sweden, July 9-11, 2018 (pp. 951-956). Elsevier, 51(15)
Open this publication in new window or tab >>On the equivalence of inverse and forward IV estimators with application to quadcopter modeling
2018 (English)In: 18th IFAC Symposium on System Identification (SYSID), Proceedings, Elsevier, 2018, Vol. 51, no 15, p. 951-956Conference paper, Published paper (Refereed)
Abstract [en]

This paper concerns the estimation of a dynamic model from two measured signals when it is not clear which signal should be used as input to the model. In this case, both a forward and an inverse model can be estimated. Here, a basic instrumental variable approach is used and it is shown that the forward and inverse model estimators give identical parameter estimates provided that corresponding model structures have been used. Furthermore, it is shown that this scenario occurs when properties of a quadcopter are estimated from accelerometer and gyro signals and, hence, that it does not matter which signal is used as input.

Place, publisher, year, edition, pages
Elsevier, 2018
Series
IFAC papers online
National Category
Engineering and Technology Control Engineering
Identifiers
urn:nbn:se:liu:diva-152269 (URN)10.1016/j.ifacol.2018.09.071 (DOI)000446599200161 ()
Conference
18th IFAC Symposium on System Identification (SYSID), Stockholm, Sweden, July 9-11, 2018
Note

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 642153.

Available from: 2018-10-24 Created: 2018-10-24 Last updated: 2018-10-30Bibliographically approved
Ho, D., Linder, J., Hendeby, G. & Enqvist, M. (2017). Mass estimation of a quadcopter using IMU data. In: 2017 International Conference on Unmanned Aircraft Systems (ICUAS), June 13-16, 2017, Miami, FL, USA: . Paper presented at 2017 International Conference on Unmanned Aircraft Systems (ICUAS), June 13-16, 2017, Miami, FL, USA (pp. 1260-1266). Institute of Electrical and Electronics Engineers (IEEE)
Open this publication in new window or tab >>Mass estimation of a quadcopter using IMU data
2017 (English)In: 2017 International Conference on Unmanned Aircraft Systems (ICUAS), June 13-16, 2017, Miami, FL, USA, Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 1260-1266Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, an approach to estimate the mass of a quadcopter using only inertial measurements and pilot commands is presented. For this purpose, a lateral dynamic model describing the relation between the roll rate and the lateral acceleration is formulated. Due to the quadcopter’s inherent instability, a controller is used to stabilize the system and the data is collected in closed loop. Under the effect of feedback and disturbances, the inertial measurements used as input and output are correlated with the disturbances, which complicates the parameter estimation. The parameters of the model are estimated using several methods. The simulation and experimental results show that the instrumental-variable method has the best potential to estimate the mass of the quadcopter in this setup.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2017
National Category
Control Engineering
Identifiers
urn:nbn:se:liu:diva-139795 (URN)10.1109/ICUAS.2017.7991417 (DOI)000425255200155 ()9781509044955 (ISBN)9781509044962 (ISBN)
Conference
2017 International Conference on Unmanned Aircraft Systems (ICUAS), June 13-16, 2017, Miami, FL, USA
Projects
MarineUAS
Funder
EU, Horizon 2020, 642153
Note

Funding agencies: European Unions Horizon research and innovation programme under the Marie Sklodowska-Curie grant [642153]

Available from: 2017-08-16 Created: 2017-08-16 Last updated: 2018-03-21Bibliographically approved
Ho, D., Linder, J., Hendeby, G. & Enqvist, M. (2017). Vertical modeling of a quadcopter for mass estimation and diagnosis purposes. In: Proceedings of the Workshop on Research, Education and Development on Unmanned Aerial Systems, RED-UAS, Linköping, Sweden, 3-5 October, 2017: . Paper presented at Workshop on Research, Education and Development on Unmanned Aerial Systems, RED-UAS, Linköping, Sweden, 3-5 October, 2017. Institute of Electrical and Electronics Engineers (IEEE)
Open this publication in new window or tab >>Vertical modeling of a quadcopter for mass estimation and diagnosis purposes
2017 (English)In: Proceedings of the Workshop on Research, Education and Development on Unmanned Aerial Systems, RED-UAS, Linköping, Sweden, 3-5 October, 2017, Institute of Electrical and Electronics Engineers (IEEE), 2017Conference paper, Published paper (Refereed)
Abstract [en]

In this work, we estimate a model of the vertical dynamics of a quadcopter and explain how this model can be used for mass estimation and diagnosis of system changes. First, a standard thrust model describing the relation between the calculated control signals of the rotors and the thrust that is commonly used in literature is estimated. The estimation results are compared to those using a refined thrust model and it turns out that the refined model gives a significant improvement. The combination of a nonlinear model and closed-loop data poses some challenges and it is shown that an instrumental variables approach can be used to obtain accurate estimates. Furthermore, we show that the refined model opens up for fault detection of the quadcopter. More specifically, this model can be used for mass estimation and also for diagnosis of other parameters that might vary between and during missions.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2017
Keywords
payload, modeling, quadcopter, fault detection and isolation
National Category
Control Engineering
Identifiers
urn:nbn:se:liu:diva-141883 (URN)10.1109/RED-UAS.2017.8101665 (DOI)000427383700032 ()978-1-5386-0939-2 (ISBN)978-1-5386-0940-8 (ISBN)
Conference
Workshop on Research, Education and Development on Unmanned Aerial Systems, RED-UAS, Linköping, Sweden, 3-5 October, 2017
Projects
MarineUAS
Funder
EU, Horizon 2020, 642153
Note

This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 642153.

Available from: 2017-10-11 Created: 2017-10-11 Last updated: 2018-04-11Bibliographically approved
Linder, J., Enqvist, M., Fossen, T. I., Johansen, T. A. & Gustafsson, F. (2015). Modeling for IMU-based Online Estimation of a Ship's Mass and Center of Mass. Linköping: Linköping University Electronic Press
Open this publication in new window or tab >>Modeling for IMU-based Online Estimation of a Ship's Mass and Center of Mass
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2015 (English)Report (Other academic)
Abstract [en]

A ship's roll dynamics is very sensitive to changes in the loading conditions and a worst-case scenario is the loss of stability.  This paper proposes an approach for online estimation of a ship's mass and center of mass. Instead of focusing on a sensor-rich environment where all possible signals on a ship can be measured and a complete model of the ship can be estimated, a minimal approach is adopted. A model of the roll dynamics is derived from a well-established model in literature and it is assumed that only motion measurements from an inertial measurement unit together with measurements of the rudder angle are available. Furthermore, identifiability properties and disturbance characteristics of the model are presented. Due to the properties of the model, the parameters are estimated with an iterative instrumental variable approach to mitigate the influence of the disturbances and it uses multiple datasets simultaneously to overcome identifiability issues. Finally, a simulation study is presented to investigate the sensitivity to the initial conditions and it is shown that there is a low sensitivity for the desired parameters.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2015. p. 16
Series
LiTH-ISY-R, ISSN 1400-3902 ; 3082
Keywords
modelling, identification, operational safety, inertial measurement unit, identifiability, centre of mass, physical models, accelerometers, gyroscopes, marine systems
National Category
Control Engineering
Identifiers
urn:nbn:se:liu:diva-115546 (URN)LiTH-ISY-R-3082 (ISRN)
Available from: 2015-03-16 Created: 2015-03-16 Last updated: 2015-03-24Bibliographically approved
Linder, J., Enqvist, M., Fossen, T. I., Johansen, T. A. & Gustafsson, F. (2015). Modeling for IMU-based Online Estimation of a Ship's Mass and Center of Mass. In: Proceedings of the 10th Conference on Manoeuvring and Control of Marine Craft: . Paper presented at 10th Conference on Manoeuvring and Control of Marine Craft.
Open this publication in new window or tab >>Modeling for IMU-based Online Estimation of a Ship's Mass and Center of Mass
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2015 (English)In: Proceedings of the 10th Conference on Manoeuvring and Control of Marine Craft, 2015, , p. 16Conference paper, Published paper (Refereed)
Abstract [en]

A ship's roll dynamics is very sensitive to changes in the loading conditions and a worst-case scenario is the loss of stability.  This paper proposes an approach for online estimation of a ship's mass and center of mass. Instead of focusing on a sensor-rich environment where all possible signals on a ship can be measured and a complete model of the ship can be estimated, a minimal approach is adopted. A model of the roll dynamics is derived from a well-established model in literature and it is assumed that only motion measurements from an inertial measurement unit together with measurements of the rudder angle are available. Furthermore, identifiability properties and disturbance characteristics of the model are presented. Due to the properties of the model, the parameters are estimated with an iterative instrumental variable approach to mitigate the influence of the disturbances and it uses multiple datasets simultaneously to overcome identifiability issues. Finally, a simulation study is presented to investigate the sensitivity to the initial conditions and it is shown that the sensitivity is low for the desired parameters.

Publisher
p. 16
Series
IFAC-PapersOnLine, ISSN 2405-8963 ; 48(16)
Keywords
modelling, identification, operational safety, inertial measurement unit, identifiability, centre of mass, physical models, accelerometers, gyroscopes, marine systems
National Category
Control Engineering
Identifiers
urn:nbn:se:liu:diva-120993 (URN)10.1016/j.ifacol.2015.10.280 (DOI)
Conference
10th Conference on Manoeuvring and Control of Marine Craft
Available from: 2015-09-01 Created: 2015-09-01 Last updated: 2016-06-22
Jung, Y. & Enqvist, M. (2015). On estimation of approximate inverse models of block-oriented systems. In: Proceedings of the 17th IFAC Symposium on System Identification: . Paper presented at 17th IFAC Symposium on System Identification, Beijing, China, October 19-21, 2015 (pp. 1226-1231).
Open this publication in new window or tab >>On estimation of approximate inverse models of block-oriented systems
2015 (English)In: Proceedings of the 17th IFAC Symposium on System Identification, 2015, p. 1226-1231Conference paper, Published paper (Refereed)
Abstract [en]

This paper concerns the estimation of approximate (linear) inverse models of block-oriented systems and the presented results give an improved understanding of these approximations. The estimated inverse is intended to be used as a pre- or postdistorter of the original system and a good inverse model would thus be one that, when used in series with the original system, produces a signal that resembles the original input. An inverse model of a nonlinear system can either be estimated in the standard way (from input to output) and then inverted, or directly (from output to input). This choice will affect the model. In the general case, the two modeling approaches will lead to different models, which will be shown for Hammerstein and Wiener systems. However, for a noise-free Hammerstein system with a white Gaussian input, the two approaches will result in the same model, up to a constant. When the two models are not equal, and the goal is to use the inverse as described above, it can be beneficial to estimate an approximate inverse directly. It will also be illustrated in an example how the inverse estimate can be used to get a nonparametric estimate of the nonlinearity in a block-oriented system. 

Series
IFAC-PapersOnLine, ISSN 2405-8963 ; 48(28)
Keywords
system identification, nonlinear systems, block-oriented systems, inverse systems
National Category
Control Engineering
Identifiers
urn:nbn:se:liu:diva-122292 (URN)10.1016/j.ifacol.2015.12.299 (DOI)
Conference
17th IFAC Symposium on System Identification, Beijing, China, October 19-21, 2015
Available from: 2015-10-28 Created: 2015-10-28 Last updated: 2016-06-22
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0001-6523-8499

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