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Glad, Torkel
Alternative names
Publications (10 of 182) Show all publications
Gunnarsson, S., Jung, Y., Veibäck, C. & Glad, T. (2016). IO (Implement and Operate) First in an Automatic Control Context. In: Jerker Björkqvist, Kristina Edström, Ronald J. Hugo, Juha Kontio, Janne Roslöf, Rick Sellens & Seppo Virtanen (Ed.), Proceedings of the 12th International CDIO Conference, Turku University of Applied Sciences,Turku, Finland, June 12-16, 2016: . Paper presented at The 12th International CDIO Conference, Turku University of Applied Sciences,Turku, Finland, June 12-16, 2016 (pp. 238-249). CDIO
Open this publication in new window or tab >>IO (Implement and Operate) First in an Automatic Control Context
2016 (English)In: Proceedings of the 12th International CDIO Conference, Turku University of Applied Sciences,Turku, Finland, June 12-16, 2016 / [ed] Jerker Björkqvist, Kristina Edström, Ronald J. Hugo, Juha Kontio, Janne Roslöf, Rick Sellens & Seppo Virtanen, CDIO , 2016, p. 238-249Conference paper, Published paper (Refereed)
Abstract [en]

A first course in Automatic control is presented.  A main objective of the course is to put most of the emphasis on the Implement and Operate phases in the process of developing a control system for a process. The course is built around a large amount of student active learning based on three extensive laboratory exercises, where each laboratory exercise can have duration of up to two weeks. For each of the laboratory exercises there is a sequence of learning activities supporting the students’ learning: Introductory lecture, problem solving session, preparation work, help-desk session, independent work in the laboratory, and a final demonstration of the control system. In addition there is a small project where the task is to write a manual for a process operator. The laboratory tasks involve implementation of a control system in an industrial PLC (Programmable Logic Controller) and development of an operator interface.

Place, publisher, year, edition, pages
CDIO, 2016
Series
Research Reports from Turku University of Applied Sciences, ISSN 1796-9964 ; 45
Keywords
Active learning, laboratory exercise, PLC-programming, operator interface, Standards 7, 8, 11
National Category
Control Engineering
Identifiers
urn:nbn:se:liu:diva-129383 (URN)978-952-216-610-4 (ISBN)
Conference
The 12th International CDIO Conference, Turku University of Applied Sciences,Turku, Finland, June 12-16, 2016
Available from: 2016-06-21 Created: 2016-06-17 Last updated: 2016-06-30Bibliographically approved
Axelsson, P., Axehill, D., Glad, T. & Norrlöf, M. (2014). Iterative Learning Control - From a Controllability Point of View. In: Proceedings of Reglermöte 2014: . Paper presented at Reglermöte 2014, Linköping, Sweden, 3-4 June, 2014.
Open this publication in new window or tab >>Iterative Learning Control - From a Controllability Point of View
2014 (English)In: Proceedings of Reglermöte 2014, 2014Conference paper, Published paper (Other academic)
National Category
Control Engineering
Identifiers
urn:nbn:se:liu:diva-107146 (URN)
Conference
Reglermöte 2014, Linköping, Sweden, 3-4 June, 2014
Projects
Vinnova Excellence Center LINK-SIC at Linköping University
Funder
Vinnova
Available from: 2014-06-05 Created: 2014-06-05 Last updated: 2016-08-31
Simon, D., Löfberg, J. & Glad, T. (2014). Reference Tracking MPC Using Dynamic Terminal Set Transformation. IEEE Transactions on Automatic Control, 59(10), 2790-2795
Open this publication in new window or tab >>Reference Tracking MPC Using Dynamic Terminal Set Transformation
2014 (English)In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 59, no 10, p. 2790-2795Article in journal (Refereed) Published
Abstract [en]

Among the many different formulations of Model Predictive Control (MPC) with guaranteed stability, one that has attracted significant attention is the formulation with a terminal cost and terminal constraint set, the so called dual mode formulation. In this technical note our goal is to make minimal changes to the dual mode framework, for the linear polytopic case, in order to develop a flexible reference tracking algorithm with guaranteed stability and low complexity, which is intuitive and easily understood. The main idea is to introduce a scaling variable that dynamically scales the terminal constraint set and therefore allows it to be centered around an arbitrary setpoint without violating the stability conditions. The main benefit of the algorithm is reduced complexity of the resulting QP compared to other state of art methods without loosing performance.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2014
Keywords
Nonlinear control systems; optimal control; optimization
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:liu:diva-112045 (URN)10.1109/TAC.2014.2313767 (DOI)000342924300017 ()
Note

Funding Agencies|Linkoping University; Saab Aeronautics; Swedish Governmental Agency for Innovation Systems (VINNOVA); Center for industrial information technology (CENIIT)

Available from: 2014-11-17 Created: 2014-11-13 Last updated: 2017-12-05
Lundquist, C., Skoglund, M., Granström, K. & Glad, T. (2013). Insights from Implementing a System for Peer-Review. IEEE Transactions on Education, 56(3), 261-267
Open this publication in new window or tab >>Insights from Implementing a System for Peer-Review
2013 (English)In: IEEE Transactions on Education, ISSN 0018-9359, E-ISSN 1557-9638, Vol. 56, no 3, p. 261-267Article in journal (Refereed) Published
Abstract [en]

Courses at the Master’s level in automatic control and signal processing cover mathematical theories and algorithms for control, estimation, and filtering. However, giving students practical experience in how to use these algorithms is also an important part of these courses. A goal is that the students should not only be able to understand and derive these algorithms, but also be able to apply them to real-life technical problems. The latter is achieved by assigning more time to the laboratory tutorials and designing them in such a way that the exercises are open for interpretation; an example of this would be giving the students more freedom to decide how to acquire the data needed to solve the given exercises.The students are asked to hand in a laboratory report in which they describe how they solved the exercises. This paper presents a double-blind peer-review process for laboratory reports, introduced at the Department of Electrical Engineering, Linköping University, Sweden. A survey was administered to students, and the results are summarized in this paper. Also discussed are the teachers’ experiences of peer review and of how students perform later in their education in writing their Master’s theses.

Keywords
Critical thinking, laboratory work, peer assessment, student learning, peer review, student self-assessment, team-based projects
National Category
Control Engineering
Identifiers
urn:nbn:se:liu:diva-96893 (URN)10.1109/TE.2012.2211876 (DOI)000322657200002 ()
Available from: 2013-08-28 Created: 2013-08-28 Last updated: 2017-12-06
Simon, D., Löfberg, J. & Glad, T. (2013). Nonlinear Model Predictive Control using Feedback Linearization and Local Inner Convex Constraint Approximations. In: Proceedings of the 2013 European Control Conference: . Paper presented at 2013 European Control Conference, July 17-19, Zurich, Switzerland (pp. 2056-2061).
Open this publication in new window or tab >>Nonlinear Model Predictive Control using Feedback Linearization and Local Inner Convex Constraint Approximations
2013 (English)In: Proceedings of the 2013 European Control Conference, 2013, p. 2056-2061Conference paper, Published paper (Refereed)
Abstract [en]

Model predictive control (MPC) is one of the most popular advanced control techniques and is used widely in industry. The main drawback with MPC is that it is fairly computationally expensive and this has so far limited its practical use for nonlinear systems.

To reduce the computational burden of nonlinear MPC, Feedback Linearization together with linear MPC has been used successfully to control nonlinear systems. The main drawback is that this results in an optimization problem with nonlinear constraints on the control signal.

In this paper we propose a method to handle the nonlinear constraints that arises using a set of dynamically generated local inner polytopic approximations. The main benefits of the proposed method is guaranteed recursive feasibility and convergence.

National Category
Control Engineering
Identifiers
urn:nbn:se:liu:diva-96743 (URN)000332509702074 ()978-39-5241-734-8 (ISBN)
Conference
2013 European Control Conference, July 17-19, Zurich, Switzerland
Funder
Vinnova, 2010-01255
Available from: 2013-08-26 Created: 2013-08-26 Last updated: 2014-04-25
Glad, T. (2012). Dealing with Inequalities in Polynomial Models. In: Proceedings of the 16th IFAC Symposium on System Identification: . Paper presented at 16th IFAC Symposium on System Identification(SYSID 2012), Brussels, Belgium, 11-13 July, 2012 (pp. 936-940).
Open this publication in new window or tab >>Dealing with Inequalities in Polynomial Models
2012 (English)In: Proceedings of the 16th IFAC Symposium on System Identification, 2012, p. 936-940Conference paper, Oral presentation only (Refereed)
Abstract [en]

It is described how set membership identification and model rejection for polynomial models can be described using polynomial inequalities and inequations. Using difference algebra methods these problems can be reduced to a form based on so called autoreduced sets. It is shown that these descriptions generalize state space descriptions. It is also discussed how special forms of autoreduced sets can make calculations based on interval methods easier to implement.

Keywords
Identification, Algebra, Polynomial
National Category
Control Engineering
Identifiers
urn:nbn:se:liu:diva-80800 (URN)10.3182/20120711-3-BE-2027.00287 (DOI)978-3-902823-06-9 (ISBN)
Conference
16th IFAC Symposium on System Identification(SYSID 2012), Brussels, Belgium, 11-13 July, 2012
Available from: 2012-09-11 Created: 2012-08-30 Last updated: 2013-07-10
Simon, D., Löfberg, J. & Glad, T. (2012). Reference Tracking MPC using Terminal Set Scaling. In: Proceedings of the 51st IEEE Conference on Decision and Control: . Paper presented at Proceedings of the 51st IEEE Conference on Decision and Control, Maui, HI, USA, 10-13 December, 2012 (pp. 4543-4548). IEEE conference proceedings
Open this publication in new window or tab >>Reference Tracking MPC using Terminal Set Scaling
2012 (English)In: Proceedings of the 51st IEEE Conference on Decision and Control, IEEE conference proceedings, 2012, p. 4543-4548Conference paper, Published paper (Refereed)
Abstract [en]

A common assumption when proving stability of linear MPC algorithms for tracking applications is to assume that the desired setpoint is located far into the interior of the feasible set. The reason for this is that the terminal state constraint set which is centered around the setpoint must be contained within the feasible set. In many applications this assumption can be severely limiting since the terminal set is relatively large and therefore limits how close the setpoint can be to the boundary of the feasible set. We present simple modifications that can be performed in order to guarantee stability and convergence to setpoints located arbitrarily close to the boundary of the feasible set. The main idea is to introduce a scaling variable which dynamically scales the terminal state constraint set and therefore allows a setpoint to be located arbitrarily close to the boundary. In addition to this the concept of pseudo setpoints is used to gain the maximum possible region of attraction and to handle infeasible references. Recursive feasibility and convergence to the desired setpoint, or its closest feasible alternative, is proven and a motivating example of controlling an agile fighter aircraft is given.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2012
Keywords
Model Predictive Control, MPC
National Category
Control Engineering
Identifiers
urn:nbn:se:liu:diva-89481 (URN)10.1109/CDC.2012.6426550 (DOI)000327200404141 ()978-1-4673-2065-8 (ISBN)978-1-4673-2064-1 (ISBN)
Conference
Proceedings of the 51st IEEE Conference on Decision and Control, Maui, HI, USA, 10-13 December, 2012
Projects
NFFP5
Funder
Vinnova, 2010-01255
Available from: 2013-02-26 Created: 2013-02-26 Last updated: 2014-01-17Bibliographically approved
Simon, D., Löfberg, J. & Glad, T. (2012). Reference Tracking MPC using Terminal Set Scaling. Linköping: Linköping University Electronic Press
Open this publication in new window or tab >>Reference Tracking MPC using Terminal Set Scaling
2012 (English)Report (Other academic)
Abstract [en]

A common assumption when proving stability of linear MPC algorithms fort racking applications is to assume that the desired setpoint is located farinto the interior of the feasible set. The reason for this is that the terminal state constraint set which is centered around the setpoint must be contained within the feasible set. In many applications this assumption can be severly limiting since the terminal set is relatively large and therefore limits how close the setpoint can be to the boundary of the feasible set. We present simple modifications that can be performed in order to guarantee stability and convergence to setpoints located arbitrarily close to the boundary of the feasible set. The main idea is to introduce a scaling variable which dynamically scales the terminal state constraint set and therefore allowsa setpoint to be located arbitrarily close to the boundary. In addition to this the concept of pseudo setpoints are used to gain the maximum possible region of attraction and to handle infeasible references. Recursive feasibility and convergence to the desired setpoint, or its closest feasible alternative, is proven and a motivating example of controlling an agile fighter aircraftis given.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2012. p. 17
Series
LiTH-ISY-R, ISSN 1400-3902 ; 3044
Keywords
MPC, Reference tracking, State constraints, Scaling, Invariant set
National Category
Control Engineering
Identifiers
urn:nbn:se:liu:diva-97988 (URN)LiTH-ISY-R-3044 (ISRN)
Funder
Vinnova
Available from: 2013-09-23 Created: 2013-09-23 Last updated: 2014-09-15Bibliographically approved
Lyzell, C., Glad, T., Enqvist, M. & Ljung, L. (2011). Difference Algebra and System Identification. Automatica, 47(9), 1896-1904
Open this publication in new window or tab >>Difference Algebra and System Identification
2011 (English)In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 47, no 9, p. 1896-1904Article in journal (Refereed) Published
Abstract [en]

The framework of differential algebra, especially Ritts algorithm, has turned out to be a useful tool when analyzing the identifiability of certain nonlinear continuous-time model structures. This framework provides conceptually interesting means to analyze complex nonlinear model structures via the much simpler linear regression models. One difficulty when working with continuous-time signals is dealing with white noise in nonlinear systems. In this paper, difference algebraic techniques, which mimic the differential-algebraic techniques, are presented. Besides making it possible to analyze discrete-time model structures, this opens up the possibility of dealing with noise. Unfortunately, the corresponding discrete-time identifiability results are not as conclusive as in continuous time. In addition, an alternative elimination scheme to Ritts algorithm will be formalized and the resulting algorithm is analyzed when applied to a special form of the NFIR model structure.

Place, publisher, year, edition, pages
Elsevier, 2011
Keywords
System identification, Identifiability, Ritts algorithm
National Category
Control Engineering
Identifiers
urn:nbn:se:liu:diva-71084 (URN)10.1016/j.automatica.2011.06.013 (DOI)000294877400006 ()
Projects
CADICS
Funder
Swedish Research CouncilVinnova
Available from: 2011-09-30 Created: 2011-09-30 Last updated: 2017-12-08
Tidefelt, H. & Glad, T. (2010). A Relaxation of the Strangeness Index. Linköping: Linköping University Electronic Press
Open this publication in new window or tab >>A Relaxation of the Strangeness Index
2010 (English)Report (Other academic)
Abstract [en]

A new index closely related to the strangeness index of a differential-algebraic equation is presented.Basic properties of the strangeness index are shown to be valid also for the new index. The definitionof the new index is conceptually simpler than that of the strangeness index, hence making it potentiallybetter suited for both practical applications and theoretical developments.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2010. p. 11
Series
LiTH-ISY-R, ISSN 1400-3902 ; 2932
Keywords
Differential-algebraic equations, Strangeness index
National Category
Control Engineering
Identifiers
urn:nbn:se:liu:diva-97541 (URN)LiTH-ISY-R-2932 (ISRN)
Available from: 2013-09-16 Created: 2013-09-16 Last updated: 2014-09-22Bibliographically approved
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