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Hansson, Anders, Professor
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Hansson, A. & Khoshfetrat Pakazad, S. (2018). Exploiting chordality in optimization algorithms for model predictive control. In: Large-scale and distributed optimization: (pp. 11-32). Cham: Springer, 2227
Öppna denna publikation i ny flik eller fönster >>Exploiting chordality in optimization algorithms for model predictive control
2018 (Engelska)Ingår i: Large-scale and distributed optimization, Cham: Springer, 2018, Vol. 2227, s. 11-32Kapitel i bok, del av antologi (Refereegranskat)
Abstract [en]

In this chapter we show that chordal structure can be used to devise efficient optimization methods for many common model predictive control problems. The chordal structure is used both for computing search directions efficiently as well as for distributing all the other computations in an interior-point method for solving the problem. The chordal structure can stem both from the sequential nature of the problem as well as from distributed formulations of the problem related to scenario trees or other formulations. The framework enables efficient parallel computations.

Ort, förlag, år, upplaga, sidor
Cham: Springer, 2018
Serie
Lecture Notes in Mathematics, ISSN 0075-8434 ; 2227
Nyckelord
Model predictive control; Quadratic programming; Chordal graphs; Message passing; Dynamic programming; Parallel computations
Nationell ämneskategori
Sannolikhetsteori och statistik
Identifikatorer
urn:nbn:se:liu:diva-154756 (URN)10.1007/978-3-319-97478-1_2 (DOI)000458487300003 ()9783319974781 (ISBN)9783319974774 (ISBN)
Tillgänglig från: 2019-02-26 Skapad: 2019-02-26 Senast uppdaterad: 2020-01-15Bibliografiskt granskad
Ahmadi, S. P. & Hansson, A. (2018). Parallel Exploitation for Tree-Structured Coupled Quadratic Programming in Julia. In: Proceedings of the 22nd International Conference on System Theory, Control and Computing: . Paper presented at 22nd International Conference on System Theory, Control and Computing, Sinaia, Romania, October 10-12, 2018 (pp. 597-602). IEEE
Öppna denna publikation i ny flik eller fönster >>Parallel Exploitation for Tree-Structured Coupled Quadratic Programming in Julia
2018 (Engelska)Ingår i: Proceedings of the 22nd International Conference on System Theory, Control and Computing, IEEE, 2018, s. 597-602Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

The main idea in this paper is to implement a distributed primal-dual interior-point algorithm for loosely coupled Quadratic Programming problems. We implement this in Julia and show how can we exploit parallelism in order to increase the computational speed. We investigate the performance of the algorithm on a Model Predictive Control problem.

Ort, förlag, år, upplaga, sidor
IEEE, 2018
Serie
INTERNATIONAL CONFERENCE ON SYSTEM THEORY, CONTROL AND COMPUTING (ICSTCC), ISSN 2372-1618
Nyckelord
Distributed Optimization, Julia, Model Predictive Control, Parallelization, Primal-Dual Interior-Point Method
Nationell ämneskategori
Reglerteknik
Identifikatorer
urn:nbn:se:liu:diva-157150 (URN)10.1109/ICSTCC.2018.8540646 (DOI)000465109800098 ()2-s2.0-85059933002 (Scopus ID)9781538644447 (ISBN)9781538644430 (ISBN)9781538644454 (ISBN)
Konferens
22nd International Conference on System Theory, Control and Computing, Sinaia, Romania, October 10-12, 2018
Forskningsfinansiär
Wallenberg AI, Autonomous Systems and Software Program (WASP)
Anmärkning

Funding agencies: Wallenberg AI, Autonomous Systems and Software Program (WASP) - Knut and Alice Wallenberg Foundation

Tillgänglig från: 2019-05-29 Skapad: 2019-05-29 Senast uppdaterad: 2019-06-12Bibliografiskt granskad
Kok, M., Khoshfetrat Pakazad, S., Schön, T., Hansson, A. & Hol, J. (2016). A Scalable and Distributed Solution to the Inertial Motion Capture Problem. In: Proceedings of the 19th International Conference on Information Fusion: . Paper presented at 19th International Conference on Information Fusion, Heidelberg, Germany, July 5-8, 2016 (pp. 1348-1355). Institute of Electrical and Electronics Engineers (IEEE)
Öppna denna publikation i ny flik eller fönster >>A Scalable and Distributed Solution to the Inertial Motion Capture Problem
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2016 (Engelska)Ingår i: Proceedings of the 19th International Conference on Information Fusion, Institute of Electrical and Electronics Engineers (IEEE), 2016, s. 1348-1355Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

In inertial motion capture, a multitude of body segments are equipped with inertial sensors, consisting of 3D accelerometers and 3D gyroscopes. Using an optimization-based approach to solve the motion capture problem allows for natural inclusion of biomechanical constraints and for modeling the connection of the body segments at the joint locations. The computational complexity of solving this problem grows both with the length of the data set and with the number of sensors and body segments considered. In this work, we present a scalable and distributed solution to this problem using tailored message passing, capable of exploiting the structure that is inherent in the problem. As a proof-of-concept we apply our algorithm to data from a lower body configuration. 

Ort, förlag, år, upplaga, sidor
Institute of Electrical and Electronics Engineers (IEEE), 2016
Nationell ämneskategori
Reglerteknik
Identifikatorer
urn:nbn:se:liu:diva-130555 (URN)000391273400178 ()978-0-9964-5274-8 (ISBN)
Konferens
19th International Conference on Information Fusion, Heidelberg, Germany, July 5-8, 2016
Projekt
CADICSELLIITThe project Probabilistic modeling of dynamical systems (Contract number: 621- 2013-5524)
Forskningsfinansiär
VetenskapsrådetELLIIT - The Linköping‐Lund Initiative on IT and Mobile Communications
Tillgänglig från: 2016-08-16 Skapad: 2016-08-16 Senast uppdaterad: 2017-02-03
Karami, F., Khoshfetrat Pakazad, S., Hansson, A. & Afshar, A. (2015). Automated Model Generation for Analysis of Large-scale Interconnected Uncertain Systems. Linköping: Linköping University Electronic Press
Öppna denna publikation i ny flik eller fönster >>Automated Model Generation for Analysis of Large-scale Interconnected Uncertain Systems
2015 (Engelska)Rapport (Övrigt vetenskapligt)
Abstract [en]

The first challenge in robustness analysis of large-scale interconnected uncertain systems is to provide a model of such systems in a standard-form that is required within different analysis frameworks. This becomes particularly important for large-scale systems, as analysis tools that can handle such systems heavily rely on the special structure within such model descriptions. We here propose an automated framework for providing such models of large-scale interconnected uncertain systems that are used in Integral Quadratic Constraint (IQC) analysis. Specifically, in this paper we put forth a methodological way to provide such models from a block-diagram and nested description of interconnected uncertain systems. We describe the details of this automated framework using an example.

Ort, förlag, år, upplaga, sidor
Linköping: Linköping University Electronic Press, 2015. s. 20
Serie
LiTH-ISY-R, ISSN 1400-3902 ; 3087
Nyckelord
LFT, Automated model generation, Large-scale analysis, Interconnected Uncertain Systems
Nationell ämneskategori
Reglerteknik
Identifikatorer
urn:nbn:se:liu:diva-123376 (URN)LiTH-ISY-R-3087 (ISRN)
Tillgänglig från: 2015-12-14 Skapad: 2015-12-14 Senast uppdaterad: 2018-09-17Bibliografiskt granskad
Khoshfetrat Pakazad, S., Andersen, M. S. & Hansson, A. (2015). Distributed solutions for loosely coupled feasibility problems using proximal splitting methods. Optimization Methods and Software, 30(1), 128-161
Öppna denna publikation i ny flik eller fönster >>Distributed solutions for loosely coupled feasibility problems using proximal splitting methods
2015 (Engelska)Ingår i: Optimization Methods and Software, ISSN 1055-6788, E-ISSN 1029-4937, Vol. 30, nr 1, s. 128-161Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

In this paper, we consider convex feasibility problems (CFPs) where the underlying sets are loosely coupled, and we propose several algorithms to solve such problems in a distributed manner. These algorithms are obtained by applying proximal splitting methods to convex minimization reformulations of CFPs. We also put forth distributed convergence tests which enable us to establish feasibility or infeasibility of the problem distributedly, and we provide convergence rate results. Under the assumption that the problem is feasible and boundedly linearly regular, these convergence results are given in terms of the distance of the iterates to the feasible set, which are similar to those of classical projection methods. In case the feasibility problem is infeasible, we provide convergence rate results that concern the convergence of certain error bounds.

Ort, förlag, år, upplaga, sidor
Taylor & Francis, 2015
Nyckelord
feasible/infeasible convex feasibility problems, proximal splitting, distributed solution, flow feasibility problem
Nationell ämneskategori
Reglerteknik
Identifikatorer
urn:nbn:se:liu:diva-110124 (URN)10.1080/10556788.2014.902056 (DOI)000345371800006 ()
Tillgänglig från: 2014-09-03 Skapad: 2014-09-03 Senast uppdaterad: 2017-12-05
Khoshfetrat Pakazad, S., Hansson, A. & Andersen, M. S. (2014). Distributed Interior-point Method for Loosely Coupled Problems. In: : . Paper presented at 19th IFAC world congress, The International Federation of Automatic Control, Cape Town, South Africa, August 24-29, 2014.
Öppna denna publikation i ny flik eller fönster >>Distributed Interior-point Method for Loosely Coupled Problems
2014 (Engelska)Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

In this paper, we put forth distributed algorithms for solving loosely coupled unconstrained and constrained optimization problems. Such problems are usually solved using algorithms that are based on a combination of decomposition and first order methods. These algorithms are commonly very slow and require many iterations to converge. In order to alleviate this issue, we propose algorithms that combine the Newton and interior-point methods with proximal splitting methods for solving such problems. Particularly, the algorithm for solving unconstrained loosely coupled problems, is based on Newton's method and utilizes proximal splitting to distribute the computations for calculating the Newton step at each iteration. A combination of this algorithm and the interior-point method is then used to introduce a distributed algorithm for solving constrained loosely coupled problems. We also provide guidelines on how to implement the proposed methods efficiently and briefly discuss the properties of the resulting solutions.

Nationell ämneskategori
Reglerteknik
Identifikatorer
urn:nbn:se:liu:diva-110126 (URN)
Konferens
19th IFAC world congress, The International Federation of Automatic Control, Cape Town, South Africa, August 24-29, 2014
Tillgänglig från: 2014-09-03 Skapad: 2014-09-03 Senast uppdaterad: 2014-10-01
Khoshfetrat Pakazad, S., Hansson, A., Andersen, M. S. & Rantzer, A. (2014). Distributed Robustness Analysis of Interconnected Uncertain Systems Using Chordal Decomposition. In: Edward Boje and Xiaohua Xia (Ed.), Proceedings of the 19th IFAC World Congress, 2014: . Paper presented at 19th IFAC world congress, The International Federation of Automatic Control, Cape Town, South Africa, August 24-29, 2014 (pp. 2594-2599). International Federation of Automatic Control
Öppna denna publikation i ny flik eller fönster >>Distributed Robustness Analysis of Interconnected Uncertain Systems Using Chordal Decomposition
2014 (Engelska)Ingår i: Proceedings of the 19th IFAC World Congress, 2014 / [ed] Edward Boje and Xiaohua Xia, International Federation of Automatic Control , 2014, s. 2594-2599Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

Large-scale interconnected uncertain systems commonly have large state and uncertainty dimensions. Aside from the heavy computational cost of solving centralized robust stability analysis techniques, privacy requirements in the network can also introduce further issues. In this paper, we utilize IQC analysis for analyzing large-scale interconnected uncertain systems and we evade these issues by describing a decomposition scheme that is based on the interconnection structure of the system. This scheme is based on the so-called chordal decomposition and does not add any conservativeness to the analysis approach. The decomposed problem can be solved using distributed computational algorithms without the need for a centralized computational unit. We further discuss the merits of the proposed analysis approach using a numerical experiment.

Ort, förlag, år, upplaga, sidor
International Federation of Automatic Control, 2014
Serie
World Congress, ISSN 1474-6670 ; Volume 19, Part 1
Nationell ämneskategori
Reglerteknik
Identifikatorer
urn:nbn:se:liu:diva-110127 (URN)10.3182/20140824-6-ZA-1003.01649 (DOI)978-3-902823-62-5 (ISBN)
Konferens
19th IFAC world congress, The International Federation of Automatic Control, Cape Town, South Africa, August 24-29, 2014
Tillgänglig från: 2014-09-03 Skapad: 2014-09-03 Senast uppdaterad: 2015-05-19Bibliografiskt granskad
Hansson, A. & Verhaegen, M. (2014). Distributed system identification with ADMM. In: Proceedings of the 53rd IEEE Conference on Decision and Control: . Paper presented at 53rd IEEE Conference on Decision and Control 15-17 Dec. 2014, Los Angeles, CA (pp. 290-295). Los Angeles
Öppna denna publikation i ny flik eller fönster >>Distributed system identification with ADMM
2014 (Engelska)Ingår i: Proceedings of the 53rd IEEE Conference on Decision and Control, Los Angeles, 2014, s. 290-295Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

This paper presents identification of both network connected systems as well as distributed systems governed by PDEs in the framework of distributed optimization via the Alternating Direction Method of Multipliers. This approach opens first the possibility to identify distributed models in a global manner using all available data sequences and second the possibility for a distributed implementation. The latter will make the application to large scale complex systems possible. In addition to outlining a new large scale identification method, illustrations are shown for identifying both network connected systems and discretized PDEs.

Ort, förlag, år, upplaga, sidor
Los Angeles: , 2014
Serie
53rd IEEE Conference on Decision and Control, ISSN 0191-2216
Nationell ämneskategori
Datavetenskap (datalogi)
Identifikatorer
urn:nbn:se:liu:diva-129292 (URN)10.1109/CDC.2014.7039396 (DOI)978-1-4799-7745-1 (ISBN)978-1-4673-6088-3 (ISBN)
Konferens
53rd IEEE Conference on Decision and Control 15-17 Dec. 2014, Los Angeles, CA
Tillgänglig från: 2016-06-15 Skapad: 2016-06-15 Senast uppdaterad: 2018-01-10
Thomas, J. & Hansson, A. (2014). Enumerative nonlinear model predictive control for linear induction motor using load observer. In: 2014 UKACC International Conference on Control, CONTROL 2014 - Proceedings: . Paper presented at 10th UKACC International Conference on Control, CONTROL 2014 (pp. 373-377). Institute of Electrical and Electronics Engineers Inc. ( 6915169)
Öppna denna publikation i ny flik eller fönster >>Enumerative nonlinear model predictive control for linear induction motor using load observer
2014 (Engelska)Ingår i: 2014 UKACC International Conference on Control, CONTROL 2014 - Proceedings, Institute of Electrical and Electronics Engineers Inc. , 2014, nr 6915169, s. 373-377Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

Enumerative nonlinear model predictive control for speed tracking problem of linear induction motors has been presented in [1], where the authors show that this control scheme has better performance as compared to direct torque control. In this paper, the authors show that using a load observer for integral action, the performance can be further improved. Specifically simulation results show that a load observer results in better tracking properties and offers more robust control.

Ort, förlag, år, upplaga, sidor
Institute of Electrical and Electronics Engineers Inc., 2014
Serie
2014 UKACC International Conference on Control, CONTROL 2014 - Proceedings
Nyckelord
Integral Action; Inverter; Linear Induction Motor; Load Observer; Nonlinear Model Predictive Control; Speed Tracking Control
Nationell ämneskategori
Elektroteknik och elektronik
Identifikatorer
urn:nbn:se:liu:diva-116789 (URN)10.1109/CONTROL.2014.6915169 (DOI)000352626000064 ()2-s2.0-84921520732 (Scopus ID)9781479950119 (ISBN)
Konferens
10th UKACC International Conference on Control, CONTROL 2014
Tillgänglig från: 2015-04-07 Skapad: 2015-04-02 Senast uppdaterad: 2015-05-11
Wallin, R. & Hansson, A. (2014). Maximum likelihood estimation of linear SISO models subject to missing output data and missing input data. International Journal of Control, 87(11), 2354-2364
Öppna denna publikation i ny flik eller fönster >>Maximum likelihood estimation of linear SISO models subject to missing output data and missing input data
2014 (Engelska)Ingår i: International Journal of Control, ISSN 0020-7179, E-ISSN 1366-5820, Vol. 87, nr 11, s. 2354-2364Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

In this paper we describe an approach to maximum likelihood estimation of linear single input single output (SISO) models when both input and output data are missing. The criterion minimised in the algorithms is the Euclidean norm of the prediction error vector scaled by a particular function of the covariance matrix of the observed output data. We also provide insight into when simpler and in general sub-optimal schemes are indeed optimal. The algorithm has been prototyped in MATLAB, and we report numerical results that support the theory.

Ort, förlag, år, upplaga, sidor
Taylor and Francis: STM, Behavioural Science and Public Health Titles, 2014
Nyckelord
system identification; maximum likelihood estimation; missing data
Nationell ämneskategori
Elektroteknik och elektronik
Identifikatorer
urn:nbn:se:liu:diva-111470 (URN)10.1080/00207179.2014.913346 (DOI)000341955300012 ()
Tillgänglig från: 2014-10-17 Skapad: 2014-10-17 Senast uppdaterad: 2017-12-05
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