| 1. |
- Axehill, Daniel, 1978-
(författare)
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Applications of Integer Quadratic Programming in Control and Communication
- 2005
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The main topic of this thesis is integer quadratic programming with applications to problems arising in the areas of automatic control and communication. One of the most widespread modern control principles is the discrete-time method Model Predictive Control (MPC). The main advantage with MPC, compared to most other control principles, is that constraints on control signals and states can easily be handled. In each time step, MPC requires the solution of a Quadratic Programming (QP) problem. To be able to use MPC for large systems, and at high sampling rates, optimization routines tailored for MPC are used. In recent years, the range of application of MPC has been extended from constrained linear systems to so-called hybrid systems. Hybrid systems are systems where continuous dynamics interact with logic. When this extension is made, binary variables are introduced in the problem. As a consequence, the QP problem has to be replaced by a far more challenging Mixed Integer Quadratic Programming (MIQP) problem. Generally, for this type of optimization problems, the computational complexity is exponential in the number of binary optimization variables. In modern communication systems, multiple users share a so-called multi-access channel, where the information sent by different users is separated by using almost orthogonal codes. Since the codes are not completely orthogonal, the decoded information at the receiver is slightly correlated between different users. Further, noise is added during the transmission. To estimate the information originally sent, a maximum likelihood problem involving binary variables is solved. The process of simultaneously estimating the information sent by multiple users is called multiuser detection. In this thesis, the problem to efficiently solve MIQP problems originating from MPC is addressed. Two different algorithms are presented. First, a polynomial complexity preprocessing algorithm for binary quadratic programming problems is presented. By using the algorithm, some, or all, binary variables can be computed efficiently already in the preprocessing phase. In simulations, the algorithm is applied to unconstrained MPC problems with a mixture of real and binary control signals. It has also been applied to the multiuser detection problem, where simulations have shown that the bit error rate can be significantly reduced by using the proposed algorithm as compared to using common suboptimal algorithms. Second, an MIQP algorithm tailored for MPC is presented. The algorithm uses a branch and bound method where the relaxed node problems are solved by a dual active set QP algorithm. In this QP algorithm, the KKT-systems are solved using Riccati recursions in order to decrease the computational complexity. Simulation results show that both the QP solver and the MIQP solver proposed have lower computational complexity than corresponding generic solvers.
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| 2. |
- Parvini Ahmadi, Shervin, 1989-
(författare)
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Distributed Optimization for Control and Estimation
- 2022
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Adopting centralized optimization approaches in order to solve optimization problem arising from analyzing large-scale systems, requires a powerful computational unit. Such units, however, do not always exist. In addition, it is not always possible to form the optimization problem in a centralized manner due to structural constraints or privacy requirements. A possible solution in these cases is to use distributed optimization approaches. Many large-scale systems have inherent structures which can be exploited to develop scalable optimization approaches. In this thesis, chordal graph properties are used in order to design tailored distributed optimization approaches for applications in control and estimation, and especially for model predictive control and localization problems. The first contribution concerns a distributed primal-dual interior-point algorithm for which it is investigated how parallelism can be exploited. In particular, it is shown how the computations of the algorithm can be distributed on different processors so that they can be run in parallel. As a result, the algorithm execution time is accelerated compared to the case where the algorithm is run on a single processor. Simulation studies on linear model predictive control and robust model predictive control confirm the efficiency of the framework. The second contribution is to devise a tailored distributed algorithm for nonlinear least squares with application to a sensor network location problem. It relies on the Levenberg-Marquardt algorithm, in which the computations are distributed using message passing over the computational graph of the problem, which is obtained from what is known as the clique tree of the problem. The results indicate that the algorithm provides not only a good localization accuracy, but also it requires fewer iterations and communications between computational agents in order to converge compared to known first-order methods. The third contribution is a study of extending the message passing idea in order to design tailored distributed algorithm for general non-convex problems. The framework relies on an augmented Lagrangian algorithm in which a primal-dual interior-point method is used for the inner iteration. Application of the framework for general model predictive control of systems with several interconnected sub-systems is extensively investigated. The performance of the framework is then compared with distributed methods based on the alternating direction method of multipliers, where the superiority of the framework is illustrated.
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| 3. |
- Hansson, Adam, 1993, et al.
(författare)
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Preventing E. coli Biofilm Formation with Antimicrobial Peptide-Functionalized Surface Coatings: Recognizing the Dependence on the Bacterial Binding Mode Using Live-Cell Microscopy
- 2024
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Ingår i: ACS APPLIED MATERIALS & INTERFACES. - : American Chemical Society. - 1944-8244 .- 1944-8252. ; 16:6, s. 6799-6812
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Tidskriftsartikel (refereegranskat)abstract
- Antimicrobial peptides (AMPs) can kill bacteria by destabilizing their membranes, yet translating these molecules' properties into a covalently attached antibacterial coating is challenging. Rational design efforts are obstructed by the fact that standard microbiology methods are ill-designed for the evaluation of coatings, disclosing few details about why grafted AMPs function or do not function. It is particularly difficult to distinguish the influence of the AMP's molecular structure from other factors controlling the total exposure, including which type of bonds are formed between bacteria and the coating and how persistent these contacts are. Here, we combine label-free live-cell microscopy, microfluidics, and automated image analysis to study the response of surface-bound Escherichia coli challenged by the same small AMP either in solution or grafted to the surface through click chemistry. Initially after binding, the grafted AMPs inhibited bacterial growth more efficiently than did AMPs in solution. Yet, after 1 h, E. coli on the coated surfaces increased their expression of type-1 fimbriae, leading to a change in their binding mode, which diminished the coating's impact. The wealth of information obtained from continuously monitoring the growth, shape, and movements of single bacterial cells allowed us to elucidate and quantify the different factors determining the antibacterial efficacy of the grafted AMPs. We expect this approach to aid the design of elaborate antibacterial material coatings working by specific and selective actions, not limited to contact-killing. This technology is needed to support health care and food production in the postantibiotic era.
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| 4. |
- Bryngelsson, Mårten, et al.
(författare)
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Energy policy on shaky ground? : A study of CCS-scenarios
- 2009
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Ingår i: Energy Procedia. - : Elsevier BV. - 1876-6102. ; :1, s. 4673-4680
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Tidskriftsartikel (refereegranskat)abstract
- Scenarios play an important role for the societal acceptance of CCS. This paper looks into influential reports containing CCS scenarios and analyses results, key assumptions and drivers for CCS' deployment. Significant uncertainties regarding CCS' development were in several cases excluded or marginalized. Despite these shortcomings, scenarios support a massive deployment of CCS and reflect an undivided optimism. If CCS would fail to meet the high expectations a backlash could follow. Indications were found that new scenarios including uncertainties are needed to balance this over-optimism. So-called unpleasant scenarios are often valuable in helping decision makers develop flexible strategies and policies.
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| 5. |
- Vernersson, Tore V, 1968, et al.
(författare)
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Wheel tread damage – a numerical study of railway wheel tread plasticity under thermomechanical loading
- 2010
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Ingår i: Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit. - 0954-4097 .- 2041-3017. ; 224:5, s. 435-443
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Tidskriftsartikel (refereegranskat)abstract
- A numerical study is presented where the impact of simultaneous thermal and mechanical loading on a railway wheel tread, as imposed by braking and rolling contact, is reported. A comparison is made of two-dimensional (2D) and 3D finite-element simulations of the thermomechanical problem featuring a material model that accounts for thermal expansion and plastic deformations. It is found that 2D simulations give unrealistic predictions of plastic deformations. The 3D simulations demonstrate a significant influence of the thermal loading also in cases of rather moderate temperature increases. In particular, the combination of thermal loading and high traction is found to be very detrimental.
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| 6. |
- Rydén, Bo, 1957, et al.
(författare)
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Fjärrvärmens Affärsmodeller: Slutrapport för Fjärrsynprojekt
- 2013
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Fjärrvärmen är en integrerad del av det framtida hållbara energisystemet, med ambitionen att i än högre grad bidra till de samhälleliga målen om låga utsläpp från uppvärmning, minskad användning av primärenergi och synergier med andra sektorer, exempelvis energiåtervinning från avfall, industrier och avloppsrening. Som produkt och bransch har fjärrvärmen gjort en betydande resa sedan starten för mer än 50 år sedan och den har genomgått en omfattande utveckling, framför allt inom teknikområdet. Nya utmaningar och förändrade omvärldsförhållanden ställer dock nya och ökade krav på fjärrvärmeaffären och fjärrvärmeföretagens affärsmodeller. Fjärrvärmens Affärsmodeller är ett tvärvetenskapligt forskningsprojekt som genomförts inom ramen för forskningsprogrammet Fjärrsyn. Projektet har pågått under 2010-2013. Målsättningen har varit att generera ny kunskap och bättre verktyg för att konkurrenskraftiga affärsmodeller skall kunna utvecklas. Syftet är att stärka fjärrvärmen, att uppmuntra affärsutveckling och att skapa resurseffektiva lösningar för framtidens hållbara energisystem, till nytta för fjärrvärmebranschen, kunderna, miljön och samhället i stort. Inom ramen för olika delstudier har vi bland annat undersökt hur fjärrvärmeföretag skapar och levererar värde, möter sina kunder, använder sina nyckelresurser, hur intäkter uppstår och hur väl organisationen utnyttjas. Vi har även analyserat de utmaningar företagen står inför, fjärrvärmeaffärens möjligheter att tackla dagens komplexa problem, liksom dess förutsättningar för att utvecklas och generera långsiktigt uthålligt värde. Denna slutrapport redovisar projektets forskningsresultat och slutsatser, samt beskriver det breda tvärvetenskapliga arbetssättet och den aktiva och omfattande kommunikation som tillämpas mellan forskningsprojektet och dess intressenter. I tre lättlästa temaböcker har projektet också redovisat resultat och metoder om hur dagens prismodeller kan utvecklas, hur kunddialogen och kundens förtroende kan stärkas och hur fjärrvärmeaffären som helhet kan utvecklas.
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| 7. |
- Arnström, Daniel, 1994-
(författare)
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On Complexity Certification of Active-Set QP Methods with Applications to Linear MPC
- 2021
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- In model predictive control (MPC) an optimization problem has to be solved at each time step, which in real-time applications makes it important to solve these efficiently and to have good upper bounds on worst-case solution time. Often for linear MPC problems, the optimization problem in question is a quadratic program (QP) that depends on parameters such as system states and reference signals. A popular class of methods for solving such QPs is active-set methods, where a sequence of linear systems of equations is solved. The primary contribution of this thesis is a method which determines which sequence of subproblems a popular class of such active-set algorithms need to solve, for every possible QP instance that might arise from a given linear MPC problem (i.e, for every possible state and reference signal). By knowing these sequences, worst-case bounds on how many iterations, floating-point operations and, ultimately, the maximum solution time, these active-set algorithms require to compute a solution can be determined, which is of importance when, e.g, linear MPC is used in safety-critical applications. After establishing this complexity certification method, its applicability is extended by showing how it can be used indirectly to certify the complexity of another, efficient, type of active-set QP algorithm which reformulates the QP as a nonnegative least-squares method. Finally, the proposed complexity certification method is extended further to situations when enhancements to the active-set algorithms are used, namely, when they are terminated early (to save computations) and when outer proximal-point iterations are performed (to improve numerical stability).
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| 8. |
- Arnström, Daniel, 1994-
(författare)
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Real-Time Certified MPC : Reliable Active-Set QP Solvers
- 2023
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- In Model Predictive Control (MPC), optimization problems are solved recurrently to produce control actions. When MPC is used in real time to control safety-critical systems, it is important to solve these optimization problems with guarantees on the worst-case execution time. In this thesis, we take aim at such worst-case guarantees through two complementary approaches:(i) By developing methods that determine exact worst-case bounds on the computational complexity and execution time for deployed optimization solvers.(ii) By developing efficient optimization solvers that are tailored for the given application and hardware at hand.We focus on linear MPC, which means that the optimization problems in question are quadratic programs (QPs) that depend on parameters such as system states and reference signals. For solving such QPs, we consider active-set methods: a popular class of optimization algorithms used in real-time applications.The first part of the thesis concerns complexity certification of well-established active-set methods. First, we propose a certification framework that determines the sequence of subproblems that a class of active-set algorithms needs to solve, for every possible QP instance that might arise from a given linear MPC problem (i.e., for every possible state and reference signal). By knowing these sequences, one can exactly bound the number of iterations and/or floating-point operations that are required to compute a solution. In a second contribution, we use this framework to determine the exact worst-case execution time (WCET) for linear MPC. This requires factors such as hardware and software implementation/compilation to be accounted for in the analysis. The framework is further extended in a third contribution by accounting for internal numerical errors in the solver that is certified. In a similar vein, a fourth contribution extends the framework to handle proximal-point iterations, which can be used to improve the numerical stability of QP solvers, furthering their reliability.The second part of the thesis concerns efficient solvers for real-time MPC. We propose an efficient active-set solver that is contained in the above-mentioned complexity-certification framework. In addition to being real-time certifiable, we show that the solver is efficient, simple to implement, can easily be warm-started, and is numerically stable, all of which are important properties for a solver that is used in real-time MPC applications. As a final contribution, we use this solver to exemplify how the proposed complexity-certification framework developed in the first part can be used to tailor active-set solvers for a given linear MPC application. Specifically, we do this by constructing and certifying parameter-varying initializations of the solver.
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| 9. |
- Assenza, Giacomo, et al.
(författare)
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White Paper on Industry Experiences in Critical Information Infrastructure Security : A Special Session at CRITIS 2019
- 2020
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Ingår i: Critical Information Infrastructures Security14th International Conference, CRITIS 2019. - Cham : Springer. - 9783030376697 - 9783030376703 ; , s. 197-207
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Bokkapitel (refereegranskat)abstract
- The security of critical infrastructures is of paramount importance nowadays due to the growing complexity of components and applications. This paper collects the contributions to the industry dissemination session within the 14th International Conference on Critical Information Infrastructures Security (CRITIS 2019). As such, it provides an overview of recent practical experience reports in the field of critical infrastructure protection (CIP), involving major industry players. The set of cases reported in this paper includes the usage of serious gaming for training infrastructure operators, integrated safety and security management in the chemical/process industry, risks related to the cyber-economy for energy suppliers, smart troubleshooting in the Internet of Things (IoT), as well as intrusion detection in power distribution Supervisory Control And Data Acquisition (SCADA). The session has been organized to stimulate an open scientific discussion about industry challenges, open issues and future opportunities in CIP research.
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| 10. |
- Axehill, Daniel, 1978-
(författare)
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Integer Quadratic Programming for Control and Communication
- 2008
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The main topic of this thesis is integer quadratic programming with applications to problems arising in the areas of automatic control and communication. One of the most widespread modern control methods is Model Predictive Control (MPC). In each sampling time, MPC requires the solution of a Quadratic Programming (QP) problem. To be able to use MPC for large systems, and at high sampling rates, optimization routines tailored for MPC are used. In recent years, the range of application of MPC has been extended to so-called hybrid systems. Hybrid systems are systems where continuous dynamics interact with logic. When this extension is made, binary variables are introduced in the problem. As a consequence, the QP problem has to be replaced by a far more challenging Mixed Integer Quadratic Programming (MIQP) problem, which is known to have a computational complexity which grows exponentially in the number of binary optimization variables. In modern communication systems, multiple users share a so-called multi-access channel. To estimate the information originally sent, a maximum likelihood problem involving binary variables can be solved. The process of simultaneously estimating the information sent by multiple users is called Multiuser Detection (MUD). In this thesis, the problem to efficiently solve MIQP problems originating from MPC and MUD is addressed. Four different algorithms are presented. First, a polynomial complexity preprocessing algorithm for binary quadratic programming problems is presented. By using the algorithm, some, or all, binary variables can be computed efficiently already in the preprocessing phase. In numerical experiments, the algorithm is applied to unconstrained MPC problems with a mixture of real valued and binary valued control signals, and the result shows that the performance gain can be significant compared to solving the problem using branch and bound. The preprocessing algorithm has also been applied to the MUD problem, where simulations have shown that the bit error rate can be significantly reduced compared to using common suboptimal algorithms. Second, an MIQP algorithm tailored for MPC is presented. The algorithm uses a branch and bound method where the relaxed node problems are solved by a dual active set QP algorithm. In this QP algorithm, the KKT systems are solved using Riccati recursions in order to decrease the computational complexity. Simulation results show that both the proposed QP solver and MIQP solver have lower computational complexity compared to corresponding generic solvers. Third, the dual active set QP algorithm is enhanced using ideas from gradient projection methods. The performance of this enhanced algorithm is shown to be comparable with the existing commercial state-of-the-art QP solver \cplex for some random linear MPC problems. Fourth, an algorithm for efficient computation of the search directions in an SDP solver for a proposed alternative SDP relaxation applicable to MPC problems with binary control signals is presented. The SDP relaxation considered has the potential to give a tighter lower bound on the optimal objective function value compared to the QP relaxation that is traditionally used in branch and bound for these problems, and its computational performance is better than the ordinary SDP relaxation for the problem. Furthermore, the tightness of the different relaxations is investigated both theoretically and in numerical experiments.
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