Many control related problems can be cast as semidefinite programs but, even though there exist polynomial time algorithms and good publicly available solvers, the time it takes to solve these problems can be long. Something many of these problems have in common, is that some of the variables enter as matrix valued variables. This leads to a low-rank structure in the basis matrices which can be exploited when forming the Newton equations. In this paper, we describe the how this can be done, and show how our code can be used when using SDPT3. The idea behind this is old and is implemented in LMI Lab, but we show that when using a modern algorithm, the computational time can be reduced. Finally, we describe how the modeling language YALMIP is changed in such a way that our code can be interfaced using standard YALMIP commands, which greatly simplifies for the user. Keywords: Semidefinite programming, Structure exploitationLowrank exploitation in semidefinite programming for control Rikard Falkeborn, Johan Löfberg and Anders HanssonAbstract-Many control related problems can be cast as semidefinite programs but, even though there exist polynomial time algorithms and good publicly available solvers, the time it takes to solve these problems can be long. Something many of these problems have in common, is that some of the variables enter as matrix valued variables. This leads to a low-rank structure in the basis matrices which can be exploited when forming the Newton equations. In this paper, we describe the how this can be done, and show how our code can be used when using SDPT3. The idea behind this is old and is implemented in LMI Lab, but we show that when using a modern algorithm, the computational time can be reduced. Finally, we describe how the modeling language YALMIP is changed in such a way that our code can be interfaced using standard YALMIP commands, which greatly simplifies for the user.

Many control related problems can be cast as semidefinite programs but, even though there exist polynomial time algorithms and good publicly available solvers, the time it takes to solve these problems can be long. Something many of these problems have in common, is that some of the variables enter as matrix valued variables. This leads to a low-rank structure in the basis matrices which can be exploited when forming the Newton equations. In this paper, we describe the how this can be done, and show how our code can be used when using SDPT3. The idea behind this is old and is implemented in LMI Lab, but we show that when using a modern algorithm, the computational time can be reduced. Finally, we describe how the modeling language YALMIP is changed in such a way that our code can be interfaced using standard YALMIP commands, which greatly simplifies for the user. Keywords: Semidefinite programming, Structure exploitationLowrank exploitation in semidefinite programming for control Rikard Falkeborn, Johan Löfberg and Anders HanssonAbstract-Many control related problems can be cast as semidefinite programs but, even though there exist polynomial time algorithms and good publicly available solvers, the time it takes to solve these problems can be long. Something many of these problems have in common, is that some of the variables enter as matrix valued variables. This leads to a low-rank structure in the basis matrices which can be exploited when forming the Newton equations. In this paper, we describe the how this can be done, and show how our code can be used when using SDPT3. The idea behind this is old and is implemented in LMI Lab, but we show that when using a modern algorithm, the computational time can be reduced. Finally, we describe how the modeling language YALMIP is changed in such a way that our code can be interfaced using standard YALMIP commands, which greatly simplifies for the user.

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In this paper, a structure exploiting algorithm for semidefinite programs derived from the Kalman-Yakubovich-Popov lemma, where some of the constraints appear as complicating constraints is presented. A decomposition algorithm is proposed, where the structure of the problem can be utilized. In a numerical example, where a controller that minimizes the sum of the H 2 -norm and the H ∞ -norm is designed, the algorithm is shown to be faster than SeDuMi and the special purpose solver KYPD. Keywords: Optimization, Optimization Algorithms A Decomposition Algorithm for KYP-SDPs Rikard Falkeborn and Anders HanssonAbstract-In this paper, a structure exploiting algorithm for semidefinite programs derived from the Kalman-YakubovichPopov lemma, where some of the constraints appear as complicating constraints is presented. A decomposition algorithm is proposed, where the structure of the problem can be utilized. In a numerical example, where a controller that minimizes the sum of the H2-norm and the H∞-norm is designed, the algorithm is shown to be faster than SeDuMi and the special purpose solver KYPD.

In this paper, a structure exploiting algorithm for semidefinite programs derived from the Kalman-Yakubovich-Popov lemma, where some of the constraints appear as complicating constraints is presented. A decomposition algorithm is proposed, where the structure of the problem can be utilized. In a numerical example, where a controller that minimizes the sum of the H 2 -norm and the H ∞ -norm is designed, the algorithm is shown to be faster than SeDuMi and the special purpose solver KYPD. Keywords: Optimization, Optimization Algorithms A Decomposition Algorithm for KYP-SDPs Rikard Falkeborn and Anders HanssonAbstract-In this paper, a structure exploiting algorithm for semidefinite programs derived from the Kalman-YakubovichPopov lemma, where some of the constraints appear as complicating constraints is presented. A decomposition algorithm is proposed, where the structure of the problem can be utilized. In a numerical example, where a controller that minimizes the sum of the H2-norm and the H∞-norm is designed, the algorithm is shown to be faster than SeDuMi and the special purpose solver KYPD.