| 1. |
- Svensson, Andreas, et al.
(author)
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Identification of jump Markov linear models using particle filters
- 2014
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In: Proceedings of the 53rd IEEE Conference on Decision and Control. - Piscataway, NJ : IEEE. - 9781467360906 - 9781479977468 - 9781479977451 ; , s. 6504-6509
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Conference paper (peer-reviewed)abstract
- Jump Markov linear models consists of a finite number of linear state space models and a discrete variable encoding the jumps (or switches) between the different linear models. Identifying jump Markov linear models makes for a challenging problem lacking an analytical solution. We derive a new expectation maximization (EM) type algorithm that produce maximum likelihood estimates of the model parameters. Our development hinges upon recent progress in combining particle filters with Markov chain Monte Carlo methods in solving the nonlinear state smoothing problem inherent in the EM formulation. Key to our development is that we exploit a conditionally linear Gaussian substructure in the model, allowing for an efficient algorithm.
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| 2. |
- Dürango, Jonas, et al.
(author)
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Control-theoretical load-balancing for cloud applications with brownout
- 2014
-
In: 2014 IEEE 53RD ANNUAL CONFERENCE ON DECISION AND CONTROL (CDC). - 9781467360906 - 9781479977468 ; , s. 5320-5327
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Conference paper (peer-reviewed)abstract
- Cloud applications are often subject to unexpected events like flash crowds and hardware failures. Without a predictable behaviour, users may abandon an unresponsive application. This problem has been partially solved on two separate fronts: first, by adding a self-adaptive feature called brownout inside cloud applications to bound response times by modulating user experience, and, second, by introducing replicas - copies of the applications having the same functionalities - for redundancy and adding a load-balancer to direct incoming traffic. However, existing load-balancing strategies interfere with brownout self-adaptivity. Load-balancers are often based on response times, that are already controlled by the self-adaptive features of the application, hence they are not a good indicator of how well a replica is performing. In this paper, we present novel load-balancing strategies, specifically designed to support brownout applications. They base their decision not on response time, but on user experience degradation. We implemented our strategies in a self-adaptive application simulator, together with some state-of-the-art solutions. Results obtained in multiple scenarios show that the proposed strategies bring significant improvements when compared to the state-of-the-art ones.
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| 3. |
- Adaldo, Antonio, 1989-, et al.
(author)
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Event-triggered pinning control of complex networks with switching topologies
- 2014
-
In: Proceedings of the 53rd annual IEEE Conference on Decision and Control. - 9781479977468 ; , s. 2783-2788
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Conference paper (peer-reviewed)abstract
- This paper investigates the problem of eventtriggered pinning control for the synchronization of networks of nonlinear dynamical agents onto a desired reference trajectory. The pinned agents are those that have access to the reference trajectory. We consider both static and switching topologies. We prove that the system is well posed and identify conditions under which the network achieves exponential convergence. A lower bound for the rate of convergence is also derived. Numerical examples demonstrating the effectiveness of the results are provided.
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| 4. |
- Andreasson, Martin, 1987-, et al.
(author)
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Control of MTDC Transmission Systems under Local Information
- 2014
-
In: Decision and Control (CDC), 2014 IEEE 53rd Annual Conference on. - : IEEE conference proceedings. - 9781479977468 ; , s. 1335-1340
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Conference paper (peer-reviewed)abstract
- High-voltage direct current (HVDC) is a commonly used technology for long-distance electric power transmission, mainly due to its low resistive losses. In this paper a distributed controller for multi-terminal high-voltage direct current (MTDC) transmission systems is considered. Sufficient conditions for when the proposed controller renders the closed-loop system asymptotically stable are provided. Provided that the closed loop system is asymptotically stable, it is shown that in steady-state a weighted average of the deviations from the nominal voltages is zero. Furthermore, a quadratic cost of the current injections is minimized asymptotically.
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| 5. |
- Araújo, José, et al.
(author)
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A down-sampled controller to reduce network usage with guaranteed closed-loop performance
- 2014
-
In: Decision and Control (CDC), 2014 IEEE 53rd Annual Conference on. - : IEEE conference proceedings. - 9781479977468 ; , s. 6849-6856
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Conference paper (peer-reviewed)abstract
- We propose and evaluate a down-sampled controller which reduces the network usage while providing a guaranteed desired linear quadratic control performance. This method is based on fast and slow sampling intervals, as the closed-system benefits by being brought quickly to steady-state conditions while behaving satisfactorily when being actuated at a slow rate once at those conditions. This mechanism is shown to provide large savings with respect to network usage when compared to traditional periodic time-triggered control and other aperiodic controllers proposed in the literature.
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| 6. |
- Ebadat, Afrooz, et al.
(author)
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Applications Oriented Input Design for Closed-Loop System Identification : a Graph-Theory Approach
- 2014
-
In: 2014 IEEE 53RD ANNUAL CONFERENCE ON DECISION AND CONTROL (CDC). - : IEEE. - 9781467360906 ; , s. 4125-4130
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Conference paper (peer-reviewed)abstract
- A new approach to experimental design for identification of closed-loop models is presented. The method considers the design of an experiment by minimizing experimental cost, subject to probabilistic bounds on the input and output signals, and quality constraints on the identified model. The input and output bounds are common in many industrial processes due to physical limitations of actuators. The aforementioned constraints make the problem non-convex. By assuming that the experiment is a realization of a stationary process with finite memory and finite alphabet, we use results from graph-theory to relax the problem. The key feature of this approach is that the problem becomes convex even for non-linear feedback systems. A numerical example shows that the proposed technique is an attractive alternative for closed-loop system identification.
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| 7. |
- Feyzmahdavian, Hamid Reza, et al.
(author)
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On the Convergence Rates of Asynchronous Iterations
- 2014
-
In: Decision and Control (CDC), 2014 IEEE 53rd Annual Conference on. - : IEEE conference proceedings. - 9781479977468 ; , s. 153-159
-
Conference paper (peer-reviewed)abstract
- This paper presents a unifying convergence result for asynchronous iterations involving pseudo-contractions in the block-maximum norm. Contrary to previous results which only established asymptotic convergence or studied simplified models of asynchronism, our result allows to bound the convergence rates for both partially and totally asynchronous implementations. Several examples are worked out to demonstrate that our theorem recovers and improves on existing results, and that it allows to characterize the solution times for several classes of asynchronous iterations that have not been addressed before.
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| 8. |
- Fresk, Emil, et al.
(author)
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Frame Induced Vibration Estimation and Attenuation Scheme on a Multirotor helicopter
- 2015
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In: Decision and Control (CDC). - Piscataway, NJ : IEEE Communications Society. - 9781479977468 ; , s. 5698-5703
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Conference paper (peer-reviewed)abstract
- The aim of this article is to establish an induced frame vibration and attenuation scheme, specifically targeting the area of multi-rotor Unmanned Aerial Vehicles (UAVs), such as quadrotors. These types of unmanned small scale helicopters are characterised by small and light frames, which are vulnerable to vibrations induced by the operation of the motors or external environmental factors. The existence of such vibrations effecting the frame can significantly deteriorate the performance of the overall closed system and even drive it to instabilities. In this article spectral estimation schemes based on: a) Autoregressive (AR) modelling and b) Multiple Signal Classification (MUSIC) are being established and evaluated towards their ability to detect the induced vibration frequencies on the UAV, while an extended discussion is being presented on selecting the correct number of the identified induced vibrating frequencies. In a sequential stage, a vibration attenuation approach based on notch filtering is being presented, being able to correctly attenuate the induced vibrating frequencies in the measurements. The efficiency of the overall suggested scheme is being evaluated by experimental results that indicate the significant improvement in the measurements achieved bythe direct application of the proposed scheme.
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| 9. |
- Hansson, Anders, et al.
(author)
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Distributed system identification with ADMM
- 2014
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In: Proceedings of the 53rd IEEE Conference on Decision and Control. - Los Angeles. - 9781479977451 - 9781467360883 ; , s. 290-295
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Conference paper (peer-reviewed)abstract
- 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.
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| 10. |
- Karlsson, Johan, et al.
(author)
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On Robustness of l(1)-Regularization Methods for Spectral Estimation
- 2014
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In: 2014 IEEE 53RD ANNUAL CONFERENCE ON DECISION AND CONTROL (CDC). - : IEEE. - 9781467360906 ; , s. 1767-1773, s. 1767-1773
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Conference paper (peer-reviewed)abstract
- The use of l(1)-regularization in sparse estimation methods has received huge attention during the last decade, and applications in virtually all fields of applied mathematics have benefited greatly. This interest was sparked by the recovery results of Cands, Donoho, Tao, Tropp, et al. and has resulted in a framework for solving a set of combinatorial problems in polynomial time by using convex relaxation techniques. In this work we study the use of l(1)-regularization methods for high-resolution spectral estimation. In this problem, the dictionary is typically coherent and existing theory for robust/exact recovery does not apply. In fact, the robustness cannot be guaranteed in the usual strong sense. Instead, we consider metrics inspired by the Monge-Kantorovich transportation problem and show that the magnitude can be robustly recovered if the original signal is sufficiently sparse and separated. We derive both worst case error bounds as well as error bounds based on assumptions on the noise distribution.
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