| 1. |
- Besselink, Bart, et al.
(författare)
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Generalized incremental balanced truncation for nonlinear systems
- 2013
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Ingår i: 2013 IEEE 52nd Annual Conference on Decision and Control (CDC). - : IEEE conference proceedings. - 9781467357173 ; , s. 5552-5557
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Konferensbidrag (refereegranskat)abstract
- The method of generalized incremental balanced truncation is introduced in this paper, providing a technique for model reduction of nonlinear systems in which the autonomous part of the vector field is anti-symmetric. This approach differs from existing balancing-like reduction techniques in the definition of two novel, incremental energy functions, which provides several advantages. First, stability properties of the reduced-order model can be guaranteed, hereby considering the stability of trajectories for both zero and nonzero input. Second, a computable bound on the reduction error is derived. The reduction technique is illustrated by means of application to an example of a nonlinear electronic circuit.
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| 2. |
- Delvenne, J. -C, et al.
(författare)
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Towards a thermodynamics of control : Entropy, energy and Kalman filtering
- 2013
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Ingår i: 2013 IEEE 52nd Annual Conference on Decision and Control (CDC). - : IEEE conference proceedings. - 9781467357173 ; , s. 3109-3114
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Konferensbidrag (refereegranskat)abstract
- We propose a method to analyse the flows of information and energy between two systems (plant and controller) connected in feedback. Extending a work by Touchette and Lloyd (2000, 2004), we estimate the advantage, both in terms of entropy reduction and energy extraction, of a feedback controller over an open-loop control in terms of the information on the plant state that is available to the controller. By energy here we mean any objective function that we seek to minimize, for example the square of the state. We apply this methodology on the Kalman filter, and develop a physical interpretation comparable to Mitter and Newton's (2005).
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| 3. |
- Dimitrakakis, Christos, 1975
(författare)
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Monte-Carlo utility estimates for Bayesian reinforcement learning
- 2013
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Ingår i: Proceedings of the IEEE Conference on Decision and Control. - 2576-2370 .- 0743-1546. - 9781467357173 ; , s. 7303-7308
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Konferensbidrag (refereegranskat)abstract
- This paper introduces a set of algorithms for Monte-Carlo Bayesian reinforcement learning. Firstly, Monte-Carlo estimation of upper bounds on the Bayes-optimal value function is employed to construct an optimistic policy. Secondly, gradient-based algorithms for approximate upper and lower bounds are introduced. Finally, we introduce a new class of gradient algorithms for Bayesian Bellman error minimisation. We theoretically show that the gradient methods are sound. Experimentally, we demonstrate the superiority of the upper bound method in terms of reward obtained. However, we also show that the Bayesian Bellman error method is a close second, despite its significant computational simplicity.
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| 4. |
- Eqtami, A., et al.
(författare)
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Self-triggered model predictive control framework for the cooperation of distributed nonholonomic agents
- 2013
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Ingår i: 2013 IEEE 52nd Annual Conference on Decision and Control (CDC). - : IEEE conference proceedings. - 9781467357173 ; , s. 7384-7389
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Konferensbidrag (refereegranskat)abstract
- In this paper we propose a decentralized Model Predictive Control (MPC) framework with a self-triggering mechanism, for a team of cooperating agents. The nonholonomic agents are controlled locally and exchange information with their neighbors. The aim at scheduling the control updates based on a self-triggering criterion is twofold: To reduce the updates of the control law for each agent and to reduce the communication effort between the agents. The input-to-state (abbr. ISS) stability of the agents is proven, the condition for triggering is provided and the theoretic results are then depicted by a simulated example.
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| 5. |
- Everitt, Niklas, 1987-, et al.
(författare)
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A Geometric Approach to Variance Analysis of Cascaded Systems
- 2013
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Ingår i: Proceedings of the 52nd Conference On Decision And Control. - : IEEE conference proceedings. - 9781467357173 ; , s. 6496-6501
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Konferensbidrag (refereegranskat)abstract
- Modeling complex and interconnected systems is a key issue in system identification. When estimating individual subsystems of a network of interconnected system, it is of interest to know the improvement of model-accuracy in using different sensors and actuators. In this paper, using a geometric approach, we quantify the accuracy improvement from additional sensors when estimating the first of a set of subsystems connected in a cascade structure. We present results on how the zeros of the first subsystem affect the accuracy of the corresponding model. Additionally we shed some light on how structural properties and experimental conditions determine the accuracy. The results are particularized to FIR systems, for which the results are illustrated by numerical simulations. A surprising special case occurs when the first subsystem contains a zero on the unit circle; as the model orders grows large, thevariance of the frequency function estimate, evaluated at thecorresponding frequency of the unit-circle zero, is shown to be the same as if the other subsystems were completely known.
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| 6. |
- Gros, Sébastien, 1977
(författare)
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An Economic NMPC Formulation for Wind Turbine Control
- 2013
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Ingår i: 52nd IEEE Conference on Decision and Control, CDC 2013, Florence, Italy, 10-13 December 2013. - 0191-2216. - 9781467357173
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Konferensbidrag (refereegranskat)abstract
- Model Predictive Control (MPC) is a strong candidate for the control of large Multi-MegaWatt Wind Turbine Generators. Several MPC and some Nonlinear MPC scheme have been proposed in the literature, based on reference-tracking objective functions. While the resulting schemes offer very promising results, the difficulty of tuning a reference-tracking NMPC scheme for performance is likely to be a hindrance to the industrial success of NMPC-based WTG control. Because they directly maximize the system performance, economic NMPC schemes are more straightforward to tune. Economic NMPC schemes present, however, some known difficulties that are a serious obstacle to their real-time deployment. This paper presents an economic NMPC formulation for maximizing the generated power of wind turbine generators, which does not suffer from such difficulties. The relationship between the proposed and more classical reference-tracking approaches is formally established.
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| 7. |
- Ishizaki, T., et al.
(författare)
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Dissipativity-preserving model reduction based on generalized singular perturbation
- 2013
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Ingår i: 2013 IEEE 52nd Annual Conference on Decision and Control (CDC). - : IEEE conference proceedings. - 9781467357173 ; , s. 5540-5545
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Konferensbidrag (refereegranskat)abstract
- In this paper, we develop a dissipativity-preserving model reduction method based on a generalized singular perturbation approximation. This model reduction framework can deal with not only standard singular perturbation approximation but also projection-based model reduction as a special case. To develop such a model reduction method, we investigate a condition under which system dissipativity is appropriately preserved through the approximation. Moreover, deriving a novel factorization of the error system in the Laplace domain, we derive an a priori error bound in terms of the H2-norm. The efficiency of the model reduction is shown through an example of interconnected second-order systems.
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| 8. |
- James, Weimer, et al.
(författare)
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Parameter-invariant detection of unknown inputs in networked systems
- 2013
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Ingår i: 2013 IEEE 52nd Annual Conference on Decision and Control (CDC). - : IEEE conference proceedings. - 9781467357173 ; , s. 4379-4384
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Konferensbidrag (refereegranskat)abstract
- This work considers the problem of detecting unknown inputs in networked systems whose dynamics are governed by time-varying unknown parameters. We propose a strategy in opposition to the commonly employed approach of first estimating the unknown parameters and then using the estimates as the true parameter values for detection, e.g. maximum-likelihood approaches. The suggested detection scheme employs test statistics that are invariant to the unknown parameters and do not rely on parameter estimation. We specifically consider the case of severe lack of prior knowledge, i.e., the problem of detecting unknown inputs when nothing is known of the system but some primitive structural properties, namely that the system is a linear network, subject to Gaussian noise, and that a certain input signal is either present or not. The aim is thus to analyze the structure and performances of invariant tests in a limiting case, specifically where the amount of prior information is minimal. The developed test is proven to be maximally invariant to the unknown parameters and Uniformly Most Powerful Invariant (UMPI). Simulation results indicate that for arbitrary networked systems the parameterinvariant detector achieves a specified probability of false alarm while ensuring that the probability of detection is maximized.
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| 9. |
- Leva, Alberto, et al.
(författare)
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A general control-theoretical methodology for runtime resource allocation in computing systems
- 2013
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Ingår i: 2013 IEEE 52nd Annual Conference on Decision and Control, CDC 2013. - 0191-2216. - 9781467357173 ; , s. 3487-3492
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Konferensbidrag (refereegranskat)abstract
- Control theory is emerging as a source of solutions for many problems in the computing systems domain, and in particular for resource allocation. However, the techniques proposed to date in the literature, do not successfully address the difficulty of devising allocation schemes that are general enough, provide stability guarantees, and can be parametrised and managed by system administrators, or computing systems' practitioners at large. This paper proposes a two-level timevarying control scheme for the allocation of a generic resource, and proves its stability. In addition, the paper discusses how the scheme can be made acceptable by computing systems administrators, and how to tune the involved parameters. A simulation campaign is reported, validating the aforementioned claims.
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| 10. |
- Lindquist, Anders, et al.
(författare)
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On the multivariate circulant rational covariance extension problem
- 2013
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Ingår i: 2013 IEEE 52nd Annual Conference on Decision and Control (CDC). - : IEEE conference proceedings. - 9781467357173 ; , s. 7155-7161
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Konferensbidrag (refereegranskat)abstract
- Partial stochastic realization of periodic processes from finite covariance data leads to the circulant rational covariance extension problem and bilateral ARMA models. In this paper we present a convex optimization-based theory for this problem that extends and modifies previous results by Carli, Ferrante, Pavon and Picci on the AR solution, which have been successfully applied to image processing of textures. We expect that our present results will provide an enhancement of these procedures.
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