| 1. |
- Altafini, Claudio, 1969-
(författare)
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Representing externally positive systems through minimal eventually positive realizations
- 2015
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Ingår i: Proceedings of the IEEE 54th Annual Conference on Decision and Control (CDC). - : Institute of Electrical and Electronics Engineers (IEEE). - 9781479978861 ; , s. 6385-6390
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Konferensbidrag (refereegranskat)abstract
- In order to investigate the cases in which an externally positive discrete-time system fails to have a minimal positive realization, in this paper we introduce the notion of minimal eventually positive realization, fr which the state update matrix becomes positive after a certain power. This property captures the idea that in the impulse response of an externally positive system the state of a minimal realization may fail to be positive, but only transiently. It is shown in the paper that whenever a minimal eventually positive realization exists, then the sequence of Markov parameters of the impulse response admits decimated subsequences for which minimal positive realizations exist and can be obtained by downsampling the eventually positive realization.
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| 2. |
- Andersson, Alina, et al.
(författare)
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Sufficient Conditions for Dynamic Stabilization of 3-State Moore-Greitzer Compressor Model
- 2015
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Ingår i: 2015 IEEE 54th Annual Conference on Decision and Control (CDC). - 9781479978861 - 9781479978847 ; , s. 4394-4399
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Konferensbidrag (refereegranskat)abstract
- We consider the classical 3-state Moore-Greitzer model, which is commonly used for approximating dynamics of deviations of flow and pressure variables in an axial compressor from their nominal steady-state values. The linearization of the nonlinear system is not controllable and, therefore, even local asymptotic stability cannot be achieved using methods of linear control theory. We propose a family of parametrized partialstate feedback control laws and derive sufficient conditions to guarantee global asymptotic stability of the closed-loop system. The stability analysis uses the integral quadratic constraints technique for the case of non-strict frequency condition and novel arguments for characterization of omega-limit sets.
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| 3. |
- Ba, Qin, et al.
(författare)
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Distributed optimal equilibrium selection for traffic flow over networks
- 2016
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Ingår i: Proceedings of the IEEE Conference on Decision and Control. - 9781479978861 ; 2016, s. 6942-6947
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Konferensbidrag (refereegranskat)abstract
- In this paper, we present two distributed algorithms to compute an equilibrium, that is optimal with respect to strictly convex and separable cost functions, for controlled traffic flow dynamics over networks under constant exogenous inflows. The dynamics is modeled in continuous time by the Cell Transmission Model and a non-FIFO Dynamic Network Loading Model, with traffic control. The two algorithms are adaptations of the alternating direct method of multipliers (ADMM) and the accelerated dual descent (ADD) method from network flow optimization literature. When the demand and supply inequality constraints in the uncontrolled dynamics are relaxed to be independent over links, the resulting feasible set is convex if the demand and supply functions are concave, thereby imparting convexity to the optimal equilibrium selection problem. Each point in the feasible set is an equilibrium for the original dynamics under appropriately designed control. For the ADMM method, explicit expressions for the primal update show that no auxiliary variables are necessary. Convergence analysis for the primal variables is also provided. The standard ADD method is extended to also incorporate non-negativity constraints on the density and flow variables, and demand and supply inequality constraints. Illustrative simulation results are also presented.
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| 4. |
- Boskos, Dmitris, et al.
(författare)
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Decentralized abstractions for feedback interconnected multi-agent systems
- 2016
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Ingår i: Proceedings of the IEEE Conference on Decision and Control. - : IEEE conference proceedings. - 9781479978861 ; , s. 282-287
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Konferensbidrag (refereegranskat)abstract
- The purpose of this paper is to define abstractions for multi-agent systems under coupled constraints. In the proposed decentralized framework, we specify a finite or countable transition system for each agent which only takes into account the discrete positions of its neighbors. The dynamics of the considered systems consist of two components. An appropriate feedback law which guarantees that certain performance requirements (e.g., connectivity) are preserved and induces the coupled constraints, and additional free inputs which are exploited for the accomplishment of high level tasks. In this work we provide sufficient conditions on the space and time discretization for the abstraction of the system's behaviour which ensure that we can extract a well posed and hence meaningful transition system.
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| 5. |
- Boskos, Dmitris, et al.
(författare)
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Robust connectivity analysis for multi-agent systems
- 2016
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Ingår i: Proceedings of the IEEE Conference on Decision and Control. - : IEEE conference proceedings. - 9781479978861 ; , s. 6767-6772
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Konferensbidrag (refereegranskat)abstract
- In this paper we provide a decentralized robust control approach, which guarantees that connectivity of a multi-agent network is maintained when certain bounded input terms are added to the control strategy. Our main motivation for this framework is to determine abstractions for multi-agent systems under coupled constraints which are further exploited for the synthesis of high level plans.
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| 6. |
- Carli, Ruggero, et al.
(författare)
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Analysis of Newton-Raphson consensus for multi-agent convex optimization under asynchronous and lossy communications
- 2015
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Ingår i: IEEE 54th Annual Conference on Decision and Control (CDC). - Piscataway, NJ : IEEE Communications Society. - 9781479978861 ; , s. 418-424
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Konferensbidrag (refereegranskat)abstract
- We extend a multi-agent convex-optimization algorithm named Newton-Raphson consensus to a network scenario that involves directed, asynchronous and lossy communications. We theoretically analyze the stability and performance of the algorithm and, in particular, provide sufficient conditions that guarantee local exponential convergence of the node-states to the global centralized minimizer even in presence of packet losses. Finally, we complement the theoretical analysis with numerical simulations that compare the performance of the Newton-Raphson consensus against asynchronous implementations of distributed subgradient methods on real datasets extracted from open-source databases
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| 7. |
- Carvalho, Joao Frederico, et al.
(författare)
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Static output feedback : On essential feasible information patterns
- 2016
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Ingår i: Proceedings of the IEEE Conference on Decision and Control. - : IEEE conference proceedings. - 9781479978861 ; , s. 3989-3994
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Konferensbidrag (refereegranskat)abstract
- In this paper, for linear time-invariant plants, where a collection of possible inputs and outputs are known a priori, we address the problem of determining the communication between outputs and inputs, i.e., information patterns, such that desired control objectives of the closed-loop system (for instance, stabilizability) through static output feedback may be ensured.
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| 8. |
- Chen, Tianshi, et al.
(författare)
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Spectral analysis of the DC kernel for regularized system identification
- 2015
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Ingår i: 2015 54TH IEEE CONFERENCE ON DECISION AND CONTROL (CDC). - : IEEE. - 9781479978861 ; , s. 4017-4022
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Konferensbidrag (refereegranskat)abstract
- System identification with regularization methods has attracted increasing attention recently and is a complement to the current standard maximum likelihood/ prediction error method. In this paper, we focus on the kernel-based regularization method and give a spectral analysis of the so-called diagonal correlated (DC) kernel, one family of kernel structures that has been proven useful for linear time-invariant system identification. In particular, using the theory of Bessel functions, we derive the eigenvalues and corresponding eigenfunctions of the DC kernel. Accordingly, we derive the Karhunen-Loeve expansion of the stochastic process whose covariance function is the DC kernel.
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| 9. |
- Churilov, Alexander N., et al.
(författare)
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Delay-induced Dynamical Phenomena in Impulsive Goodwin's Oscillator : What We Know So Far
- 2015
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Ingår i: 2015 54Th Ieee Conference On Decision And Control (CDC). - 9781479978861 ; , s. 590-595
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Konferensbidrag (refereegranskat)abstract
- Impulsive Goodwin's oscillator model is introduced to capture the dynamics of sustained periodic processes in endocrine systems controlled by episodic pulses of hormones. The model is hybrid and comprises a continuous subsystem describing the hormone concentrations operating under a discrete pulse-modulated feedback implemented by firing neurons. Time delays appear in mathematical models of endocrine systems due to the significant transport phenomena but also because of the time necessary to produce releasable hormone quantities. From a biological point of view, the neural control should be robust against the time delay to ensure the loop functionality over a wide range of inter-individual variability. The paper provides an overview of the currently available results and contributes a generalization of a Poincare mapping approach to study complex dynamics of impulsive Goodwin oscillator. Both pointwise and distributed time delays are considered in a general framework based on the Poincare mapping. Bifurcation analysis is utilized to illustrate the analytical results.
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| 10. |
- Cubo, Rubén, et al.
(författare)
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Electric field modeling and spatial control in Deep Brain Stimulation
- 2015
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Ingår i: Proc. 54th Conference on Decision and Control. - Piscataway, NJ : IEEE. - 9781479978847 - 9781479978861 ; , s. 3846-3851
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Konferensbidrag (refereegranskat)abstract
- Deep Brain Stimulation (DBS) is an established treatment, in e.g. Parkinson's Disease, whose underlying biological mechanisms are unknown. In DBS, electrical stimulation is delivered through electrodes surgically implanted into certain regions of the brain of the patient. Mathematical models aiming at a better understanding of DBS and optimization of its therapeutical effect through the simulation of the electrical field propagating in the brain tissue have been developed in the past decade. The contribution of the present study is twofold: First, an analytical approximation of the electric field produced by an emitting contact is suggested and compared to the numerical solution given by a Finite Element Method (FEM) solver. Second, the optimal stimulation settings are evaluated by fitting the field distribution to a target one to control the spread of the stimulation. Optimization results are compared to those of a geometric approach, maximizing the intersection between the target and the activated volume in the brain tissue and reducing the stimulated area beyond said target. Both methods exhibit similar performance with respect to the optimal stimuli, with the electric field control approach being faster and more versatile.
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