| 1. |
- Khoshfetrat Pakazad, Sina, et al.
(författare)
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Distributed Semidefinite Programming with Application to Large-scale System Analysis
- 2018
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Ingår i: IEEE Transactions on Automatic Control. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 0018-9286 .- 1558-2523. ; 63:4
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Tidskriftsartikel (refereegranskat)abstract
- Distributed algorithms for solving coupled semidefinite programs (SDPs) commonly require many iterations to converge. They also put high computational demand on the computational agents. In this paper we show that in case the coupled problem has an inherent tree structure, it is possible to devise an efficient distributed algorithm for solving such problems. The proposed algorithm relies on predictor-corrector primal-dual interior-point methods, where we use a message-passing algorithm to compute the search directions distributedly. Message-passing here is closely related to dynamic programming over trees. This allows us to compute the exact search directions in a finite number of steps. This is because, computing the search directions requires a recursion over the tree structure and hence, terminates after an upward and downward pass through the tree. Furthermore this number can be computed apriori and only depends on the coupling structure of the problem. We use the proposed algorithm for analyzing robustness of large-scale uncertain systems distributedly. We test the performance of this algorithm using numerical examples.
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| 2. |
- Ahmadi, Shervin Parvini, et al.
(författare)
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Distributed localization using Levenberg-Marquardt algorithm
- 2021
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Ingår i: EURASIP Journal on Advances in Signal Processing. - : SPRINGER. - 1687-6172 .- 1687-6180. ; 2021:1
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Tidskriftsartikel (refereegranskat)abstract
- In this paper, we propose a distributed algorithm for sensor network localization based on a maximum likelihood formulation. It relies on the Levenberg-Marquardt algorithm where the computations are distributed among different computational agents using message passing, or equivalently dynamic programming. The resulting algorithm provides a good localization accuracy, and it converges to the same solution as its centralized counterpart. Moreover, it requires fewer iterations and communications between computational agents as compared to first-order methods. The performance of the algorithm is demonstrated with extensive simulations in Julia in which it is shown that our method outperforms distributed methods that are based on approximate maximum likelihood formulations.
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| 3. |
- Ahmadi, Shervin Parvini, et al.
(författare)
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Efficient Robust Model Predictive Control using Chordality
- 2019
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Ingår i: 2019 18TH EUROPEAN CONTROL CONFERENCE (ECC). - : IEEE. - 9783907144008 ; , s. 4270-4275
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Konferensbidrag (refereegranskat)abstract
- In this paper we show that chordal structure can be used to devise efficient optimization methods for robust model predictive control problems. To this end, first the problem is converted to an equivalent robust quadratic programming formulation. We then illustrate how the chordal structure can be used to distribute the computations in a primal-dual interior-point method among computational agents, which in turn allows us to accelerate the algorithm by efficient parallel computations. We investigate performance of the framework in Julia using numerical examples.
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| 4. |
- Andersen, Martin, et al.
(författare)
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Distributed Robust Stability Analysis of Interconnected Uncertain Systems
- 2012
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Ingår i: Proceedings of the 51st IEEE Conference on Decision and Control. - 0743-1546. - 9781467320641 - 9781467320658 ; , s. 1548-1553
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Konferensbidrag (refereegranskat)abstract
- This paper considers robust stability analysis of a large network of interconnected uncertain systems. To avoid analyzing the entire network as a single large, lumped system, we model the network interconnections with integral quadratic constraints. This approach yields a sparse linear matrix inequality which can be decomposed into a set of smaller, coupled linear matrix inequalities. This allows us to solve the analysis problem efficiently and in a distributed manner. We also show that the decomposed problem is equivalent to the original robustness analysis problem, and hence our method does not introduce additional conservativeness.
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| 5. |
- Andersen, Martin S., et al.
(författare)
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Robust Stability Analysis of Sparsely Interconnected Uncertain Systems
- 2014
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Ingår i: IEEE Transactions on Automatic Control. - : IEEE. - 0018-9286 .- 1558-2523. ; 59:8, s. 2151-2156
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Tidskriftsartikel (refereegranskat)abstract
- In this paper, we consider robust stability analysis of large-scale sparsely interconnected uncertain systems. By modeling the interconnections among the subsystems with integral quadratic constraints, we show that robust stability analysis of such systems can be performed by solving a set of sparse linear matrix inequalities. We also show that a sparse formulation of the analysis problem is equivalent to the classical formulation of the robustness analysis problem and hence does not introduce any additional conservativeness. The sparse formulation of the analysis problem allows us to apply methods that rely on efficient sparse factorization techniques, and our numerical results illustrate the effectiveness of this approach compared to methods that are based on the standard formulation of the analysis problem.
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| 6. |
- Annergren, Mariette, et al.
(författare)
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A Distributed Primal-dual Interior-point Method for Loosely Coupled Problems Using ADMM
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- In this paper we propose an efficient distributed algorithm for solving loosely coupled convex optimization problems. The algorithm is based on a primal-dual interior-point method in which we use the alternating direction method of multipliers (ADMM) to compute the primal-dual directions at each iteration of the method. This enables us to join the exceptional convergence properties of primal-dual interior-point methods with the remarkable parallelizability of ADMM. The resulting algorithm has superior computational properties with respect to ADMM directly applied to our problem. The amount of computations that needs to be conducted by each computing agent is far less. In particular, the updates for all variables can be expressed in closed form, irrespective of the type of optimization problem. The most expensive computational burden of the algorithm occur in the updates of the primal variables and can be precomputed in each iteration of the interior-point method. We verify and compare our method to ADMM in numerical experiments.
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| 7. |
- Falcone, Paolo, 1977, et al.
(författare)
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Predictive Approaches to Rear Axle Regenerative Braking Control in Hybrid Vehicles
- 2009
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Ingår i: 48th IEEE Conference on Decision and Control and 28th Chinese Control Conference.
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Konferensbidrag (refereegranskat)abstract
- We consider the problem of controlling the regenerative braking at rear axle in hybrid vehicles. In particular, thefocus of this work is the maximization of regenerative braking in cornering maneuvers on low friction surfaces. In such cases, excessive braking at the rear axle might induce instability.We present and compare two predictive control approaches,where the objective is maximizing the regenerative braking and distributing the friction braking at the four wheels, while (i) delivering the braking force requested by the driver, (ii) preserving vehicle stability and (iii) fulfilling system constraints (e.g., bounds on regenerative braking set by the hybrid powertrain).We present simulation results in combined braking andcornering scenarios, showing that the proposed approaches are able to distribute the requested braking at the four wheels in order to counteract undesired effects, on vehicle stability, introduced by regenerative braking.
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| 8. |
- Falcone, Paolo, 1977, et al.
(författare)
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Regenerative Braking and Yaw Dynamics Optimal Control in Hybrid Vehicles
- 2009
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Ingår i: 21st International Symposium on Dynamics of Vehicles on Roads and Tracks, 17-21 August 2009, Stockholm, Sweden.
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Konferensbidrag (refereegranskat)abstract
- In hybrid vehicles, regenerative braking is used in order to recover energy when vehiclebrakes. Energy is recovered by converting the vehicle kinetic energy into electric energy tobe stored in electricity buffers, i.e., batteries or capacitors. The recovered energy can then beused for powering the vehicle and thus reduce the fuel consumption. In particular, in order togenerate a braking force, the wheels can be connected to the electric motor, thus providingmotion energy to the generator and charging the electric buffer. When regenerative brakingis applied, the connection of the wheels to the generator results in a load torque (i.e., a braketorque), slowing the vehicle down, and at the same time enables energy recovery.In this paper, we consider hybrid drivelines where the electric motor is connected to therear axle, i.e., the regenerative braking takes place by braking the rear wheels, and focus onthe implications of the regenerative braking on the vehicle dynamics.The scenario considered in this paper (i.e., regenerative braking at the rear axle) is challengingfrom both the brake force delivery and distribution and the vehicle stabilizationperspectives [1]. In fact, we first observe that the maximum force the regenerative brakingcan deliver is limited and, in general, less than the friction braking. In particular, a brakingforce request from the driver might not be delivered entirely through regenerative brakingand a combination of friction and regenerative braking might be necessary. Secondly, werecall that an “optimum” brake proportioning between front and rear axles exists, such thatthe braking performance is maximized and the vehicle stability is preserved (see [2] for adetailed explanation). Clearly, maximizing the braking at one axle might conflict with a brakeforce distribution determined according to some “optimum” brake proportioning. Moreover,preserving the vehicle stability and comfort on slippery surfaces while maximizing the energyrecovering is a significant challenge as well. In particular, on low friction surfaces, the braketorque from regenerative braking might be large enough to lock-up the rear wheel. This wouldinduce an oversteering behavior and might even lead to instability, i.e., vehicle spinning [1].Even though instability does not occur, the driver might perceive a reduction of comfort asconsequence of braking at the rear wheels. In particular, on low friction surfaces, where thevehicle can easily operate at the limit of tire force capabilities, a sudden reduction of lateralforce might be experienced as consequence of braking.In this paper, we consider testing scenarios where the driver demands a braking force whilethe vehicle is performing a cornering manoeuvres on slippery surfaces, i.e., snow or ice. Thecontrol objective is to maximize the energy recovery (i.e., the regenerative braking), while (i)delivering the requested braking force by introducing front and rear friction braking as well,if necessary, (ii) preserving the vehicle stability and (iii) limit the lateral force reduction. Weshow how this problem can be effectively formulated as a Model Predictive Control (MPC)problem. In particular, we design a cost function in order to achieve our control objectives.Every time step, based on measurements of the demanded brake force, the vehicle yaw turningrate and longitudinal and lateral velocities, we repeatedly solve an optimization problem inorder to find the braking policy minimizing the cost function while fulfilling design and systemconstraints. As shown in [3], such control approach can be high computational demandingand even prevent real-time implementation. In order to implement our MPC algorithms inreal-time, we resort to the low complexity MPC formulation used in [4], [5], [6] to solveautonomous path following problems.REFERENCES[1] M. Hancock and F. Assadian. Impact of regenerative braking on vehicle stability. IET The Institution of Engineeringand Technology, Hybrid Vehicle Conference, 2006.[2] T. Gillespie. Fundamentals of Vehicle Dynamics, chapter 3, pages 60–67. Society of Automotive Engineers (SAE),1992.[3] F. Borrelli, P. Falcone, T. Keviczky, J. Asgari, and D. Hrovat. MPC-based approach to active steering for autonomousvehicle systems. Int. J. Vehicle Autonomous Systems, 3(2/3/4):265–291, 2005.[4] P. Falcone, F. Borrelli, J. Asgari, H. E. Tseng, and D. Hrovat. Predictive active steering control for autonomous vehiclesystems. IEEE Trans. on Control System Technology, 15(3), 2007.[5] P. Falcone, F. Borrelli, J. Asgari, H. E. Tseng, and D. Hrovat. Linear time varying model predictive control and itsapplication to active steering systems: Stability analisys and experimental validation. International Journal of Robustand Nonlinear Control., 18:862–875, 2008.[6] P. Falcone. Nonlinear Model Predictive Control for Autonomous Vehicles. PhD thesis, Universit`a del Sannio,Dipartimento di Ingegneria, Piazza Roma 21, 82100, Benevento, Italy, June 2007.
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| 9. |
- Garulli, Andrea, et al.
(författare)
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Robust Finite-Frequency H2 Analysis of Uncertain Systems
- 2011
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- In many applications, design or analysis is performed over a finite frequency range of interest. The importance of the H2/robust H2 norm highlights the necessity of computing this norm accordingly. This paper provides different methods for computing upper bounds on the robust finite-frequency H2 norm for systems with structured uncertainties. An application of the robust finite-frequency H2 norm for a comfort analysis problem of an aero-elastic model of an aircraft is also presented.
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| 10. |
- Garulli, Andrea, et al.
(författare)
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Robust finite-frequency H2 analysis of uncertain systems with application to flight comfort analysis
- 2013
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Ingår i: Control Engineering Practice. - : Elsevier. - 0967-0661 .- 1873-6939. ; 21:6, s. 887-897
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Tidskriftsartikel (refereegranskat)abstract
- In many applications, design or analysis is performed over a finite-frequency range of interest. The importance of the H2 norm highlights the necessity of computing this norm accordingly. This paper provides different methods for computing upper bounds of the robust finite-frequency H2 norm for systems with structured uncertainties. An application of the robust finite-frequency H2 norm for a comfort analysis problem of an aero-elastic model of an aircraft is also presented.
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