| 1. |
- Tettamanti, T., et al.
(författare)
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Robust real-time control for urban road traffic networks
- 2014
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Ingår i: IEEE Transactions on Intelligent Transportation Systems. - 1524-9050 .- 1558-0016. ; 15:1, s. 385-398
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Tidskriftsartikel (refereegranskat)abstract
- The aim of the presented research is to elaborate a traffic-responsive optimal signal split algorithm taking uncertainty into account. The traffic control objective is to minimize the weighted link queue lengths within an urban network area. The control problem is formulated in a centralized rolling-horizon fashion in which unknown but bounded demand and queue uncertainty influences the prediction. An efficient constrained minimax optimization is suggested to obtain the green time combination, which minimizes the objective function when worst case uncertainty appears. As an illustrative example, a simulation study is carried out to demonstrate the effectiveness and computational feasibility of the robust predictive approach. By using real-world traffic data and microscopic traffic simulator, the proposed robust signal split algorithm is analyzed and compared with well-tuned fixed-time signal timing and to nominal predictive solutions under different traffic conditions.
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| 2. |
- Tettamanti, T., et al.
(författare)
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Uncertainty modeling and robust control in urban traffic
- 2011
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Ingår i: IFAC Proceedings Volumes (IFAC-PapersOnline). - 2405-8963. - 9783902661937 ; 18:PART 1, s. 14910-14915
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Konferensbidrag (refereegranskat)abstract
- The paper investigates the problem of uncertainty modeling and constrained robust control of urban traffic. Linear polytopic approach is used by state-space representations to describe the uncertain network system. In order to handle model mismatches, robust and infinite horizon model predictive control (MPC) method is proposed. The control strategy is an efficient method to reduce travel time and improve homogeneous traffic flow under changing model conditions. Centralized numerical solution has been carried out as a solution of Linear Matrix Inequalities (LMI) by using semidefinite programming (SDP). Closed-loop control results were tested in simulation environment taking alternative model uncertainty levels into account.
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| 3. |
- Luspay, T., et al.
(författare)
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Constrained Freeway Traffic Control via Linear Parameter Varying Paradigms
- 2012
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Ingår i: J. Mohammadpour and C.W. Scherer (eds.), Control of linear parameter varying systems with applications, Springer. - Boston, MA : Springer US. - 9781461418320 ; 9781461418337, s. 461-482
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- A novel freeway traffic control design framework is proposed in the chapter. The derivation is based on the parameter-dependent reformulation of the second-order macroscopic freeway model. Hard physical constraints are handled implicitly, by introducing additional scheduling parameter for controller saturation measure. The ramp metering problem is then formulated as an induced L2 norm minimization, where the effects of undesired traffic phenomena are attenuated on the network throughput. The solution of the resulting problem involves convex optimization methods subjected to Linear Matrix Inequalities. A numerical example is given to validate the parameter-dependent controller and evaluate its effectiveness under various traffic situations.
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| 4. |
- Luspay, T., et al.
(författare)
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Freeway ramp metering: an LPV set theoretical analysis
- 2011
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Ingår i: American Control Conference. - 0743-1619. - 9781457700804 ; , s. 733-738
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Konferensbidrag (refereegranskat)abstract
- The paper contributes to the set theoretic analysis of freeway traffic flow control by ramp metering.From the generic and discrete time non-linear second-order macroscopic dynamics of freeway, first, an equivalent, quasi Linear Parameter Varying (LPV) representation is derived by steady-state centering and factorization. Second, a polytopic LPV model form is obtained from the quasi reformulation of the non-linear problem statement. The latter polytopic LPV form is then used for the computation and analysis of distur- bance invariant sets. This framework is able to characterize constrained sets of states which can be reached by pure ramp metering control input signal respectively becomes invariant under the effect of other measured and unmeasured inputs.The application of disturbance invariant set theory clearly quantifies the set of states being invariant under the polytopic LPV dynamics and other physical constraints regardless to the open- and closed-loop nature of the system.The proposed idea is fully based on the analysis of the (transformed) non-linear macroscopic system and aims at filling the gap between the traffic modelling and quantitative freeway ramp metering.
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| 5. |
- Kulcsár, Balázs Adam, 1975, et al.
(författare)
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Integrated robust control/fault diagnosis design for LPV systems under input constraints
- 2012
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Ingår i: European Workshop on Advanced Control and Diagnosis ACD’12.
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Konferensbidrag (refereegranskat)abstract
- This paper proposes a joint controller and fault estimator design for continuous-time Linear Parameter Varying systems. In the presented problem statement, the structure of the modeling uncertainty couples the controller and fault estimator synthesis. Furthermore, as in most of the cases, control input actions are subjected to hard physical constraints, this paper aims at developing an integrated methodology where these bounds can explicitly be taken into considerations.
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| 6. |
- Peni, T., et al.
(författare)
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Model recovery anti-windup control for linear discrete time systems with magnitude and rate saturation
- 2012
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Ingår i: American Control Conference. - : IEEE. - 0743-1619. - 9781457710957 ; , s. 1543-1548
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Konferensbidrag (refereegranskat)abstract
- The paper proposes a model recovery anti-windup (MRAW) scheme for linear time-invariant and discrete-time systems under magnitude and rate saturation. The method is a modified, discrete-time counterpart of the algorithm presented in [4]. As it is usual in the MRAW framework the AW compensator contains the exact copy of the plant in order that the ideal (unsaturated) behavior can be preserved in the states. The compensator is a controller that aims to push the plant towards this intended behavior. The design of this control action can be reduced to a construction of a stabilizing state feedback acting on the saturated plant. In [4] this feedback is a linear one, which is designed by convex optimization by enlarging the ellipsoidal approximation of the invariant domain. This paper presents a different, set-theoretic approach, which is based on the precise construction of the maximal control invariant set. The proposed control is a nonlinear one generated by point wise convex optimization.
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