| 1. |
- Gao, Yulong, et al.
(författare)
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Distributed Freeway Ramp Metering : Optimization on Flow Speed
- 2017
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Ingår i: 2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017. - : IEEE. - 9781509028733
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Konferensbidrag (refereegranskat)abstract
- This paper studies the distributed freeway ramp metering problem, for which the cell transmission model (CTM) is utilized. Considering the jam density and the upper bounds on the queue lengths and the ramp metering, we first provide feasibility conditions with respect to the external demand to ensure the controllability of the freeway. Assuming that the freeway is controllable, we formulate an optimization problem which tradeoffs the maximum average flow speed and the minimum waiting queue for each cell. Although the cells of the CTM are dynamically coupled, we propose a distributed backward algorithm for the optimization problem and prove that the solution to the problem is a Nash equilibrium. Furthermore, if the optimization problem is simplified to only maximization of the average flow speed, we argue that the obtained explicit distributed controller is globally optimal. A numerical example is given to illustrate the effectiveness of the proposed control algorithm.
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| 2. |
- Jafarian, Matin, et al.
(författare)
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A combined nodal and uniform pricing mechanism for congestion management in distribution power networks
- 2020
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Ingår i: Electric power systems research. - : ELSEVIER SCIENCE SA. - 0378-7796 .- 1873-2046. ; 180
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Tidskriftsartikel (refereegranskat)abstract
- We present a price-based approach for congestion management in distribution power systems with renewable generations with the final goal of maximizing a social welfare function which includes net revenues of network users as well as the cost of real power losses. Particularly, we design a combined nodal and uniform pricing mechanism for maximization of the social welfare function while maintaining voltage magnitudes in a desired bound and respecting the grid's actual capacity. Storage systems are considered in order to increase/add elasticity to generations and loads. Simulation results are provided for a modified IEEE-37 bus. A scenario is numerically simulated where the excess of generation in the absence of storage and price signals leads to deviations of voltages from a desired bound. Thereafter, it is shown that the application of the price signals is effective to maintain the voltages within the desired bound while the designed social welfare function is maximized.
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| 3. |
- Jafarian, Matin
(författare)
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Robust consensus of unicycles using ternary and hybrid controllers
- 2017
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Ingår i: International Journal of Robust and Nonlinear Control. - : Wiley-Blackwell. - 1049-8923 .- 1099-1239. ; 27:17, s. 4013-4034
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Tidskriftsartikel (refereegranskat)abstract
- This paper presents consensus of the orientations and average positions for a group of unicycles using ternary and hybrid controllers. The decentralized controllers designed to reach consensus of the average positions take only values in the set {-1; 0; +1}. In addition, a hybrid controller is introduced to control the orientations. Finite-time practical consensus of the average positions is proven despite the simple ternary control laws together with asymptotic consensus of the orientations. Furthermore, the consensus problem is studied in the presence of matched input disturbances that are locally rejected using an internal-model-based controller. The analysis is performed in a hybrid framework. Simulation results illustrate the effectiveness of the design.
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| 4. |
- Jafarian, Matin, et al.
(författare)
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Stochastic phase-cohesiveness of discrete-time Kuramoto oscillators in a frequency-dependent tree network
- 2019
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Ingår i: Proceedings 2019 18th European Control Conference (ECC). - : IEEE. - 9783907144008 ; , s. 1987-1992
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Konferensbidrag (refereegranskat)abstract
- This paper presents the notion of stochastic phase-cohesiveness based on the concept of recurrent Markov chains and studies the conditions under which a discrete-time stochastic Kuramoto model is phase-cohesive. It is assumed that the exogenous frequencies of the oscillators are combined with random variables representing uncertainties. A bidirectional tree network is considered such that each oscillator is coupled to its neighbors with a coupling law which depends on its own noisy exogenous frequency. In addition, an undirected tree network is studied. For both cases, a sufficient condition for the common coupling strength (kappa) and a necessary condition for the sampling-period are derived such that the stochastic phase-cohesiveness is achieved. The analysis is performed within the stochastic systems framework and validated by means of numerical simulations.
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| 5. |
- Jafarian, Matin, et al.
(författare)
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Stochastic Stability of Discrete-Time Phase-Coupled Oscillators over Uncertain and Random Networks
- 2024
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Ingår i: IEEE Transactions on Automatic Control. - : Institute of Electrical and Electronics Engineers (IEEE). - 0018-9286 .- 1558-2523. ; 69:5, s. 2915-2930
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Tidskriftsartikel (refereegranskat)abstract
- This article studies stochastic relative phase stability, i.e., stochastic phase-cohesiveness, of discrete-time phase-coupled oscillators. The stochastic phase-cohesiveness in two types of networks is studied. First, we consider oscillators coupled with 2π-periodic odd functions over underlying undirected graphs subject to both multiplicative and additive stochastic uncertainties. We prove stochastic phase-cohesiveness of the network with respect to two specific, namely, in-phase and antiphase, sets by deriving sufficient coupling conditions. We show the dependency of these conditions on the size of the mean values of additive and multiplicative uncertainties, as well as the sign of the mean values of multiplicative uncertainties. Furthermore, we discuss the results under a relaxation of the odd property of the coupling function. Second, we study an uncertain network in which the multiplicative uncertainties are governed by the Bernoulli process representing the well-known Erdös-Rényi network. We assume constant exogenous frequencies and derive sufficient conditions for achieving both stochastic phase-cohesive and phase-locked solutions, i.e., stochastic phase-cohesiveness with respect to the origin. For the latter case, where identical exogenous frequencies are assumed, we prove that any positive probability of connectivity leads to phase-locking. Thorough analyses are provided, and insights obtained from stochastic analysis are discussed, along with numerical simulations to validate the analytical results.
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| 6. |
- Jafarian, Matin, et al.
(författare)
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Synchronization of Kuramoto oscillators in a bidirectional frequency-dependent tree network
- 2018
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Ingår i: 2018 IEEE CONFERENCE ON DECISION AND CONTROL (CDC). - : IEEE. - 9781538613955 ; , s. 4505-4510
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Konferensbidrag (refereegranskat)abstract
- This paper studies the synchronization of a finite number of Kuramoto oscillators in a frequency-dependent bidirectional tree network. We assume that the coupling strength of each link in each direction is equal to the product of a common coefficient and the exogenous frequency of its corresponding source oscillator. We derive a sufficient condition for the common coupling strength in order to guarantee frequency synchronization in tree networks. Moreover, we discuss the dependency of the obtained bound on both the graph structure and the way that exogenous frequencies are distributed. Further, we present an application of the obtained result by means of an event-triggered algorithm for achieving frequency synchronization in a star network assuming that the common coupling coefficient is given.
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| 7. |
- Jafarian, Matin, et al.
(författare)
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Synchronization of quadratic integrate-and-fire spiking neurons : Constant versus voltage-dependent couplings
- 2019
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Ingår i: Proceedings of the IEEE Conference on Decision and Control. - : Institute of Electrical and Electronics Engineers Inc.. - 9781728113982 ; , s. 4711-4716
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Konferensbidrag (refereegranskat)abstract
- This paper studies synchronization of a network of hybrid quadratic integrate-and-fire spiking neurons communicating over a complete graph and interconnected by means of bidirectional electrical couplings. Synchronization of the network of identical neurons with a common and constant coupling strength is studied using a Lyapunov-based argument for sufficiently large coupling strength. In addition, a voltage-dependent coupling law is proposed. It is assumed that each neuron is coupled to each of its neighbors by a coupling law which depends on the voltage of its neighboring neuron. For the voltage-dependent case, a sufficient condition for synchronization of two interconnected neurons is presented. Moreover, a comparison between the two mechanisms is given. Simulation results are provided to verify the theoretical analysis.
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| 8. |
- Villani, Gianluca, et al.
(författare)
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Analysis of free recall dynamics of an abstract working memory model
- 2020
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Ingår i: 2020 American Control Conference (ACC). - : IEEE. ; , s. 2562-2567
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Konferensbidrag (refereegranskat)abstract
- This paper analyzes the free recall dynamics of a working memory model. Free recalling is the reactivation of a stored pattern in the memory in the absence of the pattern. Our free recall model is based on an abstract model of a modular neural network composed on N modules, hypercolumns, each of which is a bundle of minicolumns. This paper considers a network of N modules, each consisting of two minicolumns, over a complete graph topology. We analyze the free recall dynamics assuming a constant, and homogeneous coupling between the network modules. We obtain a sufficient condition for synchronization of network's minicolumns whose activities are positively correlated. Furthermore, for the synchronized network, the bifurcation analysis of one module is presented. This analysis gives a necessary condition for having a stable limit cycle as the attractor of each module. The latter implies recalling a stored pattern. Numerical results are provided to verify the theoretical analysis.
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| 9. |
- Yoo, Jaehyun, et al.
(författare)
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Event-triggered Model Predictive Control with Machine Learning for Compensation of Model Uncertainties
- 2017
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Ingår i: 2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017. - : Institute of Electrical and Electronics Engineers (IEEE). - 9781509028733 ; , s. 5463-5468
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Konferensbidrag (refereegranskat)abstract
- As one of the extensions of model predictive control (MPC), event-triggered MPC takes advantage of the reduction of control updates. However, approaches to event-triggered MPCs may be subject to frequent event-triggering instants in the presence of large disturbances. Motivated by this, this paper suggests an application of machine learning to this control method in order to learn a compensation model for disturbance attenuation. The suggested method improves both event-triggering policy efficiency and control accuracy compared to previous approaches to event-triggered MPCs. We employ the radial basis function (RBF) kernel based machine learning technique. By the universial approximation property of the RBF, which imposes an upper bound on the training error, we can present the stability analysis of the learningaided control system. The proposed algorithm is evaluated by means of position control of a nonholonomic robot subject to state-dependent disturbances. Simulation results show that the developed method yields not only two times less event triggering instants, but also improved tracking performance.
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