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Khaled Laib

Publications and source records attributed to Khaled Laib.

7 recordsLinked to original sources

Convergence Rate Bounds for the Mirror Descent Method: IQCs, Popov Criterion and Bregman Divergence

This paper presents a comprehensive convergence analysis for the mirror descent (MD) method, a widely used algorithm in convex optimization. The key feature of this algorithm is that it provides a generalization of classical gradient-based methods via the use of generalized distance-like functions, which are formulated using the Bregman divergence. Establishing convergence rate bounds for this algorithm is in general a non-trivial problem due to the lack of monotonicity properties in the composite nonlinearities involved. In this paper, we show that the Bregman divergence from the optimal solution, which is commonly used as a Lyapunov function for this algorithm, is a special case of Lyapunov functions that follow when the Popov criterion is applied to an appropriate reformulation of the MD dynamics. This is then used as a basis to construct an integral quadratic constraint (IQC) framework through which convergence rate bounds with reduced conservatism can be deduced. We also illustrate via examples that the convergence rate bounds derived can be tight.

math.OC

A Distributed Scheme for Voltage and Frequency Control and Power Sharing in Inverter Based Microgrids

Grid-forming inverter-based autonomous microgrids present new operational challenges as the stabilizing rotational inertia of synchronous machines is absent. The design of efficient control policies for grid-forming inverters is, however, a non-trivial problem where multiple performance objectives need to be satisfied, including voltage/frequency regulation, current limiting capabilities, as well as active power sharing and a scalable operation. We propose in this paper a novel control architecture for frequency and voltage control which allows current limitation via an inner loop, active power sharing via a distributed secondary control policy and scalability by satisfying a passivity property. In particular, the frequency controller employs the inverter output current and angle to provide an angle droop-like policy which improves its stability properties. This also allows to incorporate a secondary control policy for which we provide an analytical stability result which takes line conductances into account (in contrast to the lossless line assumptions in literature). The distinctive feature of the voltage control scheme is that it has a double loop structure that uses the DC voltage in the feedback control policy to implement a power balancing strategy to improve performance. The performance of the control policy is illustrated via simulations with detailed nonlinear models in a realistic setting.

math.OC

On the synchronization of the Kuramoto-type model of oscillators with lossy couplings

We consider the problem of synchronization of coupled oscillators in a Kuramoto-type model with lossy couplings. Kuramoto models have been used to gain insight on the stability of power networks which are usually nonlinear and involve large scale interconnections. Such models commonly assume lossless couplings and Lyapunov functions have predominantly been employed to prove stability. However, coupling conductances can impact synchronization. We therefore consider a more advanced Kuramoto model that includes coupling conductances, and is characterized by nonhomogeneous coupling weights and noncomplete coupling graphs. Lyapunov analysis once such coupling conductances and aforementioned properties are included becomes nontrivial and more conventional energy-like Lyapunov functions are not applicable or are conservative. Small-signal analysis has been performed for such models, but due to the fact that we have convergence to a manifold, stability analysis via a linearization is on its own inconclusive for the nonlinear model. In this paper, we provide a formal derivation using centre manifold theory that if a particular condition on the equilibrium point associated with the coupling conductances and susceptances holds, then the synchronization manifold for the nonlinear system considered is asymptotically stable. Our analysis is demonstrated with simulations.

math.OC

Convergence Rate Bounds for the Mirror Descent Method: IQCs and the Bregman Divergence

This paper is concerned with convergence analysis for the mirror descent (MD) method, a well-known algorithm in convex optimization. An analysis framework via integral quadratic constraints (IQCs) is constructed to analyze the convergence rate of the MD method with strongly convex objective functions in both continuous-time and discrete-time. We formulate the problem of finding convergence rates of the MD algorithms into feasibility problems of linear matrix inequalities (LMIs) in both schemes. In particular, in continuous-time, we show that the Bregman divergence function, which is commonly used as a Lyapunov function for this algorithm, is a special case of the class of Lyapunov functions associated with the Popov criterion, when the latter is applied to an appropriate reformulation of the problem. Thus, applying the Popov criterion and its combination with other IQCs, can lead to convergence rate bounds with reduced conservatism. We also illustrate via examples that the convergence rate bounds derived can be tight.

math.OC

Decentralized Stability Conditions for DC Microgrids: Beyond Passivity Approaches

We consider the problem of ensuring stability in a DC microgrid by means of decentralized conditions. Such conditions are derived which are formulated as input-output properties of locally defined subsystems. These follow from various decompositions of the microgrid and corresponding properties of the resulting representations. It is shown that these stability conditions can be combined together by means of appropriate homotopy arguments, thus reducing the conservatism relative to more conventional decentralized approaches that often rely on a passivation of the bus dynamics. Examples are presented to demonstrate the efficiency and the applicability of the results derived.

math.OC

A scalable control design for grid-forming inverters in microgrids

Microgrids are increasingly recognized as a key technology for the integration of distributed energy resources into the power network, allowing local clusters of load and distributed energy resources to operate autonomously. However, microgrid operation brings new challenges, especially in islanded operation as frequency and voltage control are no longer provided by large rotating machines. Instead, the power converters in the microgrid must coordinate to regulate the frequency and voltage and ensure stability. We consider the problem of designing controllers to achieve these objectives. Using passivity theory to derive decentralized stability conditions for the microgrid, we propose a control design method for grid-forming inverters. For the analysis we use higher-order models for the inverters and also advanced dynamic models for the lines with an arbitrarily large number of states. By satisfying the decentralized condition formulated, plug-and-play operation can be achieved with guaranteed stability, and performance can also be improved by incorporating this condition as a constraint in corresponding optimization problems formulated. In addition, our control design can improve the power sharing properties of the microgrid compared to previous non-droop approaches. Finally, realistic simulations confirm that the controller design improves the stability and performance of the power network.

math.OC

Convex LMI optimization for the uncertain power flow analysis

This paper investigates the uncertain power flow analysis in distribution networks within the context of renewable power resources integration such as wind and solar power. The analysis aims to bound the worst-case voltage magnitude in any node of the network for a given uncertain power generation scenario. The major difficulty of this problem is the non-linear aspect of power flow equations. The proposed approach does not require the linearization of these equations and formulates the problem as an optimization problem with polynomial constraints. A new tool to investigate the feasibility of such problems is presented and it is obtained as an extension of the $\mathcal{S}-$procedure, a fundamental result in robustness analysis. A solution to the uncertain power flow analysis problem is proposed using this new tool. The different obtained results of this paper are expressed as LMI optimization problems which guaranties an efficient numerical resolution as it will be demonstrated through an illustrative example.

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