On designing observers for time-delay systems with nonlinear disturbances

This is the post print version of the article. The official published version can be obtained from the link below - Copyright 2002 Taylor & Francis LtdIn this paper, the observer design problem is studied for a class of time-delay nonlinear systems. The system under consideration is subject to delayed state and non-linear disturbances. The time-delay is allowed to be time-varying, and the non-linearities are assumed to satisfy global Lipschitz conditions. The problem addressed is the design of state observers such that, for the admissible time-delay as well as non-linear disturbances, the dynamics of the observation error is globally exponentially stable. An effective algebraic matrix inequality approach is developed to solve the non-linear observer design problem. Specifically, some conditions for the existence of the desired observers are derived, and an explicit expression of desired observers is given in terms of some free parameters. A simulation example is included to illustrate the practical applicability of the proposed theory.The work of Z. Wang was supported in part by the University of Kaiserslautern of Germany and the Alexander von Humboldt Foundation of Germany

Algorithms for worst case identification in H-infinity and the nu-gap metric

This paper considers two robustly convergent algorithms for the identification of a linear system from (possibly) noisy frequency response data. Both algorithms are based on the same principle; obtaining a good worst case fit to the data under a smoothness constraint on the obtained model. However they differ in their notions of distance and smoothness. The first algorithm yields an FIR model of a stable system and is optimal, in a certain sense for a finite model order. The second algorithm may be used for modelling unstable plants and yields a real rational approximation in the -gap. Given a model and a controller stabilising the true plant, a procedure for winding number correction is also suggested

Multivariable control of a grid-connected wind energy conversion system with power quality enhancement

This document is the Accepted Manuscript version of the following article: Kaddour Fouad, Houari Merabet Boulouiha, Ahmed Allali, Ali Taibi, and Mouloud Denai, ‘Multivariable control of a grid-connected wind energy conversion system with power quality enhancement’, Energy Systems, Vol. 9 (1): 25-57, February 2018. The final publication is available at Springer via: https://doi.org/10.1007/s12667-016-0223-7This paper proposes the design of a multivariable robust control strategy for a variable-speed WECS based on a SCIG. Optimal speed control of the SCIG is achieved by a conventional PI controller combined with a MPPT strategy. DTC-SVM technique based on a simple Clarke transformation is used to control the generator-side three-level converter in the variable speed WECS. The flow of real and reactive power between the inverter and the grid is controlled via the grid real and reactive currents and the DC link voltage using multivariable H∞ control. The overall WECS and control scheme are developed in Matlab/Simulink and the performance of the proposed control strategy is evaluated via a set of simulation scenarios replicating various operating conditions of the WECS such as variable wind speed and asymmetric single grid faults. The power quality of the WECS system under H∞ control control approach is assessed and the results show a significant improvement in the total harmonic distorsion as compared to that achieved with a classical PI control.Peer reviewedFinal Accepted Versio

Credible Autocoding of Convex Optimization Algorithms

International audienceThe efficiency of modern optimization methods, coupled with increasing computational resources, has led to the possibility of real-time optimization algorithms acting in safety critical roles. There is a considerable body of mathematical proofs on on-line optimization programs which can be leveraged to assist in the development and verification of their implementation. In this paper, we demonstrate how theoretical proofs of real-time optimization algorithms can be used to describe functional properties at the level of the code, thereby making it accessible for the formal methods community. The running example used in this paper is a generic semi-definite programming (SDP) solver. Semi-definite programs can encode a wide variety of optimization problems and can be solved in polynomial time at a given accuracy. We describe a top-to-down approach that transforms a high-level analysis of the algorithm into useful code annotations. We formulate some general remarks about how such a task can be incorporated into a convex programming autocoder. We then take a first step towards the automatic verification of the optimization program by identifying key issues to be adressed in future work

Guaranteed and randomized methods for stability analysis of uncertain metabolic networks

A persistent problem hampering our understanding of the dynamics of large-scale metabolic networks is the lack of experimentally determined kinetic parameters that are necessary to build computationalmodels of biochemical processes. To overcome some of the limitations imposed by absent or incomplete kinetic data, structural kinetic modeling (SKM) was proposed recently as an intermediate approach between stoichiometric analysis and a full kinetic description. SKM extends stationary flux-balance analysis (FBA) by a local stability analysis utilizing an appropriate parametrization of the Jacobian matrix. To characterize the Jacobian, we utilize results from robust control theory to determine subintervals of the Jacobian’ entries that correspond to asymptotically stable metabolic states. Furthermore, we propose an efficient sampling scheme in combination with methods from computational geometry to sketch the stability region. A glycolytic pathway model comprising 12 uncertain parameters is used to assess the feasibility of the method