Interval Prediction for Continuous-Time Systems with Parametric Uncertainties

The problem of behaviour prediction for linear parameter-varying systems is considered in the interval framework. It is assumed that the system is subject to uncertain inputs and the vector of scheduling parameters is unmeasurable, but all uncertainties take values in a given admissible set. Then an interval predictor is designed and its stability is guaranteed applying Lyapunov function with a novel structure. The conditions of stability are formulated in the form of linear matrix inequalities. Efficiency of the theoretical results is demonstrated in the application to safe motion planning for autonomous vehicles.Comment: 6 pages, CDC 2019. Website: https://eleurent.github.io/interval-prediction

Homological mirror symmetry for punctured spheres

We prove that the wrapped Fukaya category of a punctured sphere ($S^2$ with an arbitrary number of points removed) is equivalent to the triangulated category of singularities of a mirror Landau-Ginzburg model, proving one side of the homological mirror symmetry conjecture in this case. By investigating fractional gradings on these categories, we conclude that cyclic covers on the symplectic side are mirror to orbifold quotients of the Landau-Ginzburg model.Comment: 38 pages, 5 figures; v2: minor revisions (similar to published version

Moment Matching Based Model Reduction for LPV State-Space Models

We present a novel algorithm for reducing the state dimension, i.e. order, of linear parameter varying (LPV) discrete-time state-space (SS) models with affine dependence on the scheduling variable. The input-output behavior of the reduced order model approximates that of the original model. In fact, for input and scheduling sequences of a certain length, the input-output behaviors of the reduced and original model coincide. The proposed method can also be interpreted as a reachability and observability reduction (minimization) procedure for LPV-SS representations with affine dependence

Enhancement of adaptive observer robustness applying sliding mode techniques

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record.The problem studied in this paper is one of improving the performance of a class of adaptive observer in the presence of exogenous disturbances. The H1 gains of both, a conventional and the newly proposed sliding-mode adaptive observer, are evaluated to assess the effect of disturbances on the estimation errors. It is shown that if the disturbance is \matched" in the plant equations, then including an additional sliding-mode feedback injection term, dependent on the plant output, improves the accuracy of observation

On the robust synchronization of Brockett oscillators

International audienceIn this article, motivated by a recent work of R. Brockett Brockett (2013), we study a robust synchronization problem for multistable Brockett oscillators within an Input-to-State Stability (ISS) framework. Based on a recent generalization of the classical ISS theory to multistable systems and its application to the synchronization of multistable systems, a synchronization protocol is designed with respect to compact invariant sets of the unperturbed Brockett oscillator. The invariant sets are assumed to admit a decomposition without cycles (i.e. with neither homoclinic nor heteroclinic orbits). Contrarily to the local analysis of Brockett (2013), the conditions obtained in our work are global and applicable for family of non-identical oscillators. Numerical simulation examples illustrate our theoretical results

The Alestle - Vol. 58 No. 22 - 11/08/2005

Vol. 58 No. 2

Oscillatority Conditions for Nonlinear Systems with Delay

Sufficient conditions for oscillatority in the sense of Yakubovich for a class of time delay nonlinear systems are proposed. Under proposed conditions, upper and lower bounds for oscillation amplitude are given. Examples illustrating analytical results by computer simulation are presented

Robust Estimation of Fundamental Frequency Positive-Sequence Component for Grid-Integration Applications in Energy Systems

This article studies the problem of fundamental frequency positive-sequence component separation in unbalanced three-phase systems for grid-integration applications. We propose a-simple-to-implement approach involving a modified delayed signal cancellation method and moving average filtering. A delay-based linear-regression framework is considered to make the sequence component separation frequency-adaptive, providing fast and accurate frequency estimation. Comparative experimental results demonstrate the suitability of the proposed method over conventional approaches