63,779 research outputs found
H∞ optimal control. Part 1. Model matching
No full textOur aim is to develop a new approach for solving the H∞ optimal control problem where the feedback arrangement takes the form of a linear fractional transformation. In Part 1, a basic kind of model-matching problem is considered: given rational matrices M(s) and N(s), the H∞-norm of an error function defined as E(s) = M(s) - N(s)Q(s) is minimized (or bounded) subject to E(s) and Q(s) being stable. Closed-form state-space characterizations are obtained for both E(s) and Q(s). The results established here will be used in Part 2 of the paper Y. S. Hung 1989) to solve the H∞ optimal control problem.link_to_subscribed_fulltex
Detection by PCR of Candidatus Liberibacter asiaticus, the bacterium causing citrus Huanglongbing in vector psyllids: application to the study of vector-pathogen relationships
No full textDistributed H∞-consensus filtering in sensor networks with multiple missing measurements: The finite-horizon case
No full textThe official published version of the article can be found at the link below.This paper is concerned with a new distributed H∞-consensus filtering problem over a finite-horizon for sensor networks with multiple missing measurements. The so-called H∞-consensus performance requirement is defined to quantify bounded consensus regarding the filtering errors (agreements) over a finite-horizon. A set of random variables are utilized to model the probabilistic information missing phenomena occurring in the channels from the system to the sensors. A sufficient condition is first established in terms of a set of difference linear matrix inequalities (DLMIs) under which the expected H∞-consensus performance constraint is guaranteed. Given the measurements and estimates of the system state and its neighbors, the filter parameters are then explicitly parameterized by means of the solutions to a certain set of DLMIs that can be computed recursively. Subsequently, two kinds of robust distributed H∞-consensus filters are designed for the system with norm-bounded uncertainties and polytopic uncertainties. Finally, two numerical simulation examples are used to demonstrate the effectiveness of the proposed distributed filters design scheme.This work was supported in part by the Engineering and Physical Sciences Research Council (EPSRC) of the UK under Grant GR/S27658/01, the Royal Society of the UK, and the Alexander von Humboldt Foundation of Germany
Dynamic Shape Estimation by Modal Approach Using Fiber Bragg Grating Strain Sensors
No full textThe first author wishes to thank ASEM-DUO Fellowship Program for the support throughout the duration of this work.
The authors also wish to thank Prof. Chun-Gon Kim and his fiber optic sensor group at Aerospace Engineering
Department of KAIST for their help for preparation of the sensors and sensing systems
On the Coupling Lengths Between Two Circular Cylindrical Dielectric Waveguides:Exact Solution versus Coupled-Mode Analysis
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