23 research outputs found
A review on analysis and synthesis of nonlinear stochastic systems with randomly occurring incomplete information
Copyright q 2012 Hongli Dong et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.In the context of systems and control, incomplete information refers to a dynamical system in which knowledge about the system states is limited due to the difficulties in modeling complexity in a quantitative way. The well-known types of incomplete information include parameter uncertainties and norm-bounded nonlinearities. Recently, in response to the development of network technologies, the phenomenon of randomly occurring incomplete information has become more and more prevalent. Such a phenomenon typically appears in a networked environment. Examples include, but are not limited to, randomly occurring uncertainties, randomly occurring nonlinearities, randomly occurring saturation, randomly missing measurements and randomly occurring quantization. Randomly occurring incomplete information, if not properly handled, would seriously deteriorate the performance of a control system. In this paper, we aim to survey some recent advances on the analysis and synthesis problems for nonlinear stochastic systems with randomly occurring incomplete information. The developments of the filtering, control and fault detection problems are systematically reviewed. Latest results on analysis and synthesis of nonlinear stochastic systems are discussed in great detail. In addition, various distributed filtering technologies over sensor networks are highlighted. Finally, some concluding remarks are given and some possible future research directions are pointed out. © 2012 Hongli Dong et al.This work was supported in part by the National Natural Science Foundation of China under Grants 61273156, 61134009, 61273201, 61021002, and 61004067, the Engineering and Physical Sciences Research Council (EPSRC) of the UK under Grant GR/S27658/01, the Royal Society of the UK, the National Science Foundation of the USA under Grant No. HRD-1137732, and the Alexander von Humboldt Foundation of German
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Estimation, filtering and fusion for networked systems with network-induced phenomena: New progress and prospects
In this paper, some recent advances on the estimation, filtering and fusion for networked systems are reviewed. Firstly, the network-induced phenomena under consideration are briefly recalled including missing/fading measurements, signal quantization, sensor saturations, communication delays, and randomly occurring incomplete information. Secondly, the developments of the estimation, filtering and fusion for networked systems from four aspects (linear networked systems, nonlinear networked systems, complex networks and sensor networks) are reviewed comprehensively. Subsequently, some recent results on the estimation, filtering and fusion for systems with the network-induced phenomena are reviewed in great detail. In particular, some latest results on the multi-objective filtering problems for time-varying nonlinear networked systems are summarized. Finally, conclusions are given and several possible research directions concerning the estimation, filtering, and fusion for networked systems are highlighted
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Multi-sensor multi-rate fusion estimation for networked systems: Advances and perspectives
National Natural Science Foundation of China under Grants 62103095, 61873058, 61873148 and 61933007; AHPU Youth Top-notch Talent Support Program of China under Grant 2018BJRC009; Natural Science Foundation of Anhui Province of China under Grant 2108085MA07; Royal Society of the UK; Alexander von Humboldt Foundation of Germany
Optimized state feedback regulation of 3DOF helicopter system via extremum seeking
In this paper, an optimized state feedback regulation of a 3 degree of freedom (DOF) helicopter is designed via extremum seeking (ES) technique. Multi-parameter ES is applied to optimize the tracking performance via tuning State Vector Feedback with Integration of the Control Error (SVFBICE).
Discrete multivariable version of ES is developed to minimize a cost function that measures the performance of the controller. The cost function is a function of the error between the actual and desired axis positions. The controller parameters are updated online as the optimization takes place. This method significantly decreases the time in obtaining optimal controller parameters. Simulations were conducted for the online optimization under both fixed and varying operating conditions. The results demonstrate the usefulness of using ES for preserving the maximum attainable performance
Discrete Time Systems
Discrete-Time Systems comprehend an important and broad research field. The consolidation of digital-based computational means in the present, pushes a technological tool into the field with a tremendous impact in areas like Control, Signal Processing, Communications, System Modelling and related Applications. This book attempts to give a scope in the wide area of Discrete-Time Systems. Their contents are grouped conveniently in sections according to significant areas, namely Filtering, Fixed and Adaptive Control Systems, Stability Problems and Miscellaneous Applications. We think that the contribution of the book enlarges the field of the Discrete-Time Systems with signification in the present state-of-the-art. Despite the vertiginous advance in the field, we also believe that the topics described here allow us also to look through some main tendencies in the next years in the research area
Cascades and transitions in turbulent flows
Turbulence is characterized by the non-linear cascades of energy and other
inviscid invariants across a huge range of scales, from where they are injected
to where they are dissipated. Recently, new experimental, numerical and
theoretical works have revealed that many turbulent configurations deviate from
the ideal 3D/2D isotropic cases characterized by the presence of a strictly
direct/inverse energy cascade, respectively. We review recent works from a
unified point of view and we present a classification of all known transfer
mechanisms. Beside the classical cases of direct and inverse cascades, the
different scenarios include: split cascades to small and large scales
simultaneously, multiple/dual cascades of different quantities, bi-directional
cascades where direct and inverse transfers of the same invariant coexist in
the same scale-range and finally equilibrium states where no cascades are
present, including the case when a condensate is formed. We classify all
transitions as the control parameters are changed and we analyse when and why
different configurations are observed. Our discussion is based on a set of
paradigmatic applications: helical turbulence, rotating and/or stratified
flows, MHD and passive/active scalars where the transfer properties are altered
as one changes the embedding dimensions, the thickness of the domain or other
relevant control parameters, as the Reynolds, Rossby, Froude, Peclet, or Alfven
numbers. We discuss the presence of anomalous scaling laws in connection with
the intermittent nature of the energy dissipation in configuration space. An
overview is also provided concerning cascades in other applications such as
bounded flows, quantum, relativistic and compressible turbulence, and active
matter, together with implications for turbulent modelling. Finally, we present
a series of open problems and challenges that future work needs to address.Comment: accepted for publication on Physics Reports 201
Fractional Calculus and the Future of Science
Newton foresaw the limitations of geometry’s description of planetary behavior and developed fluxions (differentials) as the new language for celestial mechanics and as the way to implement his laws of mechanics. Two hundred years later Mandelbrot introduced the notion of fractals into the scientific lexicon of geometry, dynamics, and statistics and in so doing suggested ways to see beyond the limitations of Newton’s laws. Mandelbrot’s mathematical essays suggest how fractals may lead to the understanding of turbulence, viscoelasticity, and ultimately to end of dominance of the Newton’s macroscopic world view.Fractional Calculus and the Future of Science examines the nexus of these two game-changing contributions to our scientific understanding of the world. It addresses how non-integer differential equations replace Newton’s laws to describe the many guises of complexity, most of which lay beyond Newton’s experience, and many had even eluded Mandelbrot’s powerful intuition. The book’s authors look behind the mathematics and examine what must be true about a phenomenon’s behavior to justify the replacement of an integer-order with a noninteger-order (fractional) derivative. This window into the future of specific science disciplines using the fractional calculus lens suggests how what is seen entails a difference in scientific thinking and understanding
Stirring and mixing : 1999 Program of Summer Study in Geophysical Fluid Dynamics
The central theme of the 1999 GFD Program was the stirring, transport, reaction and mixing of passive and active tracers in
turbulent, stratified, rotating fluids. The problem of mixing in fluids has applications in areas ranging from oceanography to
engineering and astrophysics. In geophysical settings, mixing spans and unites a broad range of scales -- from micrometers to
megameters. The mixing of passive tracers is of fundamental importance in environmental and industrial problems, such as
pollution, and in determining the large-scale heat and salt balance of the worlds oceans. The transport of active tracers, on the other
hand, such as vorticity, plays a key role in the turbulence that occurs in most geophysical and astrophysical fluids. William R.
Young (Scripps Institution of Oceanography) gave a series of principal lectures, the notes of which as taken by the fellows, appear
in this volume. Report of the projects of the student fellows makes up the second half of this volume.Funding was provided by the National Science Foundation under Grant No. OCE-9810647 and
the Office of Naval Research under Grant No. NOO0l4-97-1-0934
Generalized averaged Gaussian quadrature and applications
A simple numerical method for constructing the optimal generalized averaged Gaussian quadrature formulas will be presented. These formulas exist in many cases in which real positive GaussKronrod formulas do not exist, and can be used as an adequate alternative in order to estimate the error of a Gaussian rule. We also investigate the conditions under which the optimal averaged Gaussian quadrature formulas and their truncated variants are internal