572,110 research outputs found
On the Parametrization of Flavor Mixing in the Standard Model
It is shown that there exist nine different ways to describe the flavor
mixing, in terms of three rotation angles and one CP-violating phase, within
the standard electroweak theory of six quarks. For the assignment of the
complex phase there essentially exists a continuum of possibilities, if one
allows the phase to appear in more than four elements of the mixing matrix. If
the phase is restricted to four elements, the phase assignment is uniquely
defined. If one imposes the constraint that the phase disappears in a natural
way in the chiral limit in which the masses of the u and d quarks are turned
off, only three of the nine parametrizations are acceptable. In particular the
``standard'' parametrization advocated by the Particle Data Group is not
permitted. One parametrization, in which the CP-violating phase is restricted
to the light quark sector, stands up as the most favorable description of the
flavor mixing.Comment: Latex 8 page
On distribution formulas for complex and -adic polylogarithms
We study an -adic Galois analogue of the distribution formulas for
polylogarithms with special emphasis on path dependency and arithmetic
behaviors. As a goal, we obtain a notion of certain universal Kummer-Heisenberg
measures that enable interpolating the -adic polylogarithmic distribution
relations for all degrees.Comment: This article has appeared in the proceedings volume "Periods in
Quantum Field Theory and Arithmetic" (J.~Burgos Gil, K.~Ebrahimi-Fard,
H.~Gangl eds), [Conference proceedings ICMAT-MZV 2014] Springer Proceedings
in Mathematics \& Statistics {\bf 314} (2020), pp.593--61
Nuclear mass predictions based on Bayesian neural network approach with pairing and shell effects
Bayesian neural network (BNN) approach is employed to improve the nuclear
mass predictions of various models. It is found that the noise error in the
likelihood function plays an important role in the predictive performance of
the BNN approach. By including a distribution for the noise error, an
appropriate value can be found automatically in the sampling process, which
optimizes the nuclear mass predictions. Furthermore, two quantities related to
nuclear pairing and shell effects are added to the input layer in addition to
the proton and mass numbers. As a result, the theoretical accuracies are
significantly improved not only for nuclear masses but also for single-nucleon
separation energies. Due to the inclusion of the shell effect, in the unknown
region, the BNN approach predicts a similar shell-correction structure to that
in the known region, e.g., the predictions of underestimation of nuclear mass
around the magic numbers in the relativistic mean-field model. This manifests
that better predictive performance can be achieved if more physical features
are included in the BNN approach.Comment: 15 pages, 4 figures, and 3 table
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Robust H2/H∞-state estimation for discrete-time systems with error variance constraints
Copyright [1997] IEEE. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.This paper studies the problem of an H∞-norm and variance-constrained state estimator design for uncertain linear discrete-time systems. The system under consideration is subjected to
time-invariant norm-bounded parameter uncertainties in both the state and measurement matrices. The problem addressed is the design of
a gain-scheduled linear state estimator such that, for all admissible measurable uncertainties, the variance of the estimation error of each state is not more than the individual prespecified value, and the transfer function from disturbances to error state outputs satisfies the prespecified H∞-norm upper bound constraint, simultaneously. The conditions for the existence of desired estimators are obtained in terms of matrix inequalities, and the explicit expression of these estimators is also derived. A numerical example is provided to demonstrate various aspects of theoretical results
H∞ fuzzy control for systems with repeated scalar nonlinearities and random packet losses
Copyright [2009] IEEE. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.This paper is concerned with the H∞ fuzzy control problem for a class of systems with repeated scalar nonlinearities and random packet losses. A modified Takagi-Sugeno (T-S) fuzzy model is proposed in which the consequent parts are composed of a set of discrete-time state equations containing a repeated scalar nonlinearity. Such a model can describe some well-known nonlinear systems such as recurrent neural networks. The measurement transmission between the plant and controller is assumed to be imperfect and a stochastic variable satisfying the Bernoulli random binary distribution is utilized to represent the phenomenon of random packet losses. Attention is focused on the analysis and design of H∞ fuzzy controllers with the same repeated scalar nonlinearities such that the closed-loop T-S fuzzy control system is stochastically stable and preserves a guaranteed H∞ performance. Sufficient conditions are obtained for the existence of admissible controllers, and the cone complementarity linearization procedure is employed to cast the controller design problem into a sequential minimization one subject to linear matrix inequalities, which can be readily solved by using standard numerical software. Two examples are given to illustrate the effectiveness of the proposed design method
Robust H∞ filtering for a class of nonlinear networked systems with multiple stochastic communication delays and packet dropouts
Copyright [2010] IEEE. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected].
By choosing to view this document, you agree to all provisions of the copyright laws protecting it.In this paper, the robust H∞ filtering problem is studied for a class of uncertain nonlinear networked systems with both multiple stochastic time-varying communication delays and multiple packet dropouts. A sequence of random variables, all of which are mutually independent but obey Bernoulli distribution, are introduced to account for the randomly occurred communication delays. The packet dropout phenomenon occurs in a random way and the occurrence probability for each sensor is governed by an individual random variable satisfying a certain probabilistic distribution in the interval. The discrete-time system under consideration is also subject to parameter uncertainties, state-dependent stochastic disturbances and sector-bounded nonlinearities. We aim to design a linear full-order filter such that the estimation error converges to zero exponentially in the mean square while the disturbance rejection attenuation is constrained to a give level by means of the H∞ performance index. Intensive stochastic analysis is carried out to obtain sufficient conditions for ensuring the exponential stability as well as prescribed H∞ performance for the overall filtering error dynamics, in the presence of random delays, random dropouts, nonlinearities, and the parameter uncertainties. These conditions are characterized in terms of the feasibility of a set of linear matrix inequalities (LMIs), and then the explicit expression is given for the desired filter parameters. Simulation results are employed to demonstrate the effectiveness of the proposed filter design technique in this paper.This work was supported in part by the Engineering and Physical Sciences Research Council (EPSRC) of the U.K. under Grant GR/S27658/01, the Royal Society of the U.K., the Alexander von Humboldt Foundation of Germany, National Natural Science Foundation of China under Grant 60825303, 60834003, 973 Project under Grant 2009CB320600, Fok Ying Tung Education Foundation under Grant 111064, and the Youth Science Fund of Heilongjiang Province under Grant QC2009C63
Experimental investigation of feedforward control schemes of a flexible robot manipulator system
This paper presents experimental investigations into the applications of feedforward control schemes for vibration control of a flexible manipulator system. Feedforward control schemes based on input shaping and filtering techniques are to be examined. A constrained planar single-link flexible manipulator is considered in this experimental work. An unshaped bang-bang torque input is used to determine the characteristic parameters of the system for design and evaluation of the input shaping control techniques. The input shapers and filtering techniques are designed based on the properties of the system. Simulation results of the response of the manipulator to the shaped and filtered inputs are presented in time and frequency domains. Performances of the shapers are examined in terms of level of vibration reduction and time response specifications. The effects of derivative order of the input shaper on the performance of the system are investigated. Finally, a comparative assessment of the control strategies is presented and discusse
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