Fast automatic two-stage nonlinear model identification based on the extreme learning machine

It is convenient and effective to solve nonlinear problems with a model that has a linear-in-the-parameters (LITP) structure. However, the nonlinear parameters (e.g. the width of Gaussian function) of each model term needs to be pre-determined either from expert experience or through exhaustive search. An alternative approach is to optimize them by a gradient-based technique (e.g. Newton’s method). Unfortunately, all of these methods still need a lot of computations. Recently, the extreme learning machine (ELM) has shown its advantages in terms of fast learning from data, but the sparsity of the constructed model cannot be guaranteed. This paper proposes a novel algorithm for automatic construction of a nonlinear system model based on the extreme learning machine. This is achieved by effectively integrating the ELM and leave-one-out (LOO) cross validation with our two-stage stepwise construction procedure [1]. The main objective is to improve the compactness and generalization capability of the model constructed by the ELM method. Numerical analysis shows that the proposed algorithm only involves about half of the computation of orthogonal least squares (OLS) based method. Simulation examples are included to confirm the efficacy and superiority of the proposed technique.

An integrated approach for real-time model-based state-of-charge estimation of lithium-ion batteries

Lithium-ion batteries have been widely adopted in electric vehicles (EVs), and accurate state of charge (SOC) estimation is of paramount importance for the EV battery management system. Though a number of methods have been proposed, the SOC estimation for Lithium-ion batteries, such as LiFePo4 battery, however, faces two key challenges: the flat open circuit voltage (OCV) vs SOC relationship for some SOC ranges and the hysteresis effect. To address these problems, an integrated approach for real-time model-based SOC estimation of Lithium-ion batteries is proposed in this paper. Firstly, an auto-regression model is adopted to reproduce the battery terminal behaviour, combined with a non-linear complementary model to capture the hysteresis effect. The model parameters, including linear parameters and non-linear parameters, are optimized off-line using a hybrid optimization method that combines a meta-heuristic method (i.e., the teaching learning based optimization method) and the least square method. Secondly, using the trained model, two real-time model-based SOC estimation methods are presented, one based on the real-time battery OCV regression model achieved through weighted recursive least square method, and the other based on the state estimation using the extended Kalman filter method (EKF). To tackle the problem caused by the flat OCV-vs-SOC segments when the OCV-based SOC estimation method is adopted, a method combining the coulombic counting and the OCV-based method is proposed. Finally, modelling results and SOC estimation results are presented and analysed using the data collected from LiFePo4 battery cell. The results confirmed the effectiveness of the proposed approach, in particular the joint-EKF method.

An exactly solvable four transition point model

Heavy particle collisions, in particular low-energy ion-atom collisions, are amenable to semiclassical JWKB phase integral analysis in the complex plane of the internuclear separation. Analytic continuation in this plane requires due attention to the Stokes phenomenon which parametrizes the physical mechanisms of curve crossing, non-crossing, the hybrid Nikitin model, rotational coupling and predissociation. Complex transition points represent adiabatic degeneracies. In the case of two or more such points, the Stokes constants may only be completely determined by resort to the so-called comparison- equation method involving, in particular, parabolic cylinder functions or Whittaker functions and their strong-coupling asymptotics. In particular, the Nikitin model is a two transition-point one-double-pole problem in each half-plane corresponding to either ingoing or outgoing waves. When the four transition points are closely clustered, new techniques are required to determine Stokes constants. However, such investigations remain incomplete, A model problem is therefore solved exactly for scattering along a one-dimensional z-axis. The energy eigenvalue is b(2)-a(2) and the potential comprises -z(2)/2 (parabolic) and -a(2) + b(2)/2z(2) (centrifugal/centripetal) components. The square of the wavenumber has in the complex z-plane, four zeros each a transition point at z = +/-a +/- ib and has a double pole at z = 0. In cases (a) and (b), a and b are real and unitarity obtains. In case (a) the reflection and transition coefficients are parametrized by exponentials when a(2) + b(2) > 1/2. In case (b) they are parametrized by trigonometrics when a(2) + b(2) <1/2 and total reflection is achievable. In case (c) a and b are complex and in general unitarity is not achieved due to loss of flux to a continuum (O'Rourke and Crothers, 1992 Proc. R. Sec. 438 1). Nevertheless, case (c) coefficients reduce to (a) or (b) under appropriate limiting conditions. Setting z = ht, with h a real constant, an attempt is made to model a two-state collision problem modelled by a pair of coupled first-order impact parameter equations and an appropriate (T) over tilde-tau relation, where (T) over tilde is the Stueckelberg variable and tau is the reduced or scaled time. The attempt fails because (T) over tilde is an odd function of tau, which is unphysical in a real collision problem. However, it is pointed out that by applying the Kummer exponential model to each half-plane (O'Rourke and Crothers 1994 J. Phys. B: At. Mel. Opt. Phys. 27 2497) the current model is in effect extended to a collision problem with four transition points and a double pole in each half-plane. Moreover, the attempt in itself is not a complete failure since it is shown that the result is a perfect diabatic inelastic collision for a traceless Hamiltonian matrix, or at least when both diagonal elements are odd and the off-diagonal elements equal and even.

Stochastic Sznajd Model in open community

We extend the Sznajd Model for opinion formation by introducing persuasion probabilities for opinions. Moreover, we couple the system to an environment which mimics the application of the opinion. This results in a feedback, representing single-state opinion transitions in opposite to the two-state opinion transitions for persuading other people. We call this model opinion formation in an open community (OFOC). It can be seen as "stochastic extension of the Sznajd model for an open community, because it allows for "special choice of parameters to recover the original Sznajd model. We demonstrate the effect of feedback in the OFOC model by applying it to a scenario in which, e.g., opinion B is worse then opinion A but easier explained to other people. Casually formulated we analyzed the question, how much better one has to be, in order to persuade other people, provided the opinion is worse. Our results reveal a linear relation between the transition probability for opinion B and the influence of the environment on B.

Simulation of the Unsteady Gas Flow through a Three-way Automotive Catalyst

This paper describes a model of a 1.8-litre four-cylinder four-stroke gasoline engine fitted with a close-coupled three-way catalyst (TWC). Designed to meet EURO 3 emissions standards, the engine includes some advanced emission control features in addition to the TWC, namely: variable valve timing (VVT), swirl control plates, and exhaust gas recirculation (EGR). Gas flow is treated as one-dimensional (1D) and unsteady in the engine ducting and in the catalyst. Reflection and transmission of pressure waves at the boundaries of the catalyst monolith are modelled. In-cylinder combustion is represented by a two-zone burn model with dissociation and reaction kinetics. A single Wiebe analysis of measured in-cylinder pressure data is used to determine the mass fraction burned as a function of crank angle (CA) at each engine speed. Measured data from steady-state dynamometer tests are presented for operation at wide open throttle (WOT) over a range of engine speeds. These results include CA-resolved traces of pressure at various locations throughout the engine together with cycle-averaged traces of gas composition entering the catalyst as indicated by a fast-response emissions analyser. Simulated engine performance and pressure wave action throughout the engine are well validated by the measured data.

Total and single differential cross sections for simple resonant collisions using a fully orthonormal continuum-distorted-wave basis

Simple electron capture processes are studied using an orthonormal two state continuum-distorted-wave (CDW) basis. The suitability of the basis set is tested by comparing predictions for total and differential cross sections with available experimental data. Overall good agreement is obtained and the authors conclude that a relatively small CDW basis set may be suitable to model a wide variety of low-energy collisions if the members of this extended set are astutely chosen.

Ion-Atom/Argon - Calculation of ionization cross sections by fast ion impact for neutral target atoms ranging from hydrogen to argon

A FORTRAN 90 program is presented which calculates the total cross sections, and the electron energy spectra of the singly and doubly differential cross sections for the single target ionization of neutral atoms ranging from hydrogen up to and including argon. The code is applicable for the case of both high and low Z projectile impact in fast ion-atom collisions. The theoretical models provided for the program user are based on two quantum mechanical approximations which have proved to be very successful in the study of ionization in ion-atom collisions. These are the continuum-distorted-wave (CDW) and continuum-distorted-wave eikonal-initial-state (CDW-EIS) approximations. The codes presented here extend previously published. codes for single ionization of. target hydrogen [Crothers and McCartney, Comput. Phys. Commun. 72 (1992) 288], target helium [Nesbitt, O'Rourke and Crothers, Comput. Phys. Commun. 114 (1998) 385] and target atoms ranging from lithium to neon [O'Rourke, McSherry and Crothers, Comput. Phys. Commun. 131 (2000) 129]. Cross sections for all of these target atoms may be obtained as limiting cases from the present code. Title of program: ARGON Catalogue identifier: ADSE Program summary URL: http://cpc.cs.qub.ac.uk/cpc/summaries/ADSE Program obtainable from: CPC Program Library Queen's University of Belfast, N. Ireland Licensing provisions: none Computer for which the program is designed and others on which it is operable: Computers: Four by 200 MHz Pro Pentium Linux server, DEC Alpha 21164; Four by 400 MHz Pentium 2 Xeon 450 Linux server, IBM SP2 and SUN Enterprise 3500 Installations: Queen's University, Belfast Operating systems under which the program has been tested: Red-hat Linux 5.2, Digital UNIX Version 4.0d, AIX, Solaris SunOS 5.7 Compilers: PGI workstations, DEC CAMPUS Programming language used: FORTRAN 90 with MPI directives No. of bits in a word: 64, except on Linux servers 32 Number of processors used: any number Has the code been vectorized or parallelized? Parallelized using MPI No. of bytes in distributed program, including test data, etc.: 32 189 Distribution format: tar gzip file Keywords: Single ionization, cross sections, continuum-distorted-wave model, continuum- distorted-wave eikonal-initial-state model, target atoms, wave treatment Nature of physical problem: The code calculates total, and differential cross sections for the single ionization of target atoms ranging from hydrogen up to and including argon by both light and heavy ion impact. Method of solution: ARGON allows the user to calculate the cross sections using either the CDW or CDW-EIS [J. Phys. B 16 (1983) 3229] models within the wave treatment. Restrictions on the complexity of the program: Both the CDW and CDW-EIS models are two-state perturbative approximations. Typical running time: Times vary according to input data and number of processors. For one processor the test input data for double differential cross sections (40 points) took less than one second, whereas the test input for total cross sections (20 points) took 32 minutes. Unusual features of the program: none (C) 2003 Elsevier B.V All rights reserved.

Plant-wide predictive control for a thermal power plant based on a physical plant model

A constrained non-linear, physical model-based, predictive control (NPMPC) strategy is developed for improved plant-wide control of a thermal power plant. The strategy makes use of successive linearisation and recursive state estimation using extended Kalman filtering to obtain a linear state-space model. The linear model and a quadratic programming routine are used to design a constrained long-range predictive controller One special feature is the careful selection of a specific set of plant model parameters for online estimation, to account for time-varying system characteristics resulting from major system disturbances and ageing. These parameters act as nonstationary stochastic states and help to provide sufficient degrees-of-freedom to obtain unbiased estimates of controlled outputs. A 14th order non-linear plant model, simulating the dominant characteristics of a 200 MW oil-fired pou er plant has been used to test the NPMPC algorithm. The control strategy gives impressive simulation results, during large system disturbances and extremely high rate of load changes, right across the operating range. These results compare favourably to those obtained with the state-space GPC method designed under similar conditions.

Two-dimensional hygrothermal transfer in porous building materials

A two-dimensional mathematical model for evaluating the simultaneous heat and moisture migration in porous building materials was proposed. Vapor content and temperature were chosen as the principal driving potentials. The numerical solution was based on the control volume finite difference technique with fully implicit scheme in time. Two validation experiments were developed in this study. The evolution of transient moisture distributions in both one-dimensional and two-dimensional cases was measured. A comparison between experimental results and those obtained by the numerical model proves that they are fully consistent with each other. The model can be easily integrated into a whole building heat, air and moisture transfer model. Another main advantage of the present numerical method lies in the fact that the required moisture transport properties are comparatively simple and easy to determine.

Computer simulations of seasonal outbreak and diurnal vertical migration of cyanobacteria

Algal blooms caused by cyanobacteria are characterized by two features with different time scales: one is seasonal outbreak and collapse of a bloom and the other is diurnal vertical migration. Our two-component mathematical model can simulate both phenomena, in which the state variables are nutrients and cyanobacteria. The model is a set of one-dimensional reaction-advection-diffusion equations, and temporal changes of these two variables are regulated by the following five factors: (1) annual variation of light intensity, (2) diurnal variation of light intensity, (3) annual variation of water temperature, (4) thermal stratification within a water column and (5) the buoyancy regulation mechanism. The seasonal change of cyanobacteria biomass is mainly controlled by factors, (1), (3) and (4), among which annual variations of light intensity and water temperature directly affect the maximum growth rate of cyanobacteria. The latter also contributes to formation of the thermocline during the summer season. Thermal stratification causes a reduction in vertical diffusion and largely prevents mixing of both nutrients and cyanobacteria between the epilimnion and the hypolimnion. Meanwhile, the other two factors, (2) and (5), play a significant role in diurnal vertical migration of cyanobacteria. A key mechanism of vertical migration is buoyancy regulation due to gas-vesicle synthesis and ballast formation, by which a quick reversal between floating and sinking becomes possible within a water column. The mechanism of bloom formation controlled by these five factors is integrated into the one-dimensional model consisting of two reaction-advection-diffusion equations.

Detailed analytical investigation of magnetic field line random walk in turbulent plasmas: I. Two-component slab/two-dimensional turbulence

The random displacement of magnetic field lines in the presence of magnetic turbulence in plasmas is investigated from first principles. A two-component (slab/two-dimensional composite) model for the turbulence spectrum is employes. An analytical investigation of the asymptotic behavior of the field-line mean square displacement (FL-MSD) is carried out. It is shown that the magnetic field lines behave superdifusively for every large values of the position variable z, since the FL-MSD sigma varies as sigma similar to z(4/3). An intermediate diffusive regime may also possible exist for finite values of z under conditions which are explicitly determined in terms of the intrinsic turbulent plasma parameters. The superdiffusie asymptotic result is confirmed numerically via an iterative algorithm. The relevance to previous resuslts is discussed.

Increasing entanglement through engineered disorder in the random Ising chain

The ground-state entanglement entropy between block of sites in the random Ising chain is studied by means of the Von Neumann entropy. We show that in presence of strong correlations between the disordered couplings and local magnetic fields the entanglement increases and becomes larger than in the ordered case. The different behavior with respect to the uncorrelated disordered model is due to the drastic change of the ground state properties. The same result holds also for the random three-state quantum Potts model.