Conditionally minimax algorithm for nonlinear system stateestimation

In this note, a method of conditionally minimax nonlinear filtering (CMNF) of processes in nonlinear stochastic discrete-time controlled systems is proposed. The CMNF is derived by means of local nonparametric optimization of the filtering process given the class of admissible filters. Sufficient conditions for the existence of the CMNF are considered, and the properties of CMNF estimates are investigated. Results of the CMNF application to control and identification problems are presented     

A computational algorithm for system modelling based on bi-dimensional finite element techniques

This paper develops a modelling methodology for studying relations defined a priori in two dimensions, z = u(x, y), for which experimental data are known. An innovation is that the methodology is based on bi-dimensional finite element techniques, in which the model’s value consists of a finite number of points, making it possible to obtain its value at any point. Its application permits obtaining representational models of the relation. A computational algorithm is presented; its program has been called Finit Trap 2D, which generates families of models. It has defined criteria for model selection based on information parameters.This scientific research technique complements those existing in scientific literature for generating mathematical models based on experimental data [Cortés M, Villacampa Y, Mateu J, Usó, JL. A new methodology for modelling highly structured systems. Environmental modelling and software 2000;15(5):461–70, S-PLUS 2000. Guide to statistics, vosl. 1–2. Mathsoft Inc.; 1999, SPSS 12.0. Guide to statistics, Mathsoft Inc.; 2003, Verdu F. Un algoritmo para la construcción múltiple de modelos matemáticos no lineales y el estudio de su estabilidad, Thesis Doctoral, Universidad de Alicante; 2001, Verdu F, Villacampa Y. A computational algorithm for the multiple generation of nonlinear mathematical models and stability study. Advances in Engineering Software 2008;39(5):430–7, Villacampa Y, Cortés M, Vives F, Usó JL, Castro MA. A new computational algorithm to construct mathematical models. In: Ecosystems and sustainable development II. Advances in ecological sciences, vol. 2, WIT Press: Southampton, Boston; 1999], and will be useful in the effort to simplify the model.It should be emphasised that representational models have been generated from bi-dimensional finite element models. This will naturally lead to their future application in processes described by partial differential equation whose coefficients are functions, A(x, y) for which only experimental data are known.     

Visualization techniques for modelling carbon allotropes

Carbon takes many different forms, each with its own electronic structure and has a fantastic range of properties. As well as graphite/diamond, a hexagonal diamond called londsdaleite, and amorphous carbons of sp², sp³ and mixed natures there are all the fullerenes, graphene, nanotubes, etc. Fortunately, their different electronic structures take distinct geometrical forms, so that deducing the geometry of a sample that has been simulated is a crucial step towards understanding its properties. Visualization is essential for understanding sample geometries. AViz [J. Adler, Computers in Science and Engineering 5 (2003) 61] is an Atomistic Visualization package developed at the Technion that can be freely downloaded and installed. Both still and animated AViz implementations for viewing data from our atomistic simulations of carbon allotropes enable understanding of the simulation results and when compared with laboratory experiments and theoretical models provide insight into nanodiamond growth, gas flow in nanotubes, nanotube vibrations and other topics of current research interest.     

TCSC 系统的自适应minimax 干扰抑制控制器设计

针对含有未知外部干扰和不确定参数的非线性晶闸管控制串联补偿器(TCSC) 系统, 提出一种L₂增益干扰抑制算法. 将minimax 方法引入耗散Hamilton 系统, 消除了不等式假设条件的约束; 构造检验函数, 推算出系统所能承受的最大干扰程度, 降低了传统干扰处理方法的保守性; 采用参数映射方法设计自适应律, 提高了参数跟踪效率. 最后通过机械功率和对地短路故障的仿真结果表明了所提出的控制方案能够有效改善系统的暂态性能.

     

An overview of physically-based modelling techniques for virtual environments

A class of virtual environments is concerned with the representation of behaviour that is apparent in the real world. In order to model this behaviour, sophisticated physical models are required. The development of these models, classed asphysically-based modelling, is based upon the fundamental concepts of Newtonian dynamics. Considerable research into physically-based modelling has already been conducted by the computer graphics community, permitting realistic animation of object motion. The application of physical models to virtual environments poses further problems, not least that of real-time execution in a fully interactive environment. This paper gives an overview of the existing computer graphics research concerned with physically-based modelling, discussing the merits and problems of various techniques in terms of the requirements of virtual environment.     

面向嵌入式系统的IPSec形式化建模

为了满足嵌入式系统在网络通信环境下的一些安全需求,通过考察嵌入式开发的系统环境,对比现存的一些网络安全问题的解决方法,采用选取适用的IPSec(网络层安全协议)模块,并使用形式化语言对其进行描述,以给有此类安全需求的嵌入式开发提供一个形式化的IPSec模型.同时,在协议的开发过程中引入形式化的方法也有利于保证协议的一致性.     

A support system for optimization modelling

With widespread use of executive decision support systems, the activity of modelling itself needs to be supported by a user friendly interface. This paper outlines an effort in this direction with respect to optimization modelling using linear programs. The approach is through a synthesis of a modelling language (LAMP) under development, for manipulating the structure, and a commercially available database management system for manipulating the data. Such a synthesis provides a very powerful ‘what if’ analysis capability paving the way for a new generation of modelling systems.     

Symbolic manipulation techniques for low order LFT-based parametric uncertainty modelling

Symbolic techniques are very useful in obtaining low order LFT-representations of linear parametric models. The main role of symbolic manipulations is to find, via suitable pre-processing steps, equivalent representations of rationally dependent parametric matrices, which automatically lead to lower order LFT-representations. In this paper we give an overview of symbolic processing methods and we propose some new techniques and several enhancements of existing methods. All proposed methods are implemented in the latest version of the LFR-toolbox and served to illustrate the strengths of symbolic processing in obtaining low order LFT-representations of two challenging parametric model examples.     

Implementing IDEF techniques as simulation modelling specifications

Recent advantages in computer software have seen the introduction of powerful and easy-to-use simulation products, but unfortunately, still locking the ability to analyse real world problems in a high level terminology. A recent project undertaken for the company ATNS, forms the case study for demonstrating the merging of IDEF techniques and simulation modelling into meaningful business models.     

A system for visual role-based policy modelling

The definition of security policies in information systems and programming applications is often accomplished through traditional low level languages that are difficult to use. This is a remarkable drawback if we consider that security policies are often specified and maintained by top level enterprise managers who would probably prefer to use simplified, metaphor oriented policy management tools.To support all the different kinds of users we propose a suite of visual languages to specify access and security policies according to the role based access control (RBAC) model. Moreover, a system implementing the proposed visual languages is proposed. The system provides a set of tools to enable a user to visually edit security policies and to successively translate them into (eXtensible Access Control Markup Language) code, which can be managed by a Policy Based Management System supporting such policy language.The system and the visual approach have been assessed by means of usability studies and of several case studies. The one presented in this paper regards the configuration of access policies for a multimedia content management platform providing video streaming services also accessible through mobile devices.     

A system for compartmental modelling and simulation

The paper describes a software package for modelling and simulating compartmental systems based upon a generalisation of the equations of compartmental systems. The aim is a versatile package which can be used for rapid model development. Its use is first illustrated in a number of simple classical examples. The power of the software--and more generally the methodology--is demonstrated by showing its application in developing a model-based system for insulin planning for diabetic patients. The software has been written in Pascal and runs on IBM PC and compatible computers.     

A PDP constructive algorithm for system modelling

A new constructive algorithm is presented for building neural networks that learn to reproduce output temporal sequences based on one or several input sequences. This algorithm builds a network for the task of system modelling, dealing with continuous variables in the discrete time domain. The constructive scheme makes it user independent. The network's structure consists of an ordinary set and a classification set, so it is a hybrid network like that of Stokbro et al. [6], but with a binary classification. The networks can easily be interpreted, so the learned representation can be transferred to a human engineer, unlike many other network models. This allows for a better understanding of the system structure than just its simulation. This constructive algorithm limits the network complexity automatically, hence preserving extrapolation capabilities. Examples with real data from three totally different sources show good performance and allow for a promising line of research.     

Computational system identification for Bayesian NARMAX modelling

In this contribution we derive a computational Bayesian approach to NARMAX model identification. The identification algorithm exploits continuing advances in computational processing power to numerically obtain posterior distributions for both model structure and parameters via sampling methods. The main advantage of this approach over other NARMAX identification algorithms is that for the first time model uncertainty is characterised as a byproduct of the identification procedure. The algorithm is based on the reversible jump Markov chain Monte Carlo (RJMCMC) procedure. Key features of the approach are (i) sampling of unselected model terms for testing for inclusion in the model (the birth move), which encourages global searching of the model term space, (ii) sampling of previously selected model terms for testing for exclusion from the model—a naturally incorporated pruning step (the death move), which leads to model parsimony, and (iii) estimation of model and parameter distributions, which are naturally generated in the Bayesian framework. We present a numerical example to demonstrate the algorithm and a comparison with a forward regression method: the results show that the RJMCMC approach is competitive and gives useful additional information regarding uncertainty in both model parameters and structure.     

Spherical approximations for minimax optimization problems

A general iterative method for the solution of convex minimax optimization problems is proposed. At each iteration, the functions are locally approximated by spheres and the resulting minimax problem is solved. We tested the algorithm on three different minimax location problems in the plane. Computational results with these problems are favorable.     

Entropy minimax expansions for waveform analysis

Consider a collection of waveforms, each of which is treated as a set of independent variables containing information about some other (dependent) variable. This paper addresses the problem of finding informationally efficient expansions of the waveforms. A procedure is described for determining conditional entropy efficient basis functions for the given collection of waveforms, where the entropy is conditioned on the specified dependent variable. Use of these basis functions for approximate waveform reconstruction minimizes the loss of information about the dependent variable (the degree of approximation depending upon the number of basis functions used).     

Computational techniques for hybrid system verification

This paper concerns computational methods for verifying properties of polyhedral invariant hybrid automata (PIHA), which are hybrid automata with discrete transitions governed by polyhedral guards. To verify properties of the state trajectories for PIHA, the planar switching surfaces are partitioned to define a finite set of discrete states in an approximate quotient transition system (AQTS). State transitions in the AQTS are determined by the reachable states, or flow pipes, emitting from the switching surfaces according to the continuous dynamics. This paper presents a method for computing polyhedral approximations to flow pipes. It is shown that the flow-pipe approximation error can be made arbitrarily small for general nonlinear dynamics and that the computations can be made more efficient for affine systems. The paper also describes CheckMate, a MATLAB-based tool for modeling, simulating and verifying properties of hybrid systems based on the computational methods previously described.     

Algorithms for solving minimax scheduling problem

A series of exact and approximate algorithms are developed for the problem of time-optimal scheduling without interruptions and switchings in a multiprocessor system. The efficiency of these algorithms is determined and the comparative analysis is performed.     

Incremental constraint modelling in a feature modelling system

The techniques of constraint propagation have recently been successfully applied to feature-based design. Because of their speed, constraint propagation methods allow incremental design and rapid local modifcations of the part. However, cyclic constraints cause serious problems to current constraint propagation algorithms. Variational geometric design systems can, in principle, manage these cases. Unfortunately, this typically requires complete re-evaluation of the underlying set of constraint equations, making the method unsuitable for interactive use. The proposed system aims to localize the problem of constraint solving and maintenance. The constraint graph of the part or assembly is divided into several independent partial graphs, subsystems. Afterwards, each subsystem is handled separately using a selected constraint solving technique for the subsystem.