ISSN:0890-6327    

DOI:10.1002/acs.4480090602

出版商:Wiley Subscription Services, Inc., A Wiley Company    

年代:1995

数据来源: WILEY

摘要:

AbstractGrey box identification refers to the practice of identifying dynamical systems in model structures exploiting partial prior information. This contribution reviews a method for stochastic grey box identification and surveys experiences and lessons of applying it to a number of industrial processes. Issues to be addressed include advantages and costs of introducing stochastics into the model, the question of what contribution must be expected from the model designer as opposed to what can be formalized in computer algorithms, and an outlook on future plans to resolve present shortcomings.

ISSN:0890-6327    

DOI:10.1002/acs.4480090603

出版商:Wiley Subscription Services, Inc., A Wiley Company    

年代:1995

数据来源: WILEY

摘要:

AbstractGrey box models are characterized by their physical significance e.g. in parametrization and by the partial prior information that is available about e.g. the parameter values. These aspects of the grey box model affect the design of optimal excitations for identification and we study the extension of classical theory for experiment design to input design for identification of grey box models. Partial prior information is expressed as a probability distribution and is employed in the design of optimal excitations through optimization of Bayesian criteria.

ISSN:0890-6327    

DOI:10.1002/acs.4480090604

出版商:Wiley Subscription Services, Inc., A Wiley Company    

年代:1995

数据来源: WILEY

摘要:

AbstractSemiphysical modelling is often interpreted as an application of system identification where physical insight into the application is used to come up with suitable non‐linear transformations of the raw measurements so as to allow for a good model structure. This modelling procedure is less ‘ambitious’ than those used for traditional physical modelling in that no complete physical structure is sought, just suitable inputs and outputs that can be subjected to more or less standard model structures such as linear regressions. In this paper we discuss a semiphysical modelling procedure and various tools supporting it. These include constructive algorithms originating from commutative and differential algebra as well as more informal tools such as the programming enviro

ISSN:0890-6327    

DOI:10.1002/acs.4480090605

出版商:Wiley Subscription Services, Inc., A Wiley Company    

年代:1995

数据来源: WILEY

摘要:

AbstractThe presented procedure computes approximate probabilistic models of complex dynamic phenomena recursively with respect to an increasing amount of observed evidence. Measured, fictitious as well as simulated data can be used in combination for obtaining a reasonably conservative approximate model. Thus information from a number of sources can be systematically merged using a refinement of the recently proposed method of Bayesian pooling of imprecise opinions from a variety of experts. It can be applied recursively as the number of treated items grows.The procedure provides (i) a new tool needed for grey as well as black box modelling, (ii) a novel adaptation of probabilistic models and (iii) an approximation of a given model by a simpler one.The general procedure is applied to the autoregressive model with exogenous variables (AM). This example illustrates the adopted approach and conmbutes to the solution of the following tasks: (i) estimation of an appropriate model structure; (ii) incorporation of prior knowledge into the initial conditions of recursive least squares; (iii) construction of a reference for an advanced forgetting technique; (iv) approximation of a complex analytic/simulation model by an ARX model.The behaviour of the procedure is illustrated on typical examples.

ISSN:0890-6327    

DOI:10.1002/acs.4480090606

出版商:Wiley Subscription Services, Inc., A Wiley Company    

年代:1995

数据来源: WILEY

摘要:

AbstractGrey box modelling traditionally reflects that botha prioriand experimental knowledge are being incorporated into the model‐building process, where both of them may exhibit uncertain character. A brief investigation into various grey box modelling approaches reveals that they differ mainly with respect to the required model accuracy. Moreover, the goal of the model application has to be considered in the model building, since this goal defines the desired accuracy of the model, which is represented as model uncertainty.This paper advocates the view that grey box modelling is model building which incorporates uncertainty description. Qualitative differential and algebraic equations are proposed in this paper as a unifying framework for development of dynamic models with uncertainty. the steps in the model development cycle are defined for this unifying framework, wherein the computational complexity issues are addressed at each step. It is also shown how qualitative differential and algebraic equations can be specialized to important well‐known grey box model forms such as robust models with parametric uncertainty, constraint qualitative differential equations and digraph models. the presented concepts and grey box model forms are illustrated on a simple example: a heat exchanger with byp

ISSN:0890-6327    

DOI:10.1002/acs.4480090607

出版商:Wiley Subscription Services, Inc., A Wiley Company    

年代:1995

数据来源: WILEY

ISSN:0890-6327    

DOI:10.1002/acs.4480090601

出版商:Wiley Subscription Services, Inc., A Wiley Company    

年代:1995

数据来源: WILEY