摘要:

An identification algorithm is presented for a pollution source distributed along a river. The water quality is described by a couple of partial differential equations of the first order or a parabolic one. This problem, after transformation, results in the Fredholm integral equation of the first kind, which is non-well posed in the sense of Hadamard. The solution does not continuously depend on the observed data. The application of the regularization method proposed by Tikhonov (1963) yields a stable algorithm for the identification problem. Some simulation examples are given to illustrate the applicability of this method to environmental control systems based on the convective or dispersive phenomena.

ISSN:0020-7721    

DOI:10.1080/00207727408920135

出版商:Taylor & Francis Group    

年代:1974

数据来源: Taylor

摘要:

The use of psoudo-random binary sequence for the estimation of weighting sequence matrices of multivariable discrete-time systems is studied using the matrix approach and the least squares method. The input phase separation scheme is used for test signal. Another approach, which is a little less optimal but yet computationally much simpler, is also presented.

ISSN:0020-7721    

DOI:10.1080/00207727408920136

出版商:Taylor & Francis Group    

年代:1974

数据来源: Taylor

摘要:

In this paper a discrete-time model of a production-inventory system is considered, and model control theory is used to synthesize piecewiso-constant control policies which result in both good transient and good steady-state behaviour of the system. The theory is illustrated by the presentation of typical response characteristics of a production-inventory system subject to a deadbeat control policy of this class.

ISSN:0020-7721    

DOI:10.1080/00207727408920137

出版商:Taylor & Francis Group    

年代:1974

数据来源: Taylor

摘要:

A new technique for organizing and accessing a table of queries satisfied by at least one record of a file is proposed.

ISSN:0020-7721    

DOI:10.1080/00207727408920138

出版商:Taylor & Francis Group    

年代:1974

数据来源: Taylor

摘要:

Hierarchical decomposition is considered to be one of the most powerful and offective tools to deal with complexity. Hierarchical system theory, which deals with system decomposition and coordination, can be used to decentralize and reduce the computational efforts requirements for many large-scale problems. This is achieved by decomposing the original system problem into several lower order easier to handle sub-problems, which are then coordinated such that the overall system objectives are met. In this work a hierarchical system theory approach to the discrete-time system identification problem is considered for stochastic large-scale system applications. A set of sequential discrete-time hierarchical identification algorithms, suitable for known and unknown system noise moments, are first obtained using a maximuma posteriori(MAP) approach with covariance matching and maximum likelihood (ML) methods. This is conducted in a two level hierarchical structure with two principles of coordination. Next, the hierarchical system identification algorithms are extended to multilevel hierarchical structures based on system characteristics of priority of action, spatial structure and time behaviour. This results in multilevel and composite multilevel coordinated system identification procedures, where each subsystem unit can be treated independently in reaching the overall system optimality. Application of these algorithms for the purpose of decentralization and reduction of computational requirements as well as adaptation to structural changes in growth and merger are considered.

ISSN:0020-7721    

DOI:10.1080/00207727408920139

出版商:Taylor & Francis Group    

年代:1974

数据来源: Taylor

摘要:

A basic mathematical formalism of dynamical systems is presented from the view-point of control engineering. The notion of input-output systems is given in a general logistic format in which most of the detailed system models can be embedded. Concepts of time, time system, causality, and state are introduced. The time system is of a generalized form in which the time domains of component functions of input and output may be different from each other. The causality is a term for the traditional non-anticipation. The state is introduced firstly in a pure form. Then a state representation, state mapping, state transition, and a static output system are formalized. The results of discussion and propositions show close interrelations between the causality, state mapping, and static output system.

ISSN:0020-7721    

DOI:10.1080/00207727408920140

出版商:Taylor & Francis Group    

年代:1974

数据来源: Taylor