ISSN:0020-7179    

DOI:10.1080/00207179208934223

出版商:Taylor & Francis Group    

年代:1992

数据来源: Taylor

摘要:

In this second part of a three part series of papers examining the performance issues raised by the introductory paper (O'Reilly and Leithead 1991) on individual channel design for multivariable control, attention is focused on robustness: that is, on the meeting of performance specifications—in particular closed-loop system stability—in the face of plant uncertainty. The main results are that the use of phase margins and gain margins to assess robustness of 2-input 2-output multi-variable systems is justified. Further, it is shown that controllers for uncertain 2-input 2-output multivariable systems can be designed by classical SISO Nyquist-Bode local loop shaping using stable minimum phase controllers. Several additional results are also described in the paper.

ISSN:0020-7179    

DOI:10.1080/00207179208934224

出版商:Taylor & Francis Group    

年代:1992

数据来源: Taylor

摘要:

The linear regulator problem is studied for systems with slow and fast modes. Using the descriptor variable method, the design of sub-optimal regulators for such systems is completely decomposed. It is shown that the sub-optimal regulator is composed of fast and slow regulators, and that both of these, mutually decoupled, can be designed independently. A relevant computational procedure is also presented. The procedure is applicable to designs of sub-optimal regulators with either finite or infinite terminal time, and for both singular and normal singularly perturbed systems.

ISSN:0020-7179    

DOI:10.1080/00207179208934225

出版商:Taylor & Francis Group    

年代:1992

数据来源: Taylor

摘要:

The problem of output stabilization for uncertain S1SO systems is considered. Using structural transformations uncertain systems can change to the form convenient for output feedback design. Synthesis of observer-based variable structure control for asymptotical stabilization or uniform ultimate boundedness of the closed-loop system is provided. Examples are considered and simulation results are given.

ISSN:0020-7179    

DOI:10.1080/00207179208934226

出版商:Taylor & Francis Group    

年代:1992

数据来源: Taylor

摘要:

The problem of output stabilization for uncertain MIMO systems is considered. Using structural transformations, an uncertain system is changed to a "form convenient for output feedback design. Synthesis of observer-based variable structure control for asymptotical stabilization and uniform ultimate boundedness of the closed-loop system is provided. Examples are considered and simulation results are given.

ISSN:0020-7179    

DOI:10.1080/00207179208934227

出版商:Taylor & Francis Group    

年代:1992

数据来源: Taylor

摘要:

Fn the first part of this paper, a general forgetting algorithm is formulated and analysed. It contains most existing forgetting schemes as special cases. Conditions are given ensuring that the basic convergence properties will hold. In the second part of the paper, the results are applied to a specific algorithm with selective forgetting. Here, the forgetting is non-uniform in time and space. The theoretical analysis is supported by a simulation example demonstrating the practical performance of this algorithm.

ISSN:0020-7179    

DOI:10.1080/00207179208934228

出版商:Taylor & Francis Group    

年代:1992

数据来源: Taylor

摘要:

For the Kalman filter-type sampled-data estimation problem utilizing an averaging A/D device, the equivalent discrete-time problem is shown to be of increased order. The fixed-structure optimal projection approach for reduced-order, discrete-time estimation is applied to the equivalent discrete-time problem in order to characterize reduced-order estimators.

ISSN:0020-7179    

DOI:10.1080/00207179208934229

出版商:Taylor & Francis Group    

年代:1992

数据来源: Taylor

摘要:

Most processes of realistic complexity cannot be described by simple linear relationships. An alternative to creating high order/non-linear models is to develop 'composite models’, i.e. a collection of simple models along with rules concerning when to use which one. In this paper we describe a method for constructing such composite models from observed data. It is assumed that the dynamics of the process changes with some 'operating-point vector’, which is assumed to be a measurable quantity. Based on input-output measurements and measurements of the operating-point vector, a composite model is constructed which consists of piecewise linear models. Different regions of the operating point space thus give different linear dynamics. The dynamics as well as the region boundaries are determined from the data. The basic idea is to utilize a method from recursive identification, which is able to track slow as well as rapid dynamic changes. A classification procedure is then applied to the models produced by this identification procedure, and finally borders are created between the different classified models. Techniques for supervised pattern recognition are used for the latter step. The whole construction procedure is illustrated with an example.

ISSN:0020-7179    

DOI:10.1080/00207179208934230

出版商:Taylor & Francis Group    

年代:1992

数据来源: Taylor

摘要:

A model predictive control (MPC) technique is developed for systems with measurements available at different sampling rates. The method uses general state-space system representations that incorporate secondary measurements as well as primary measurements. The optimal multi-rate (MR) filtering method is used to develop prediction equations for MPC. A simple suboptimal cascade filter is also proposed for dual-rate (DR) systems where the primary measurements are available at a 'slow’ rate and the secondary measurements are available at a 'fast’ rate. In addition to significant reduction in filter-gain computation requirements, the suboptimal filtering strategy offers superior primary-measurement-failure tolerance. The applicability of the proposed methods to realistic systems is demonstrated through an example application to a high-purity distillation column.

ISSN:0020-7179    

DOI:10.1080/00207179208934231

出版商:Taylor & Francis Group    

年代:1992

数据来源: Taylor

摘要:

Properties of neural network performance are investigated by studying the modelling of non-linear dynamical systems. Network complexity, node selection, prediction and the effects of noise are studied and some new metrics of performance are introduced. The results are illustrated with both simulated and industrial examples.

ISSN:0020-7179    

DOI:10.1080/00207179208934232

出版商:Taylor & Francis Group    

年代:1992

数据来源: Taylor