A generic supervisory systems architecture is presented for control of two different types of systems;medical systems and industrial systems. It is structured in a hierarchical manner, consisting of a basic-level fuzz...
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A generic supervisory systems architecture is presented for control of two different types of systems;medical systems and industrial systems. It is structured in a hierarchical manner, consisting of a basic-level fuzzy logic controller supervised by a higher level decision-maker, which employs fuzzy logic theory to represent the human expertise used in supervising the plant including both the controller and the process. The supervisory level tasks consist of tuning, generating control rules, fault detection and diagnosis, together with an alarm and monitoring system. The paper is concerned more with the fault detection and diagnosis methods incorporated in the system. Simulation results for a medical system application are presented.
Phase shift is very important in the frequency response analysis of non-linear systems and in this paper the phase response function is analysed and interpreted to provide a clear understanding of phase. Non-linear sy...
Phase shift is very important in the frequency response analysis of non-linear systems and in this paper the phase response function is analysed and interpreted to provide a clear understanding of phase. Non-linear systems which include delay elements are also discussed and simulations of both continuous and discrete time non-linear systems are included to demonstrate the concepts involved.
A general structure detection and parameter estimation algorithm is derived for the identification of nonlinear systems that can be approximated by a stochastic nonlinear rational model defined as the ratio of two pol...
A general structure detection and parameter estimation algorithm is derived for the identification of nonlinear systems that can be approximated by a stochastic nonlinear rational model defined as the ratio of two polynomial expansions of past inputs, outputs and noise sequences. The algorithm includes an intelligent structure detection module that learns the structure of the model from the input/output data. Simulation results are included to illustrate the application of the new algorithm.
New higher order correlation tests which use model residuals combined with system inputs and outputs are presented to check the validity of a general class of nonlinear models. The new method is illustrated by testing...
New higher order correlation tests which use model residuals combined with system inputs and outputs are presented to check the validity of a general class of nonlinear models. The new method is illustrated by testing both simple and complex nonlinear system models.
Computer-aided design of controlsystems via multi-objective optimisation is a computationally demanding task that may benefit from parallel processing techniques. In this paper, we report on a new parallel processing...
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Computer-aided design of controlsystems via multi-objective optimisation is a computationally demanding task that may benefit from parallel processing techniques. In this paper, we report on a new parallel processing gateway that supports the use of parallel processing within the framework of an existing computer-aided control system design software package. In many control system design exercises which employ optimisation, the bulk of the computational effort is devoted to the evaluation of the objectives of the optimisation at each iteration. This paper demonstrates, with an example, how, using the gateway, parallel processing can be used within the framework of existing computer-aided control system design tools to compute these objective values.
The paper describes an extension to a standard, block-structured, interactive simulation language in which colours are used to indicate the levels of variables in the simulated process. A coding system is used to clas...
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The paper describes an extension to a standard, block-structured, interactive simulation language in which colours are used to indicate the levels of variables in the simulated process. A coding system is used to classify the level of simulated process variables into three regions of safe, unsafe and dangerous operation, represented by green, yellow and red colours respectively. The enhanced simulation package facilitates controller development for industrial plant and avoids dangerous levels being overlooked in the simulation of prototype systems prior to their implementation on plant. The use of enhanced facility is demonstrated by simulation of the electrode drive system and controller for an electric arc furnace.
One of the objectives of this paper is to describe some of the available techniques and tools which are believed to be particularly useful in practical problems of model approximation. The issues and methods described...
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One of the objectives of this paper is to describe some of the available techniques and tools which are believed to be particularly useful in practical problems of model approximation. The issues and methods described are grouped under the following headings: (i) order-reduction algorithms, (ii) dominant pole selection, (iii) quality indices, (iv) open- and closed-loop optimization procedures, and (v) model validation. Another objective is to show that model approximation techniques can also be used in quite an effective way in the analysis and synthesis of controlsystems. It is shown, by way of examples, how the techniques and tools described in the first part of the paper may be used not only to compute reliable simplified models but also to obtain qualitative and quantitative information regarding the original system. In addition. an example is provided which illustrates how some of the tools and methods can be easily used in the design of reduced-order controllers. Examples taken from the models of a power system arid a thermal power station are provided to illustrate the main points of the paper.
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