The paper investigates in detail certain aspects of the "System V" powertrain development stages: the use of an engine model to establish the robust performance of the candidate systems in the presence of re...
The paper investigates in detail certain aspects of the "System V" powertrain development stages: the use of an engine model to establish the robust performance of the candidate systems in the presence of real world uncertainties; and the use of a robust modern control technique as a candidate solution to the problem of idle speed control. Structured design and analysis techniques have an essential role in understanding complex powertrain systems. matlab design tools provide insight and the potential to improve system performance.
The paper presents a review of matlab/Simulink-based techniques used in the development of fault models of signalling railway systems. The data used to develop the models was derived, both in normal and fault modes, f...
The paper presents a review of matlab/Simulink-based techniques used in the development of fault models of signalling railway systems. The data used to develop the models was derived, both in normal and fault modes, from operational railway monitoring equipment using four data signals to characterise the electrical and mechanical behaviour of a points mechanism. The main objective of the work was to regenerate three of the data signals from a single monitored signal, thus reducing the number of sensors required to identify and predict a system failure. matlab/Simulink based static curve fitting and dynamic system identification techniques were applied to regenerate the data, and in each case the robustness and accuracy of the fault model are discussed. Finally, the signal regeneration is demonstrated using a Simulink model combining dynamic and linear models.
The decision whether to accept or refuse a new connection into an ATM network, while preserving the cell loss requirements of the existing sources and the new source, is the task of Connection Admission control (CAC)....
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The decision whether to accept or refuse a new connection into an ATM network, while preserving the cell loss requirements of the existing sources and the new source, is the task of Connection Admission control (CAC). To make this decision, CAC must have some knowledge of the bandwidth requirements for the new source. The statistical behaviour of several sources of different types multiplexed on an ATM link is often difficult to predict;stochastic theory cannot be used to describe all the multiplexing effects and, where it can be applied, it may result in excessively long computation times. This paper describes an approach for CAC that uses fuzzy logic techniques and a method for learning the behaviour of the traffic in an ATM link. The learning process is performed by collecting, at specific times, examples of information on the current traffic pattern in the system. using fuzzy reasoning, the system will then infer, from the knowledge extracted from the examples, a value for the bandwidth required for the new source, when the source is operating within the current traffic pattern. An investigation is made of how the system deals with traffic generated by on-off sources, each of them with the same peak and mean: the results focus on the statistical multiplexing gain and cell loss. The results indicate that the statistical multiplexing gain increases for small mean to peak ratios (high burstiness).
A trend towards the integration of systems in high-technology industry is noted. The authors describe integrated control systems based on modern robust controltechniques. They have been applied sucessfully in the aer...
A trend towards the integration of systems in high-technology industry is noted. The authors describe integrated control systems based on modern robust controltechniques. They have been applied sucessfully in the aerospace industry, and it is argued that they can readily be applied to the problem of integrated optimal control system design in the automotive industry. 2 approaches are considered, one centralised and one decentralised.
Fuzzy modelling techniques have been applied to the simulated control of the air/fuel ratio. The method enables the identification of structured nonlinear models, due to the existence of the G and H matrices, that cou...
Fuzzy modelling techniques have been applied to the simulated control of the air/fuel ratio. The method enables the identification of structured nonlinear models, due to the existence of the G and H matrices, that could be readily adapted online. The model used within the control scheme has been selected using the Young information criteria, which is used to assess its appropriateness, normally linear models, for control. The performance of the model, as part of the combined feedforward/feedback controller, appears satisfactory. When the nonlinear and time varying nature of the automotive engine system is considered, the fuzzy modelling methods are considered to offer some potential for engine control applications.
This paper compares the results of four robust multivariable design techniquesapplied to the depth control of a nonlinear Remotely Operated Vehicle (ROV) subjected to parameter perturbations. Three nonlinear control ...
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This paper compares the results of four robust multivariable design techniquesapplied to the depth control of a nonlinear Remotely Operated Vehicle (ROV) subjected to parameter perturbations. Three nonlinear controltechniques, namely, input-output(i/o) linearization control, input-output linearization control with sliding mode control and input-output linearization control with adaptive fuzzy control are studied. The fourth technique is the H/sub infinity / loop shaping design procedure using multiobjective optimization for the simultaneous design of robust stability and performance.< >
The CEGB has devised a distributed computer installation consisting of a host machine and three target machines. One target controls five real and simulated plant systems via a suitable interface. The five plants have...
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The CEGB has devised a distributed computer installation consisting of a host machine and three target machines. One target controls five real and simulated plant systems via a suitable interface. The five plants have been selected to demonstrate different aspects of control such as three-element, cascade and ratio. The plant was designed as scaled down versions of boiler drums, temperature controllers, pressure systems, etc., and has been constructed as working engineering systems using hardware such as motors, valves, water tanks and pipework. Each physical plant system may be controlled by a target computer running CUTLASS software schemes. In order to give more of the CEGB trainee engineers hands on experience of real-time controlusing CUTLASS, the development of a low cost version of the power plant simulator was proposed. The low cost simulator is able to simulate any of the original sections of plant, or several sections simultaneously by using a dedicated microprocessor.< >
The problem of quality control of radiological systems is discussed in relation to the management and quantitative tools normally applied to it. An alternative approach is to consider the problem in terms of a control...
The problem of quality control of radiological systems is discussed in relation to the management and quantitative tools normally applied to it. An alternative approach is to consider the problem in terms of a control loop in which the sets of quality control measurements are compared with their previous values in the context of a numerical model of the system to produce quantitative corrections. A preliminary study of the method applied to mammographic quality control is discussed. By modelling the system with an appropriate set of simultaneous linear equations relating changes in the controlled parameters to the quality control measurements obtained, it is possible to identify quantitative changes in the controlled parameters from measured quality control data using the inverse of the model in matrix form. This method essentially encapsulates knowledge about the system in the form of the linear model. This is distinct from current work attempting to apply artificial intelligence knowledge-based techniques to the problem.
Despite the successful application of advanced predictive control algorithms to many industrial chemical processes satisfactory system performance cannot always be guaranteed. This is often the case where the infreque...
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Despite the successful application of advanced predictive control algorithms to many industrial chemical processes satisfactory system performance cannot always be guaranteed. This is often the case where the infrequent measurement of key process outputs is unavoidable due to sampling limitations. In such situations the ability to detect deviations from desired process behavior is significantly impaired. Inferential estimation techniques employ more easily measured secondary variables to infer the desired primary variable. This facilitates the early detection of disturbances thus improved control performance is to be expected. An adaptive inferential measurement algorithm has been successfully applied to various industrial processes. This contribution discusses the development of a model based control strategy using the inferential estimation algorithm as a basis. The theoretical development of the adaptive inferential long range predictive control algorithm is outlined. The algorithm offers enhanced control performance when compared to existing model based design strategies.
Summary form only given. This paper reports on developments in simulation technologies to support the formal language LOTOS and experience using these techniques in the communications field. LOTOS simulation is curren...
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Summary form only given. This paper reports on developments in simulation technologies to support the formal language LOTOS and experience using these techniques in the communications field. LOTOS simulation is currently applied to effect quality control through a large part of the development lifecycle. Its first application is in interaction with the non specialist user who needs to understand a formal specification as a customer. This class of use extends to the LOTOS user who will often use simulation as a tool for specification development. The capability to execute specifications also means that they can be tested using much of the theory and practice of software testing. Used in this way simulation provides a flexible and powerful framework for quality control which can exploit much of industries existing expertise and investment in testing technologies.< >
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