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.
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.
This paper reports on work carried out at Colt International, the aim of which is to investigate cold oxidation techniques for pollution controlusing dielectric barrier discharges (DBD). The principle of the DBD has ...
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This paper reports on work carried out at Colt International, the aim of which is to investigate cold oxidation techniques for pollution controlusing dielectric barrier discharges (DBD). The principle of the DBD has been well reported and so only a brief description is given here. The DBD usually comprises two electrodes, at least one of which is covered with a dielectric material. They are separated by an air-gap of a few millimetres through which the influent air stream passes. When a voltage is applied across these electrodes, the gas initially acts as an insulator and the electrodes present a capacitive load to the power supply. As the voltage increases, electrons gain enough energy from the electric field to ionise molecules in the air and produce an avalanche or micro-discharge.
An alternative approach to the generation of realistic confidence bounds is proposed which considers two aspects of the data which are known to influence the resultant prediction error. These are the ability of the ne...
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An alternative approach to the generation of realistic confidence bounds is proposed which considers two aspects of the data which are known to influence the resultant prediction error. These are the ability of the network to predict the output and the impact of the density of the training data on the resultant bounds. Neural network predictions encompassed by confidence bounds provide a more robust and believable representation of the forecast, and provide industries with greater confidence when using such models as software sensors and for monitoring and control. The power of the technique lies in the fact that it is not necessary to identify an underlying distribution which is difficult to satisfy and that it is equally applicable to all forms of network topologies and non-linear modelling procedures. The two techniques are applied to a pilot plant batch methyl methacrylate polymerisation reactor.
The proceedings contains 11 papers from the iee colloquium on applied control techniques using matlab. Topics discussed include: analysis of multivariable Smith predictors;controller design for the idle speed control ...
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The proceedings contains 11 papers from the iee colloquium on applied control techniques using matlab. Topics discussed include: analysis of multivariable Smith predictors;controller design for the idle speed control of an internal combustion engine;design of a discrete linear quadratic optimal missile autopilot;observer design;neural networks;multiobjective control system design;and genetic algorithms.
Provision of reliability of the walking robots is complex problem. Application of soft computing allows to provide the reliability of robots. Soft-computing is new discipline that bring together all features of fuzzy-...
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Provision of reliability of the walking robots is complex problem. Application of soft computing allows to provide the reliability of robots. Soft-computing is new discipline that bring together all features of fuzzy-logic, genetic programming, and neural networks. The main peculiarity of soft-computing is capability to treat with uncertain systems that cannot be easily modelled an controlled by using the classical approaches. The walking robots are typical example of systems affected by uncertainty: leg kinematic is often non-linear and known with low accuracy. Overview of soft-computing techniques developed that have been applied to several walking robots is given.
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.
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 behaviour 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 (Lant et al., 1991; Mitchell et al., 1995). 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.
matlab, SIMULINK and dSPACE control implementation tools are applied to the idle speed control of an internal combustion engine. The different control design techniques under examination include classical, fuzzy, H-in...
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matlab, SIMULINK and dSPACE control implementation tools are applied to the idle speed control of an internal combustion engine. The different control design techniques under examination include classical, fuzzy, H-infinity, predictive and variable structure methods. The controllers are assessed for their transient and steady state performance, sensitivity to load disturbance, robustness, control signal activity and the algorithm size, complexity and execution time.
The matlab Genetic Algorithm Toolbox aims to make genetic algorithms accessible to the control engineer within the framework of an existing computer-aided control system design (CACSD) package. This allows the retenti...
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The matlab Genetic Algorithm Toolbox aims to make genetic algorithms accessible to the control engineer within the framework of an existing computer-aided control system design (CACSD) package. This allows the retention of existing modeling and simulation tools for building objective functions and enables the user to make direct comparisons between genetic methods and traditional procedures.
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