This paper provides a brief introduction to model based statistical change detection. It introduces the concepts of residual generation and statistical evaluation. The power of this approach is then illustrated using ...
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This paper provides a brief introduction to model based statistical change detection. It introduces the concepts of residual generation and statistical evaluation. The power of this approach is then illustrated using two automotive applications: suspension monitoring and engine misfire detection. The difference in the characteristics of these applications indicates that these techniques can be used more widely in automotive monitoring/diagnostic systems.
The problem of robust model-based diagnosis of faults is addressed with application to a three-tank system. The present approach is based on artificial neural networks used as predictors of dynamic nonlinear models fo...
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The problem of robust model-based diagnosis of faults is addressed with application to a three-tank system. The present approach is based on artificial neural networks used as predictors of dynamic nonlinear models for residual generation, and as pattern classifiers for residual evaluation. A diagnosing subsystem is implemented in real-time using the Simulink/Matlab environment.
This paper presents a set of realistic simulations conducted to demonstrate the applicability of the partial state reference model (PSRM) control approach to automotive control. Particular emphasis is put on those eng...
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This paper presents a set of realistic simulations conducted to demonstrate the applicability of the partial state reference model (PSRM) control approach to automotive control. Particular emphasis is put on those engineering design features as the tracking capability and the stability robustness and performances in the presence of state disturbance and modelling errors.
There is a strong desire for the controlsystems design community and the electronic design community to leverage off each other's accomplishments in the area of modeling and simulation. In the past this has been ...
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There is a strong desire for the controlsystems design community and the electronic design community to leverage off each other's accomplishments in the area of modeling and simulation. In the past this has been impeded by the fact that they use different modeling languages and simulators, With the development of analog hardware description languages (AHDLs), which combine both discrete-time and continuous-time modeling and simulation capabilities, we are close to realizing this goal of a common modeling language. This paper investigates the modeling requirements associated with systemdesign in an effort to illustrate capabilities desirable in a unified modeling language. It then provides an overview of the VHDL-A a candidate for unified modeling special session to place things into perspective. The combined package introduces VHDL-A (the language bring developed under ieee DASC 1076.1) and discusses its suitability as a unified modeling language for controlsystemdesign.
We discuss the numerical solution of the output feedback optimal periodic control problem by using a gradient search based optimization approach. For the evaluation of the cost function and its gradient explicit expre...
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We discuss the numerical solution of the output feedback optimal periodic control problem by using a gradient search based optimization approach. For the evaluation of the cost function and its gradient explicit expressions are derived which involve the numerical solution of a pair of discrete-time periodic Lyapunov equations. Efficient numerically reliable algorithms based on the periodic Schur decomposition are proposed for the solution of these equations. The proposed algorithms are extensions of the methods proposed for standard systems. An example is given to illustrate the effectiveness of the presented approach.
This paper presents a new toolbox for robust controldesign and analysis. A drawback of physically motivated approaches to robust control has been the amount of extensive calculation required for various methods, e.g....
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This paper presents a new toolbox for robust controldesign and analysis. A drawback of physically motivated approaches to robust control has been the amount of extensive calculation required for various methods, e.g. parameter space approach. This new toolbox overcomes these problems and makes parametric robust control methods available in an efficient, easy comprehensible, and flexible manner. The toolbox uses Matlab/Simulink which is a well-know tool to most control engineers.
A fundamental limitation in achieving high performance control for multivariable plants is associated with the uncertainty in the modelling of the plant. Previous measures of robust stability uncertainty have typicall...
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A fundamental limitation in achieving high performance control for multivariable plants is associated with the uncertainty in the modelling of the plant. Previous measures of robust stability uncertainty have typically been based on complex plant perturbations, which often lead to excessively conservative controller design. It is the purpose of this paper to propose a nonconservative measure of plant model uncertainty; this is done by utilizing results obtained on the real stability radius problem. A CAD approach to synthesize controllers for a plant which has a specified degree of plant model uncertainty is then proposed. Some application studies of the procedure are included.
Development of a CAD of controlsystems which realizes coordination of modeling of plant and design of controller is introduced. It enables us to do not only analysis of controlsystems and design of controllers but a...
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Development of a CAD of controlsystems which realizes coordination of modeling of plant and design of controller is introduced. It enables us to do not only analysis of controlsystems and design of controllers but also online modeling of plants in the same environment. By utilizing this software, the control engineer is able to repeat the procedure of design of controlsystems efficiently to archive the best performance, which depends on the controller as well as the model of the plant. It is also shown how to improve the speed of computation by introducing the technique of memory management for real time control and how to change the parameters of the controller without stopping real time control.
A nonlinear PI controller is developed from a low-order nonlinear empirical process model. Implementation issues such as model parameter identification and open-loop stability are discussed. The procedure for construc...
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A nonlinear PI controller is developed from a low-order nonlinear empirical process model. Implementation issues such as model parameter identification and open-loop stability are discussed. The procedure for constructing effective controllers (including a simple model identification procedure) is illustrated with an example process of industrial significance.
The purpose of this paper is to give an overview of recent developments in algorithms and software for linear matrix inequality (LMI) problems. We review the definition and some basic properties of the semidefinite pr...
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The purpose of this paper is to give an overview of recent developments in algorithms and software for linear matrix inequality (LMI) problems. We review the definition and some basic properties of the semidefinite programming (SDP) problem, and describe recent developments in interior point algorithms and available software. We conclude with some extensions of the SDP.
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