This work is concerned with the validation of reduced-order models which are intended for closed-loop applications. The main objective is to point out some issues arising in the use of such models in closed-loop appli...
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This work is concerned with the validation of reduced-order models which are intended for closed-loop applications. The main objective is to point out some issues arising in the use of such models in closed-loop applications. It is shown that in validating simplified models, special attention should be given to the accuracy of the approximation at crossover frequencies. This observation naturally leads to the conclusion that, in some cases, open-loop model reduction techniques can be successfully used in deriving models intended for closed-loop applications thus avoiding optimal methods which are far more time-consuming. A second objective is to show how a reduced-order model could have varying degrees of accuracy in closed-loop when controller parameters are varied. Numerical examples which use the model of an actual fuel control system are included to illustrate the main points of the paper.< >
The authors present a fuzzified cerebellar model articulation controller (CMAC) network acting as a multivariable adaptive controller featuring self-organizing association cells and the ability for self-learning requi...
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The authors present a fuzzified cerebellar model articulation controller (CMAC) network acting as a multivariable adaptive controller featuring self-organizing association cells and the ability for self-learning required teaching signals in real time. In particular, the original CMAC has been reformulated within a framework of a simplified fuzzy control algorithm, and the associated self-learning algorithms have been developed by incorporating the schemes of competitive learning and iterative learning control into the system. The approach described here can be thought of as either a completely unsupervised fuzzy-neural control strategy or equivalently an automatic real-time knowledge acquisition scheme. The approach has been successfully applied to a problem of multivariable blood pressure control.< >
The paper describes an updated model of iron-ore sintering and discusses results of computer simulation studies of the proces. A number of features are illustrated including the dependence of ignition 0n particle size...
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The paper describes an updated model of iron-ore sintering and discusses results of computer simulation studies of the proces. A number of features are illustrated including the dependence of ignition 0n particle size and the effect on bed temperature of varying the limestone content of the raw mix. The effect of subjecting the surface of the bed to preheated air, rather than cold air, immediately after ignition is investigated. Finally, consideration is given to the use of parallel computing and the results of applying a parallel algorithm to the heat exchange problem are discussed.
Genetic algorithms (GA) are adaptive search techniques, based on the principles of natural genetics and natural selection, which, in controlsystemsengineering, can be used as an optimization tool or as the basis of ...
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Genetic algorithms (GA) are adaptive search techniques, based on the principles of natural genetics and natural selection, which, in controlsystemsengineering, can be used as an optimization tool or as the basis of more general adaptive systems. Following an introduction to the simple GA, important characteristics of GA are identified and control applications are described.< >
A quantitative measure of modal dominance for continuous systems is proposed. This measure takes into account both transient and steady-state information of the system. Consequently the new indices indicate which pole...
A quantitative measure of modal dominance for continuous systems is proposed. This measure takes into account both transient and steady-state information of the system. Consequently the new indices indicate which poles are dominant even when they are not the slowest. Simple formulae are developed for transfer functions and state-space models. Three numerical examples illustrate the main points of the paper.< >
This paper is concerned with introducing a genetic-based algorithm for the minimum-time trajectory planning of articulated robotic manipulators. The planning procedure is performed in the configuration space and respe...
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This paper is concerned with introducing a genetic-based algorithm for the minimum-time trajectory planning of articulated robotic manipulators. The planning procedure is performed in the configuration space and respects all physical constraints imposed on the manipulator design, including the limits on the torque values applied to the motor of each joint of the arm; consequently, the complete nonlinear dynamic robot model is incorporated in the formulation.< >
This paper is concerned with recognition and subsequent tracking of hardness patterns in coal deposita for the purpose of automatic guidance of a mining machine. A framework for the formal presentation of the problem ...
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This paper is concerned with recognition and subsequent tracking of hardness patterns in coal deposita for the purpose of automatic guidance of a mining machine. A framework for the formal presentation of the problem and its sOlution is developed. An enhanced algorithm for determining tactile flow using linear correlation is presented. It has been shown that inclusion of only a single rule knowledge-base could improve the performance of the motion detection significantly. A trajectory learning scheme is suggested for acquiring the coal-seam undulation profile that is gradually matured as the mining progresses
This paper introduce a simple and systematic scheme capable of self-organizing and self-learning the required control knowledge for use with multivariable fuzzy controllers. The starting point of the approach is to st...
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This paper introduce a simple and systematic scheme capable of self-organizing and self-learning the required control knowledge for use with multivariable fuzzy controllers. The starting point of the approach is to structurally map a simplified fuzzy control algorithm (SFCA) into a counterpropagation network (CPN) in such a way that the control knowledge is explicitly represented in the form of connection weights of the nets, the control rule-base is gradually self-constructed with the fulfillment of the prespecified performance requirements, and finally the approximate reasoning is carried out by replacing a winner-take-all competitive scheme with a soft matching cooperative strategy. Two problems of multivariable control of blood pressure and anaesthesia have been studied as demonstration examples.
The paper is concerned with the problem of applying prescribed dynamic forces to a common structure, as in fatigue testing. The work reported investigates the use of self-tuning control in a two-channel force-control ...
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The paper is concerned with the problem of applying prescribed dynamic forces to a common structure, as in fatigue testing. The work reported investigates the use of self-tuning control in a two-channel force-control system acting upon a cantilever beam. An implicit pole-placement algorithm is developed on the basis of a linear model and its application in a nonlinear situation is tested and the results discussed. The effects of choosing different pole locations are investigated, and it is shown that minimum interaction between channels occurs when the poles are equal
Recent research into the mechanisms of evolution and genetics has shown how biological systems have managed to develop some very powerful methods of optimising and adapting themselves to meet new environmental challen...
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Recent research into the mechanisms of evolution and genetics has shown how biological systems have managed to develop some very powerful methods of optimising and adapting themselves to meet new environmental challenges. For applications in controlsystemsengineering, many of the characteristics exhibited by genetic algorithms are particularly appropriate. They can be used as an optimization tool or as the basis of adaptive systems. The versatile and robust qualities of these algorithms are reviewed and their relevance for controlsystems is highlighted. Applications are described and implementation issues are addressed, including parallelization. Prospective future directions are identified
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