Some frequency-domain properties of innovations sequence are studied. As their applications, a frequency-domain method for the identification of statistical parameters in adaptive Kalman filtering is proposed. This me...
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Some frequency-domain properties of innovations sequence are studied. As their applications, a frequency-domain method for the identification of statistical parameters in adaptive Kalman filtering is proposed. This method has clear physical meaning, and by using the weighted least-squares estimation algorithm, the statistical parameters can be identified accurately and robustly. A sufficient condition for the identifiability of model mismatches with arbitrary phase characters in adaptive Kalman filtering is also given, by using the structure of innovations sequence and the theory of higher-order statistics.
In this paper, an adaptive decentralized controller is presented to attenuate the transversal vibration of a flexible cablestayed bridge induced by seismic excitation, in which only local sensor information has been u...
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When the air-gap flux is saturated, the conventional adaptive speed estimator cannot remove the influence of the nonlinear inductance variation. Without speed sensors, it is difficult to identify inductance variation ...
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Embedded systems are computer-based systems which must respond to external stimuli within time scales determined by the external environment. Such systems are required to achieve ever more demanding behavioural. perfo...
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Embedded systems are computer-based systems which must respond to external stimuli within time scales determined by the external environment. Such systems are required to achieve ever more demanding behavioural. performance and safety requirements. Embedded systems are found in applications such as primary flight control, gas-turbine engine control and railway traffic management Often complex embedded systems are distributed, typically to achieve demanding performance or dependability requirements, and must operate within hard real-time constraints. Considerable effort is required to select optimal design solutions and ensure adherence to specified requirements. In embedded systems safety, reliability and response-times are considered as strict constraints on the system design. Achievement of these constraints requires meticulous analysis, typically through the use of specialist modelling and simulation techniques. Integration of knowledge and understanding obtained from disparate detailed models remains a considerable challenge. Ideally, a system which has both continuous dynamics and event-driven parts. would be modelled in one environment, using the most appropriate techniques for each part, and allowing the analysis of the whole system to be carried out simultaneously. The paper presents an integrated approach in order to translate automatically the information manipulated during the different phases of the design: specification. analysis, design and implementation.
in this paper a general algorithm to obtain Robust H ∞ Static Output Feedback controllers is derived. The technique used is based on the transformation of the time-varying uncertainty problem into one without uncerta...
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in this paper a general algorithm to obtain Robust H ∞ Static Output Feedback controllers is derived. The technique used is based on the transformation of the time-varying uncertainty problem into one without uncertainty and then applying the dual-iteration numerical technique of Iwasaki to the problem of determining the optimal parameters for a static H ∞ output feedback controller. To show how the method works, we apply it to a model which contains time-varying structured parameter uncertainty and is subject to external disturbances.
Constrained predictive controller that is based on Youla-Kučera (YK) parametrisation of all stabilising controllers is discussed. The optimised variables are not future control increments as usual but directly paramet...
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Constrained predictive controller that is based on Youla-Kučera (YK) parametrisation of all stabilising controllers is discussed. The optimised variables are not future control increments as usual but directly parameters of the controller. Both finite and infinite horizon formulations are handled.
In this paper, three neural network based d-step-ahead prediction strategies, i.e. a recursive d-step-ahead neural predictor, a non-recursive d-step-ahead neural predictor, and a Smith type neural predictor are presen...
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In this paper, three neural network based d-step-ahead prediction strategies, i.e. a recursive d-step-ahead neural predictor, a non-recursive d-step-ahead neural predictor, and a Smith type neural predictor are presented for time-delay compensation for nonlinear systems. Both the recursive and the non-recursive predictors have been extended to the case of long-range prediction. Finally, the proposed neural network based predictors are applied to the prediction of the manifold pressure process in an automotive engine. The predictive result of the corresponding first principles model based nonlinear predictor is also illustrated for comparison. The experimental results show that the neural network based predictive methods have obtained better performance.
Neural networks and genetic algorithms have been in the past successfully applied, separately, to controller tuning problems. In this paper we purpose to combine its joint use, by exploiting the nonlinear mapping capa...
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Neural networks and genetic algorithms have been in the past successfully applied, separately, to controller tuning problems. In this paper we purpose to combine its joint use, by exploiting the nonlinear mapping capabilities of neural networks to model objective functions, and to use them to supply their values to a genetic algorithm which performs on-line minimization. Simulation results show that this is a valid approach, offering desired properties for on-line use such as a dramatic reduction in computation time and avoiding the need of perturbing the closed-loop operation
Builds on the previous work by the authors (1998) by defining local versions of cross-positivity for vector fields, especially as related to shifted cones. The paper also furthers the development of a stability theory...
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Builds on the previous work by the authors (1998) by defining local versions of cross-positivity for vector fields, especially as related to shifted cones. The paper also furthers the development of a stability theory by introducing preliminary concepts of directed stability. The motivation is to apply this theory to analyzing the control of certain directionally constrained models, such as those found in materials processing.
When an unknown object with Lambertian reflectance is viewed orthographically, there is an implicit ambiguity in determining its 3-d structure: we show that the object's visible surface f(x, y) is indistinguishabl...
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When an unknown object with Lambertian reflectance is viewed orthographically, there is an implicit ambiguity in determining its 3-d structure: we show that the object's visible surface f(x, y) is indistinguishable from a `generalized bas-relief' transformation of the object's geometry, f¯(x, y) = λf(x, y)+μx+vy, and a corresponding transformation on the object's albedo. For each image of the object illuminated by an arbitrary number of distant light sources, there exists an identical image of the transformed object illuminated by similarly transformed light sources. This result holds both for the illuminated regions of the object as well as those in cast and attached shadows. Furthermore, neither small motion of the object, nor of the viewer will resolve the ambiguity in determining the flattening (or scaling) λ of the object's surface. Implications of this ambiguity on structure recovery and shape representation are discussed.
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