This paper develops a class of iterative learning control (ILC) laws for a subclass of uncertain spatially interconnected systems. Model uncertainties appear both in the state and the output equation of the dynamics m...
This paper develops a class of iterative learning control (ILC) laws for a subclass of uncertain spatially interconnected systems. Model uncertainties appear both in the state and the output equation of the dynamics modeled in the 2D systems setting to which existing results are not applicable. The first stage is to write the dynamics in 2D model form. Then the stability theory for a distinct class of 2D systems known as repetitive processes is used to develop the ILC law in the case of differential dynamics. This analysis results in a design algorithm that can be applied using linear matrix inequalities.
In this paper we present a generalization of Yamamoto’s theorem relating eigenvalue moduli and singular values of a matrix. In our generalization a single matrix is replaced by a bounded set of matrices. The main res...
In this paper we present a generalization of Yamamoto’s theorem relating eigenvalue moduli and singular values of a matrix. In our generalization a single matrix is replaced by a bounded set of matrices. The main result of the paper includes also, as a special case, the equality between generalized spectral radius and joint spectral radius.
作者:
Maciej NiedzwieckiAdam SobocinskiFaculty of Electronics
Telecommunications and Computer Science Department of Automatic Control Gdansk University of Technology Narutowicza 11/12 Gdansk Poland Tel: + 48 58 3472519 Fax: +48 58 3416132 e-mail: maciekn@eti.pg.gda.pl adsob@eti.pg.
Generalized adaptive notch filters are used for identification/ tracking of quasi-periodically varying dynamic systems and can be considered an extension, to the system case, of classical adaptive notch filters. Belon...
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Generalized adaptive notch filters are used for identification/ tracking of quasi-periodically varying dynamic systems and can be considered an extension, to the system case, of classical adaptive notch filters. Belonging to the class of causal adaptive filters, the generalized adaptive notch filtering algorithms yield biased frequency estimates. We show that this bias can be removed, or at least substantially reduced. The only price paid for the resulting improvement of the filter’s tracking performance is in terms of a decision delay, which must be incorporated in the adaptive loop. Since decision delay is acceptable in many practical applications, the proposed bias/delay trade-off is an attractive alternative to the classical bias/variance compromise.
The neural correlates of face individuation – the acquisition of memory representations for novel faces – have been studied only in coarse detail and disregarding individual differences between learners. In their se...
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The optimization of crop harvesting processes for commonly cultivated crops is of great importance in the aim of agricultural industrialization. Nowadays, the utilization of machine vision has enabled the automated id...
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ISBN:
(数字)9798350340266
ISBN:
(纸本)9798350340273
The optimization of crop harvesting processes for commonly cultivated crops is of great importance in the aim of agricultural industrialization. Nowadays, the utilization of machine vision has enabled the automated identification of crops, leading to the enhancement of harvesting efficiency, but challenges still exist. This study presents a new framework that combines two separate architectures of Convolutional Neural Networks (CNNs) in order to simultaneously accomplish the tasks of crop detection and harvesting (robotic manipulation) inside a simulated environment. Crop images in the simulated environment are subjected to random rotations, cropping, brightness, and contrast adjustments to create augmented images for dataset generation. The You Only Look Once(YOLO) algorithmic framework is employed with traditional Rectangular Bounding Boxes (R-Bbox) for crop localization. The proposed method subsequently utilises the acquired image data via a visual geometry group model in order to reveal the grasping positions for the robotic manipulation.
The article presents the material type from which the conductors of the overhead power lines are produced influences on the size of the overhang and the tension. The aim of the calculations was to present the benefits...
The article presents the material type from which the conductors of the overhead power lines are produced influences on the size of the overhang and the tension. The aim of the calculations was to present the benefits of the mechanics of the cable resulting from the type of cable used. The analysis was performed for two types of cables: aluminium with steel core and aluminium with composite core, twice span power line section. 10 different conductor-to-strand coil, wind, icing, and temperature variations were included in the calculations. The string description was made by means of a chain curve, while the horizontal component H of the tension force was determined using the bisection method. The loads were collected in accordance with applicable Eurocode.
A concept of the porous core electromagnet is studied. The form for the electromagnet core was printed using 3D technique. The core was manufactured manually using iron filings and cured in room temperature and air pr...
A concept of the porous core electromagnet is studied. The form for the electromagnet core was printed using 3D technique. The core was manufactured manually using iron filings and cured in room temperature and air pressure. The aim of this paper is to deliver initial analysis of the proposed powder core together with the modelling procedure by the using finite element method, and to compare the experimental results of the manually manufactured electromagnet. The material property of the numerical model was adjusted to fit the experimental results. Finally, the electromagnet was tested in the levitation real–time experiment.
Gas sensors are extensively employed for monitoring and detection of hazardous gases and vapors. Many of them are produced on rigid substrates, but flexible and wearable gas sensors are needed for intriguing usage inc...
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A repetitive process makes a series of sweeps or passes through dynamics defined on a finite duration termed the pass length. The process output is termed the pass profile and when each pass is completed, resetting to...
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ISBN:
(纸本)9781612848006
A repetitive process makes a series of sweeps or passes through dynamics defined on a finite duration termed the pass length. The process output is termed the pass profile and when each pass is completed, resetting to the starting location ready for the start of the next one. On any pass the previous pass profile acts as a forcing function on, and hence contributes to, the dynamics of the next one. There has been a considerable volume of profitable work on the development of a control theory for these processes with more recent focus on the design of control laws. The novel contribution of this paper is a new design algorithm which makes more use of available previous pass profile information and reduces the conservativeness present in existing alternatives.
In this study, brain, and gait dynamic information were combined and used for diagnosis and monitoring of Parkinson's disease (the most important Neurodegenerative Disorder). Analysis of the information correspond...
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In this study, brain, and gait dynamic information were combined and used for diagnosis and monitoring of Parkinson's disease (the most important Neurodegenerative Disorder). Analysis of the information corresponding to a prescribed movement involving tremor, and the related changes in brain connectivity is novel and original. Analytically, developing a space-time nonlinear adaptive system which fuses brain and gait information algorithmically is proposed here for the first time. The overall dynamic system will be constrained by the clinical impressions of the patient symptoms embedded in a knowledge-based system. The entire complex constrained problem were solved to enable a powerful model for recognition and monitoring of Parkinson's disease and establishing appropriate rules for its clinical following up.
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