This paper describes a computationally efficient nonlinear Model Predictive control (MPC) algorithm in which the neural Hammerstein model is used. The Multiple-Input Multiple-Output (MIMO) dynamic model contains a neu...
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This paper considers on-line training of feadforward neural networks. Training examples are only available sampled randomly from a given generator. What emerges in this setting is the problem of step-sizes, or learnin...
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This paper considers on-line training of feadforward neural networks. Training examples are only available sampled randomly from a given generator. What emerges in this setting is the problem of step-sizes, or learning rates, adaptation. A scheme of determining step-sizes is introduced here that satisfies the following requirements: (i) it does not need any auxiliary problem-dependent parameters, (ii) it does not assume any particular loss function that the training process is intended to minimize, (iii) it makes the learning process stable and efficient. An experimental study with the 2D Gabor function approximation is presented.
A fast global minimization segmentation model based on total variation is presented around Functional modeling and algorithm constructing. Firstly, a new active contour model is developed by maximum a-posterior probab...
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This paper uses 2D control systems theory to develop robust iterative learning control laws for linear plants with experimental validation on a gantry robot used for 'pick and place' operations commonly found ...
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A general (application independent) computer vision framework is proposed. It follows the methodology of knowledge-base systems - dividing a system into knowledge base and control. We choose procedural semantic networ...
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A general (application independent) computer vision framework is proposed. It follows the methodology of knowledge-base systems - dividing a system into knowledge base and control. We choose procedural semantic networks for object-oriented modelling of the world. It is basically a non-monotonic logical system. Several inference rules are proposed that allow to create instances of model concepts. In order to activate an inference rule a model-to-image data matching process need to be performed. We view this matching as a solution to constraint satisfaction problem (CSP), supported by Bayesian net-based evaluation of partial variable assignments. A modified incremental search for CSP is designed that allows partial solutions and calls for stochastic inference in order to provide judgments of partial states. Hence the detection of partial occlusion of objects is handled consistently with Bayesian inference over evidence and hidden variables.
The paper focuses on the FraDIA vision subsystem part responsible for GPU-based image processing. The developed set of classes encapsulates the OpenCL subroutines and utilizes GPU to fulfill the robotic requirements f...
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The paper focuses on the FraDIA vision subsystem part responsible for GPU-based image processing. The developed set of classes encapsulates the OpenCL subroutines and utilizes GPU to fulfill the robotic requirements for real-time visual data processing. The class structure reflects the proposed classification of image processing algorithms.
The paper describes the design and performance of a novel technique that can be used to calculate the geographic locations of nodes that form wireless sensor network system (WSN). Location awareness is required for ma...
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Cogeneration is currently one of the cheapest ways to generate electricity. The European Union promotes systems for combined heat and power generation. In Europe in general - and Poland in particular - there are numer...
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ISBN:
(纸本)9781439834152
Cogeneration is currently one of the cheapest ways to generate electricity. The European Union promotes systems for combined heat and power generation. In Europe in general - and Poland in particular - there are numerous large district heating systems powered by CHP plants. Most plants are equipped with back-pressure turbines. Energy conversion efficiency for this class of installations reaches approximately 80%. The main disadvantage of cogeneration is that electricity production is directly related to heat production (i.e. demand). The load curve of the heating system varies depending on the time of day, day of the week, and season. On the daily scale the largest heat demand is observed at night and smallest during the day. In contrast, electricity demand is lowest at night and highest during the day, with two standard peaks in the morning and afternoon. Accordingly, electricity is at its most expensive at that time. Therefore it is beneficial to maximise electricity generation during the morning and afternoon peaks, and minimise it during the decreased night-time demand. Electricity and heat outputs at a CHP plant can be uncoupled by using a heat accumulator. This study proposes a mathematical model to plan out a large CHP plant with a heat storage tank to be used for the purposes of operational optimization. Potential increases in profits from electricity sales enabled by the heat accumulator are also quantified.
In this paper, an active FTC strategy is proposed. First, it is developed in the context of linear systems and then it is extended to Lipschitz non-linear systems. The key contribution of the proposed approach is an i...
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In this paper, an active FTC strategy is proposed. First, it is developed in the context of linear systems and then it is extended to Lipschitz non-linear systems. The key contribution of the proposed approach is an integrated FTC design procedure of the fault identification and fault-tolerant control schemes. Fault identification is based on the use of an observer. While, the FTC controller is implemented as a state feedback controller. This controller is designed such that it can stabilize the faulty plant using Lyapunov theory and LMIs. Finally, the last part of the paper shows experimental results that confirm the high performance of the proposed approach.
An efficient fuzzy predictive control algorithm based on Hammerstein models is proposed in the paper. The algorithm uses the DMC (Dynamic Matrix control) technique and a Hammerstein model, in which fuzzy static block ...
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