The success of blood glucose automatic regulation depends on the robustness of the control algorithm used. It is a difficult task to perform due to the complexity of the glucose-insulin regulation system. The variety ...
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ISBN:
(纸本)9781424441211
The success of blood glucose automatic regulation depends on the robustness of the control algorithm used. It is a difficult task to perform due to the complexity of the glucose-insulin regulation system. The variety of model existing reflects the great amount of phenomena involved in the process, and the inter-patient variability of the parameters represent another challenge. In this research a High-Order Sliding-Mode control is proposed. It is applied to two well known models, Bergman Minimal Model, and Sorensen Model, to test its robustness with respect to uncertain dynamics, and patients' parameter variability. The controller designed based on the simulations is tested with the specific Bergman Minimal Model of a diabetic patient whose parameters were identified from an in vivo assay. To minimize the insulin infusion rate, and avoid the hypoglycemia risk, the glucose target is a dynamical profile.
A passive universal image steganalysis method is proposed that is shown to be of higher detection accuracy than existing truly blind steganalysis methods including Farid's and the WAM. This is achieved by improvin...
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A passive universal image steganalysis method is proposed that is shown to be of higher detection accuracy than existing truly blind steganalysis methods including Farid's and the WAM. This is achieved by improving some weaknesses of Farid's steganalysis scheme in feature extraction, that is, instead of deriving an over-determined equation system for each sub band of the wavelet decomposition, the sub bands are divided into overlapping blocks and an over-determined equation system is constructed for each block. To guarantee the existence of finite answers, the over-determined equation systems are solved in a way different from Farid's by using Moore-Penrose pseudo-inverse concept. Further improvement to the performance is achieved by adding diagonal directions and increasing the number of moments. The comparative evaluations confirm the superiority of the proposed method over prevalent blind steganalysis schemes.
Assembly and disassembly processes are similar from the viewpoint of automation. Assembly process is more or less a “classical” subject; disassembly process is more a quite new field. Flexible system are very import...
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Assembly and disassembly processes are similar from the viewpoint of automation. Assembly process is more or less a “classical” subject; disassembly process is more a quite new field. Flexible system are very important issue in the current industry when disassembling and recycling tasks have to be performed. These tasks can be performed by a human operator or by a robot system. In this paper an autonomous robot with manipulator system perform the required task for different operation. This system takes into consideration the necessary task to perform the disassembly of a component using robots synchronization with flexible line process. The proposed algorithm is to distribute the task among the robot and flexible line and takes into consideration the characteristics of each sequence that needs to be followed to perform the required disassembly of the product. The proposed system is validated by experiments using several types of components.
In a traditional anti-windup design, the anti-windup mechanism is set to be activated as soon as the control signal saturates the actuator. A recent innovation of delaying the activation of the anti-windup mechanism, ...
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This paper presents a reinforcement learning algorithm and provides conditions for global convergence to Nash equilibria. For several reinforcement learning schemes, including the ones proposed here, excluding converg...
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ISBN:
(纸本)9781612848006
This paper presents a reinforcement learning algorithm and provides conditions for global convergence to Nash equilibria. For several reinforcement learning schemes, including the ones proposed here, excluding convergence to action profiles which are not Nash equilibria may not be trivial, unless the step-size sequence is appropriately tailored to the specifics of the game. In this paper, we sidestep these issues by introducing a new class of reinforcement learning schemes where the strategy of each agent is perturbed by a state-dependent perturbation function. Contrary to prior work on equilibrium selection in games, where perturbation functions are globally state dependent, the perturbation function here is assumed to be local, i.e., it only depends on the strategy of each agent. We provide conditions under which the strategies of the agents will converge to an arbitrarily small neighborhood of the set of Nash equilibria almost surely. We further specialize the results to a class of potential games.
This project was inspired by the idea of the connection of amusement and useful thing respectively the movement by the playing games, because as is known global problem of the Word is increasing obesity caused by the ...
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This project was inspired by the idea of the connection of amusement and useful thing respectively the movement by the playing games, because as is known global problem of the Word is increasing obesity caused by the addiction on the PC games at the young people. This project connects pleasurable with useful, respectively playing of the game with physical effort. By the help of the accelerometer is possible to handle by simple games to whose operating is needed physical impulsion of the player. After it would be possible to take up on this project by the beat measurement of the player in order to check on effectivity of the suggested system. Software was programmed in background C#.
In this paper, we study marginal problems for a class of binary pairwise Gibbs random fields (BPW-GRFs). Given a BPW-GRF associated with a family of binary positive pairwise potentials, finding the exact marginal for ...
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In this paper, we study marginal problems for a class of binary pairwise Gibbs random fields (BPW-GRFs). Given a BPW-GRF associated with a family of binary positive pairwise potentials, finding the exact marginal for each random variable is typically an NP-hard problem. In this paper, we develop upper and lower bounds of the true marginals in BPW-GRFs. Our bounds can be easily computed via an iteration on appropriate trees that are constructed from the corresponding BPW-GRF graphs. We prove that these marginal bounds outperform existing bounds. We also show via simulations that this improvement is significant on graphs with weak potentials.
In this paper, we discuss in time domain the convergence of the iterative process for fractional-order nonlinear systems. The PD~(alpha)-type iterative learning updating laws are considered. Most of the classical frac...
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In this paper, we discuss in time domain the convergence of the iterative process for fractional-order nonlinear systems. The PD~(alpha)-type iterative learning updating laws are considered. Most of the classical fractional-order cases for linear or nonlinear systems fall into the scheme of this paper. A number of numerical simulations are illustrated to validate the concepts.
The Discrete Cosine Transform (DCT) is one of the most widely used techniques for image compression. Several algorithms are proposed to implement the DCT-2D. The scaled SDCT algorithm is an optimization of the DCT-1D,...
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The Discrete Cosine Transform (DCT) is one of the most widely used techniques for image compression. Several algorithms are proposed to implement the DCT-2D. The scaled SDCT algorithm is an optimization of the DCT-1D, which consists in gathering all the multiplications at the end. In this paper, in addition to the hardware implementation on an FPGA, an extended optimization has been performed by merging the multiplications in the quantization block without having an impact on the image quality. Tests using MATLAB environment have shown that our proposed approach produces images with quality comparable to the ones obtained using the JPEG standard. FPGA-based implementations of this proposed approach and the Loeffler's algorithm are proposed and compared in this paper using an Altera Startix FPGA family with the synthesis and implementation tool Quartus II. Results show that our approach outperforms the well known Loeffler's algorithm in terms of processing-speed and resources used.
Permanent magnet synchronous motors (PMSMs) produce a parasitic oscillating torque due to several reasons. This contribution cancels the oscillating torque with adaptive control algorithms. Therefore a mathematical mo...
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Permanent magnet synchronous motors (PMSMs) produce a parasitic oscillating torque due to several reasons. This contribution cancels the oscillating torque with adaptive control algorithms. Therefore a mathematical model of the PMSM is necessary. A model with nonlinear dynamics and a Fourier approach for the ripples is used as a mathematical description. Through comparisons between measured data and simulated data it is shown that the model assumptions are valid. The adaptive algorithm is implemented as an add-on controller to the already existing control system which consists of a feedforward part and a basis controller. The challenge is that the closed loop system has a resonant frequency and the algorithm should have the same performance for all frequencies. Experimental results show the performance and convergence of the adaptive algorithm at constant and non constant velocity.
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