The model based realizability loss part of the sensitivity function in a generic two-degree of freedom (TDOF) control system has an important role in shaping the deviation between our design goal and the nominal close...
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ISBN:
(纸本)9780889867116
The model based realizability loss part of the sensitivity function in a generic two-degree of freedom (TDOF) control system has an important role in shaping the deviation between our design goal and the nominal closed-loop properties. The paper investigates the optimality of this loss using infinite norm spaces.
The use of decoy states in quantum key distribution (QKD) has provided a method for substantially increasing the secret key rate and distance that can be covered by QKD protocols with practical signals. The security a...
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The use of decoy states in quantum key distribution (QKD) has provided a method for substantially increasing the secret key rate and distance that can be covered by QKD protocols with practical signals. The security analysis of these schemes, however, leaves open the possibility that the development of better proof techniques or better classical postprocessing methods might further improve their performance in realistic scenarios. In this paper, we derive upper bounds on the secure key rate for decoy-state QKD. These bounds are based basically only on the classical correlations established by the legitimate users during the quantum communication phase of the protocol. The only assumption about the possible postprocessing methods is that double click events are randomly assigned to single click events. Further, we consider only secure key rates based on the uncalibrated device scenario which assigns imperfections such as detection inefficiency to the eavesdropper. Our analysis relies on two preconditions for secure two-way and one-way QKD. The legitimate users need to prove that there exists no separable state (in the case of two-way QKD) or that there exists no quantum state having a symmetric extension (one-way QKD) that is compatible with the available measurements results. Both criteria have been previously applied to evaluate single-photon implementations of QKD. Here we use them to investigate a realistic source of weak coherent pulses. The resulting upper bounds can be formulated as a convex optimization problem known as a semidefinite program which can be efficiently solved. For the standard four-state QKD protocol, they are quite close to known lower bounds, thus showing that there are clear limits to the further improvement of classical postprocessing techniques in decoy-state QKD.
The sensitivity function in a generic two-degree of freedom ( TDOF ) control system can be decomposed into three major parts: design-, realizability- and modeling-loss. The paper investigates the optimality of the sec...
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The sensitivity function in a generic two-degree of freedom ( TDOF ) control system can be decomposed into three major parts: design-, realizability- and modeling-loss. The paper investigates the optimality of the second term in infinite norm spaces and proposes a new iterative algorithm for the solution.
The sensitivity function can be decomposed into three major parts: design-, realizability- and modeling-loss. The paper investigates the optimality of the second term in infinite norm spaces and proposes a new iterati...
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The sensitivity function can be decomposed into three major parts: design-, realizability- and modeling-loss. The paper investigates the optimality of the second term in infinite norm spaces and proposes a new iterative algorithm for the solution.
Multispectral bioluminescence tomography (BLT) attracts increasing more attention in the area of small animal studies because multispectral data acquisition could help in the 3D location of bioluminescent sources. Gen...
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This paper presents the results of the parameter estimation procedure for the primary circuit dynamics of a VVER-type nuclear power plant. The model structure is a low dimensional lumped nonlinear model published prev...
This paper presents the results of the parameter estimation procedure for the primary circuit dynamics of a VVER-type nuclear power plant. The model structure is a low dimensional lumped nonlinear model published previously in Fazekas et al. [2007a]. The parameter estimation method uses the modular decomposition of the system model for obtaining physically meaningful initial parameter estimates. The final parameter estimates are computed using the integrated model.
This paper presents a scheme for designing a robust decentralized PI controller for an industrial utility boiler system. First, a new method for designing robust decentralized PI controllers for uncertain LTI MIMO sys...
This paper presents a scheme for designing a robust decentralized PI controller for an industrial utility boiler system. First, a new method for designing robust decentralized PI controllers for uncertain LTI MIMO systems is presented. Sufficient conditions for closed-loop stability and diagonal dominance of a multivariable system are given. For each isolated subsystem a first order approximation is obtained. Then, achieving robust stability and closedloop diagonal dominance is formulated as local robust performance problems. It is shown by selecting time constants of the closed-loop isolated subsystems appropriately, these local robust performance problems are solved and the interactions between closed-loop stabilized subsystems are attenuated. The internal model control (IMC) method is used to design local PI controllers. The suggested design strategy is applicable to unstable systems as well. Thereafter, the nonlinear model of an industrial utility boiler is linearized about its operating points and the nonlinearity is modeled as uncertainty for a nominal LTI MIMO system. Using the new proposed method, a decentralized PI controller for the uncertain LTI nominal model is designed. The designed controller is applied to the real system. The simulation results show the effectiveness of the proposed methodology.
Brain emotional learning based intelligent controller (BELBIC) is based on computational model of limbic system in the mammalian brain. In recent years, this model was applied in many linear and nonlinear control appl...
Brain emotional learning based intelligent controller (BELBIC) is based on computational model of limbic system in the mammalian brain. In recent years, this model was applied in many linear and nonlinear control applications. Previous studies show that this controller has fast response, simple implementation and robustness with respect to disturbances. It is also possible to define emotional signal based on control application objectives. But in the previous studies, internal instability of this controller was not considered and control task were done in limited time period. In this article mathematical description of BELBIC is investigated and improved to avoid internal instability. Simulation and implementation of improved model was done on level plant. The obtained results showed that instability of model has been solved in the new model without loss of performance by using Integral Anti Windup (IAW).
The field of Unmanned Aerial Vehicles (UAV) has gained great significance in the R&D activities of several institutions, and numerous realizations have been constructed. controlling the movement of a UAV is one of...
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ISBN:
(纸本)9789633130117
The field of Unmanned Aerial Vehicles (UAV) has gained great significance in the R&D activities of several institutions, and numerous realizations have been constructed. controlling the movement of a UAV is one of the most significant tasks in the hierarchical control system that should be realized in order to successfully manage UAVs in several missions. Precise control of the movement requires accurate mathematical models of the aircraft that correspond to the several control schemes that are intended to apply, including linearised, LPV, and nonlinear ones. The source of mathematical models includes the physical model constructed on the basis of the Newtonian equations and the rules of aerodynamics, as well as the use of empirical observations, measurements. The methodology of system identification offers the tools that can be used to manage this field. The Systems and control Laboratory of the computer and automationresearchinstitute in cooperation with University of Minnesota and Budapest University of Technology and Economics has built - as a part of a more general framework established to solve complex UAV control problems - small UAVs, equipped with on-board sensors and embedded computer with the purpose of obtaining an adequate test platform for the aircraft experiments. Based on on-board measurements acquired during the flight tests performed with the UAVs, the opportunity has been given to test several system identification approaches corresponding to the control tasks to be solved. This paper gives an outline of the system identification and modelling methods that have successfully been applied, and also analyzes the problems encountered in the data-acquisition - signal processing - computing chain.
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