In this paper we compared the power transistor switching algorithms of electric energy converters. The algorithms of power keys switching proposed for minimizing the dimensions of filtering components and dynamic loss...
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ISBN:
(纸本)9781538643075
In this paper we compared the power transistor switching algorithms of electric energy converters. The algorithms of power keys switching proposed for minimizing the dimensions of filtering components and dynamic losses in switching components of a converter meeting at the same time the requirements for energy quality. We also described the circuit topology of a synchronous-vector rectifier (SVR) model. The proposed algorithms were modeled for the rectifier and inverter modes of operation using the LTSpice software circuit simulator. The obtained results are presented in the form of diagrams. The modeled algorithms provide the performance of functions of a synchronous-vector rectifier both in the rectifier and inverter modes of operation under very "modest" requirements for the parameters of filtering components.
The battery is a key component in any Electric Vehicle (EV) and its method of operation may have a tremendous effect on its life. In this paper we focus on improving the battery's life. Each battery is a pack of c...
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The battery is a key component in any Electric Vehicle (EV) and its method of operation may have a tremendous effect on its life. In this paper we focus on improving the battery's life. Each battery is a pack of cells designed to be discharged and charged with specific optimal currents, whereby other currents, i.e. higher or lower than the optimal currents, may have negative effects on its life. We model these negative effects as penalties that are aggregate over time and propose a discharge method to minimize them. The common discharge method is very simple but far from optimal since the current demand is supplied using all the battery's cells where the current from each is the same. The method we propose is advanced switching algorithms that select a subset of the battery's cells for each current demand and control the discharge current from each, based on the electrochemical properties of the individual cells. We evaluate our proposed algorithms using simulations on world-wide driving cycles. The results reveal that compared to the common discharge method almost all penalties can be eliminated and the battery's life can be significantly extended. (C) 2012 Elsevier B.V. All rights reserved.
In this paper, it is proposed to switch between swarm optimization algorithms during the optimization process, aiming at combining the best performance from each single swarm optimization algorithm and hence improving...
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ISBN:
(纸本)9781728124858
In this paper, it is proposed to switch between swarm optimization algorithms during the optimization process, aiming at combining the best performance from each single swarm optimization algorithm and hence improving the overall empirical performance. To investigate this switching scheme, an empirical study is carried on four swarm algorithms, Particle Swarm Optimization, Gravitational Search, Grey Wolf Optimizer and Chicken Swarm Optimization. All possible switches (combinations) among those four algorithms are tested. In addition, instead of searching for the best switching point, it is prescribed in the experiment. The proposed method is empirically investigated on the so-called Black-Box Optimization Benchmark (BBOB), where the switching method is compared to each individual swarm algorithm as well as using the state-of-the-art black-box optimization algorithm, BIPOP-CMA-ES (BI-population Covariance Matrix Adaptation Evolution Strategy). The result shows that the switching approach generally improves the performance of individual swarm algorithms. However, none of them can rival the performance of the BIPOP-CMA-ES.
This paper deals with the design of a switched Nonlinear Model Predictive Controller (NMPC) for collaborative ecodrive control of railway vehicles. Relying on a discrete, switched and nonlinear model of the train, the...
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This paper deals with the design of a switched Nonlinear Model Predictive Controller (NMPC) for collaborative ecodrive control of railway vehicles. Relying on a discrete, switched and nonlinear model of the train, the NMPC optimizes the handle position while fulfilling constraints on velocity and journey time. Specifically, the optimizer provides a set of operating modes, which the human driver is able to implement to modulate traction or braking forces and such that the corresponding driving style is constrained by predefined driving sequences. At network level, a Dissension based Adaptive Law (DAL) is then proposed to adjust the parameters of the NMPC cost so as to efficiently share the available regenerated braking energy among the trains connected to the same substation, while negotiating between constraint satisfaction and control aggressiveness. The effectiveness of the proposed strategy is finally demonstrated on a realistic simulation case study. (C) 2019 European Control Association. Published by Elsevier Ltd. All rights reserved.
作者:
Filipovic, VojislavUniv Kragujevac
Fac Mech & Civil Engn Dept Automat Control Robot & Fluid Tech Dositejeva 19 Kraljevo 36000 Serbia
The paper considers the recursive identification of nonlinear (Hammerstein) model in the presence of outliers. In this model the nonlinear part is a polynomial of a known order in the input and linear part is describe...
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The paper considers the recursive identification of nonlinear (Hammerstein) model in the presence of outliers. In this model the nonlinear part is a polynomial of a known order in the input and linear part is described as an ARX (auto - regressive model with exogenous inputs) model. It is assumed that there is a priori information about a disturbance distribution in the form of a class of distributions. Owing that fact it is possible to use robust statistics in the sense of Huber. But Huber's loss function is only first order differentiable. It follows that second order methods (Newton - Raphson methodology) cannot be used. The problem is avoided by analysis of the structure of least favourable distribution. It is shown that robust recursive algorithm derivation can be set in frame of l(1) - l(2) - norm estimation problem. The main contributions of the paper are: (i) it is shown that the robust identification belongs l(1) - l(2)-norm estimation problem: (ii) the derivation of the new robust recursive algorithm;(iii) it is shown that robust recursive algorithm is switching algorithm (collection of linear least squares and sign algorithm) and that fact opens the new research opportunities. (C) 2019 Elsevier Ltd. All rights reserved.
The problem of rejection of a sinusoidal disturbance with unknown frequency acting on an unknown single-input-single-output stable linear system is addressed in this paper. We present a new hybrid approach that does n...
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The problem of rejection of a sinusoidal disturbance with unknown frequency acting on an unknown single-input-single-output stable linear system is addressed in this paper. We present a new hybrid approach that does not require knowledge of the frequency response of the transfer function over the range of frequencies of interest. The proposed controller reposes upon a switching strategy within a family of linear controllers based on the adaptive feedforward / internal model control methodology. A dead-beat frequency estimation method is integrated in the controller. The method also accounts for the presence of bounded sensor noise as well as imprecise frequency estimation. It is shown that, within a finite number of switchings, the regulation error is ultimately bounded by a function of the norm of the noise that depends on the choice of the controller and the estimator gains. (C) 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
This paper studies the approach of taking network topology as a control variable for the analysis of coupled harmonic oscillators. We particularly consider the setting where the local control inputs of individual osci...
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The problem of rejection of a sinusoidal disturbance with unknown frequency acting on an unknown single-input-single-output stable linear system is addressed in this paper. We present a new hybrid approach that does n...
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The problem of rejection of a sinusoidal disturbance with unknown frequency acting on an unknown single-input-single-output stable linear system is addressed in this paper. We present a new hybrid approach that does not require knowledge of the frequency response of the transfer function over the range of frequencies of interest. The proposed controller reposes upon a switching strategy within a family of linear controllers based on the adaptive feedforward / internal model control methodology. A dead-beat frequency estimation method is integrated in the controller. The method also accounts for the presence of bounded sensor noise as well as imprecise frequency estimation. It is shown that, within a finite number of switchings, the regulation error is ultimately bounded by a function of the norm of the noise that depends on the choice of the controller and the estimator gains.
A switched Nonlinear Model Predictive Control (NMPC) strategy for time efficient energy control of railway vehicles, while fulfilling constraints on velocity, journey time and driving style in a collaborative fashion ...
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A switched Nonlinear Model Predictive Control (NMPC) strategy for time efficient energy control of railway vehicles, while fulfilling constraints on velocity, journey time and driving style in a collaborative fashion ...
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A switched Nonlinear Model Predictive Control (NMPC) strategy for time efficient energy control of railway vehicles, while fulfilling constraints on velocity, journey time and driving style in a collaborative fashion (collaborative eco-drive) is proposed. More specifically, the train dynamics are modeled as discrete, switched and nonlinear, while the optimization variable is the handle position which modulates the available traction/braking force and has to belong to a set of discrete values and/or operating modes, which the human driver is able to implement. Hence the aim is to choose the optimal handle position that minimizes the cost, is implementable by the driver and also fulfills the eco-driving objective, such that the driving style is constrained by predefined driving sequences. A supervisor detects the states of the trains and subsequently modifies the weights of the cost by negotiating between constraint satisfaction and control aggressiveness, in order to share the available regenerated braking energy among the connected trains in a substation network. The efficiency of the proposed switched NMPC strategy is demonstrated using realistic simulation case study. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
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