To deal with the problem of observing or tracking for discontinuous signal,a kind of second order linear extended state observer(LESO) algorithm is *** ESO estimating the uncertain disturbance,a simple second-order li...
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ISBN:
(纸本)9781467397155
To deal with the problem of observing or tracking for discontinuous signal,a kind of second order linear extended state observer(LESO) algorithm is *** ESO estimating the uncertain disturbance,a simple second-order linear ESO with less tunable parameters was designed in the absence of dynamic model,and the method of discrete time realization was *** proposed LESO was applied to the tracking of discontinuous Stribeck Friction in comparison with adaptive state *** results show that the proposed ESO is effective and practical.
The distributed H ∞ state estimation problem over a filtering network with Markov switching topology is studied in this paper by employing event-triggered strategy. The strategy at each node is built on the output e...
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The distributed H ∞ state estimation problem over a filtering network with Markov switching topology is studied in this paper by employing event-triggered strategy. The strategy at each node is built on the output estimation error of its own and those received from its neighbours. Based on the communication uncertainty of practical networks, switching topology which subjects to a heterogeneous Markov chain is considered in filter design. By utilizing stochastic Markov stability theory, switching topology-dependent filters are designed such that the underlying error system is stochastically stable in mean square and the disturbance rejection attenuation level guarantees an H ∞ performance bound. An illustrative example is presented to show the applicability of the obtained results.
Brain computer interface (BCI) could help patients to manipulate external devices based on the specific brain activities. One of the most popular BCI systems is the visual-based BCI system. Mostly, users were asked to...
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This paper is concerned with the guaranteed cost filtering problem for discrete-time multi-layer neural networks with unideal measurements and time-varying delays. First, the innovative state space model of multi-laye...
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ISBN:
(纸本)9781509041039
This paper is concerned with the guaranteed cost filtering problem for discrete-time multi-layer neural networks with unideal measurements and time-varying delays. First, the innovative state space model of multi-layer neural networks can be described by the weighted-nonlinear function, which means that there have connections among neural layers. Then, the unideal measurements are made up by combination of random sensor nonlinearity and partial missing measurements, where partial missing measurements is the product of two mutually independent stochastic variables and normal measurements. Moreover, by using proportionate-additive filter and constructing a unified Lyapunov function, a novel criterion is proposed so that the augmented filtering error system achieves robust stability and has a guaranteed cost index. Finally, simulation results are presented to demonstrate the effectiveness of the derived method.
Conventional principal component analysis (PCA) can obtain low-dimensional representations of original data space, but the selection of principal components (PCs) based on variance is subjective, which may lead to inf...
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This article deals with the problem of driving a family of second-order nonlinear agents to land on a sphere and formation tracking a set of given orbits on the sphere.A novel geometric extension called the concentric...
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ISBN:
(纸本)9781467397155
This article deals with the problem of driving a family of second-order nonlinear agents to land on a sphere and formation tracking a set of given orbits on the sphere.A novel geometric extension called the concentric compression method is proposed to give a solution to spheral landing and then combines with the control of spherical meridian and parallel to achieve formation motion along given orbits on the *** asymptotic stability of system is proved by Lyapunov-based method when the communication topology is *** effectiveness of the analytical result is verified by a numerical simulation.
This paper addresses the problem of robust stabilization for uncertain systems subject to input saturation and nonhomogeneous Markov *** uncertainties are assumed to be norm bounded and the transition probabilities ar...
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ISBN:
(纸本)9781467397155
This paper addresses the problem of robust stabilization for uncertain systems subject to input saturation and nonhomogeneous Markov *** uncertainties are assumed to be norm bounded and the transition probabilities are time-varying and *** expressing the saturated linear feedback law on a convex hull of a group of auxiliary linear feedback laws and the time-varying transition probabilities inside a polytope,we establish conditions under which the closed-loop system is asymptotically *** on these conditions,the problem of designing the state feedback gains for achieving fast transience response with a guaranteed size of the domain of attraction is formulated and solved as a constrained optimization problem with linear matrix inequality(LMI) *** results are then illustrated by a numerical example.
Catalytic naphtha reforming is one of the most important processes for high octane gasoline manufacture and aromatic hydrocarbons production. In this article, a modified differential evolution (DE) algorithm is propos...
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Catalytic naphtha reforming is one of the most important processes for high octane gasoline manufacture and aromatic hydrocarbons production. In this article, a modified differential evolution (DE) algorithm is proposed to optimize an actual continuous catalytic naphtha reforming (CCR) process. The optimization problem considers to minimize the energy consumption and maximize the aromatics yield. The CCR process model is established by adopting the 27-lumped kinetics reaction network, and all parameters are adjusted based on the actual process data. The DE algorithm is modified to maintain the diversity of the population. In this mechanism, individuals further from the best individual have larger possibilities to be selected in the mutation operator. The modified DE is evaluated by solving 6 benchmark functions, and the performance is compared with classic DEs. The results demonstrate that the modified DE has better global search ability and higher computation efficiency. Furthermore, the optimization results of catalytic naphtha reforming process indicate that the proposed algorithm has the ability of locating the optimal operating points, in which the aromatics yield is improved, while energy consumption is reduced. Meanwhile, the optimal operating points and results are discussed at the end of the article.
This paper addresses robust multiobjective identification of driver nodes in the neuronal network of a cat's brain,in which uncertainties in determination of driver nodes and control gains are considered. A framew...
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ISBN:
(纸本)9781467374439
This paper addresses robust multiobjective identification of driver nodes in the neuronal network of a cat's brain,in which uncertainties in determination of driver nodes and control gains are considered. A framework by including interval uncertainties is proposed for robust controllability. It is revealed that the existence of uncertainties in choosing driver nodes and designing control gains heavily affect the controllability of neuronal networks.
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