2011
DOI: 10.1016/j.asoc.2010.11.004
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Stability analysis and robustness design of nonlinear systems: An NN-based approach

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Cited by 106 publications
(21 citation statements)
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“…The component values given in (10), (11) and (12) correspond to the nodes of the partitioned data sets having one parameter, two parameters and three parameters respectively. To determine an analytical structure as the model of the given problem, a rule should be defined.…”
Section: The Euclidean Indexing Hdmr Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…The component values given in (10), (11) and (12) correspond to the nodes of the partitioned data sets having one parameter, two parameters and three parameters respectively. To determine an analytical structure as the model of the given problem, a rule should be defined.…”
Section: The Euclidean Indexing Hdmr Methodsmentioning
confidence: 99%
“…Another approach based on fuzzy analytic hierarchy process (FAHP) is developed for the ambiguous fault evaluations of lithography process [9]. A neural-network (NN) based approach is developed for the purpose of stabilization and stability analysis of nonlinear systems [10]. Another model based on fuzzy systems is developed to efficiently control nonlinear multivariable systems [11,12].…”
Section: Introductionmentioning
confidence: 99%
“…As a result, the online learning time becomes prohibitively large. In addition, recent years, the applications of the new control theory have achieved great development and a lot of results have been obtained, such as [36][37][38] and the references therein, and many control approaches have been proposed to control the real systems, such as fuzzy control [5,6,18,19,21,26,29,[39][40][41][42][43][44][45][46][47][48][49], neural network control [2,4] and so on.…”
Section: Introductionmentioning
confidence: 99%
“…Li et al [6] and Chyu and Chang [7] examine the UPMSP to minimize the mean flow time, while Cao et al [8] study the Amiri and Khanmohammadi [17] classified the proposed methods for solving such problems into two categories as classic and intelligent algorithms (IA). While the Dynamic programming [18] and Lagrangian relaxation [19] are classified as former categories, genetic algorithm (GA) [20], PSO [21], ant colony optimization (ACO) [22], neural network (NN) [23][24][25][26] and various hybrid IAs [27] are categorized as the later one.…”
Section: Introductionmentioning
confidence: 99%