$m^*$-fuzzy basically disconnected spaces in smooth fuzzy topological spaces

Amudhambigai, B.; Uma, M. K.; Roja, E.

doi:10.21136/mb.2013.143223

Cited by 2 publications

(2 citation statements)

References 5 publications

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“…After introduction of topological structures [9], different researchers have studied the concept of smooth fuzzy topological spaces [10] and their properties and characterizations in different compact, disconnected and bitopological spaces [11][12][13][14].…”

Section: International Journal Of Fuzzy Systemsmentioning

confidence: 99%

Fuzzy Model Identification and Self Learning with Smooth Compositions

Sadjadi

García

López

et al. 2019

Int. J. Fuzzy Syst.

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This paper develops a smooth model identifica-10 tion and self-learning strategy for dynamic systems taking 11 into account possible parameter variations and uncertain-12 ties. We have tried to solve the problem such that the 13 model follows the changes and variations in the system on 14 a continuous and smooth surface. Running the model to 15 adaptively gain the optimum values of the parameters on a 16 smooth surface would facilitate further improvements in 17 the application of other derivative based optimization 18 control algorithms such as MPC or robust control algo-19 rithms to achieve a combined modeling-control scheme. 20 Compared to the earlier works on the smooth fuzzy mod-21 eling structures, we could reach a desired trade-off between 22 the model optimality and the computational load. The 23 proposed method has been evaluated on a test problem as 24 well as the non-linear dynamic of a chemical process. 25 26 Keywords Fuzzy control Á Fuzzy IF-THEN systems 27 (TSK) Á Smooth compositions 28 1 Introduction 29 Soft computing methods are being used for identification of 30 non-linear and complex systems based on the input-output 31 data collected from the original system [1]. There are many

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Section: International Journal Of Fuzzy Systemsmentioning

confidence: 99%

Fuzzy Model Identification and Self Learning with Smooth Compositions

Sadjadi

García

López

et al. 2019

Int. J. Fuzzy Syst.

View full text Add to dashboard Cite

show abstract

“…After introduction of topological structures [12], different researchers have studied the concept of smooth fuzzy topological spaces [13] and their properties and characterizations in different compact, disconnected and bitopological spaces [14][15][16][17].…”

Section: Smooth Fuzzy Compositionsmentioning

confidence: 99%

How Effective are Smooth Compositions in Predictive Control of TS Fuzzy Models?

Sadjadi

Menhaj

Herrero

et al. 2019

Int. J. Fuzzy Syst.

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In this article, we study the structural properties that smooth compositions bring to predictive control of TS fuzzy models and examine how they affect the uncertainties, parameter variations of the system and environmental noises to die out. We have employed the smoothness structure of compositions to convert the MPC cost function of TS fuzzy model of the nonlinear systems to an incremental iterative algorithm. Hence, the proposed algorithm does not linearize the nonlinear dynamics, neither requires solving an NP optimization problem in MPC and, therefore, is very fast and simple. The connectivist identification-MPC approach-can be employed for the systems with the long-range horizons. Therefore, the technique is beneficial to the dead-time and non-minimum phase systems. The stability analysis of the algorithm has been carried out, and the performance of the smooth TS fuzzy identification-controller scheme to the classical ones has been compared on a non-min phase test problem with different uncertainties and working environments, including (a) the normal working conditions, (b) with the additive noises, (c) with the parametric changes, (d) with the additive time-varying disturbances to demonstrate the robust behavior of the smooth compositions.

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$m^*$-fuzzy basically disconnected spaces in smooth fuzzy topological spaces

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Cited by 2 publications

References 5 publications

Fuzzy Model Identification and Self Learning with Smooth Compositions

Fuzzy Model Identification and Self Learning with Smooth Compositions

How Effective are Smooth Compositions in Predictive Control of TS Fuzzy Models?

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