Explicit formula of hedge-algebras-based fuzzy controller and applications in structural vibration control

Bui, Hai-Le; Le, Tung-Anh; Bui, Van-Binh

doi:10.1016/j.asoc.2017.06.045

Cited by 33 publications

(31 citation statements)

References 44 publications

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“…These achieved theoretical results sufficiently form a necessary formalized basis for solving application problems in different fields. One can find its applications in cybernetics [15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30], in classification and regression [31,32,33], decision making [38,39], multi-channel image processing [37], robotics [45,46,47,48,49], networking [43,44], fuzzy linguistic time series [40,41,42], linguistic data summaries [35,36], databases and object-oriented databases based on hedge algebraic semantic [58,59,60], and it is not the end.…”

Section: Introductionmentioning

confidence: 99%

Information and Mathematical Structures Contained in the Natural Language Word Domains and Their Applications

Hồ

2021

JCC

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The study stands on the standpoint that there exist relationships between real-world structures and their provided information in reality. Such relationships are essential because the natural language plays a specifically vital and crucial role in, e.g., capturing, conveying information, and accumulating knowledge containing useful high-level information. Consequently, it must contain certain semantics structures, including linguistic (L-) variables’ semantic structures, which are fundamental, similar to the math variables’ structures. In this context, the fact that the (L-) variables’ word domains can be formalized as algebraic semantics-based structures in an axiomatic manner, called hedge algebras (HAs,) is still a novel event and essential for developing computational methods to simulate the human capabilities in problem-solving based on the so-called natural language-based formalism. Hedge algebras were founded in 1990. Since then, HA-formalism has been significantly developed and applied to solve several application problems in many distinct fields, such as fuzzy control, data classification and regression, robotics, L-time series forecasting, and L-data summarization. The study gives a survey to summarize specific distinguishing fundamental features of HA-formalism, its applicability in problem-solving, and its performance.

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Section: Introductionmentioning

confidence: 99%

Information and Mathematical Structures Contained in the Natural Language Word Domains and Their Applications

Hồ

2021

JCC

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“…In this approach, the word-domain of a variable is considered as an order-based algebraic structure, whose words are generated from its two atomic words with the opposite meaning one to the other by using linguistic hedges regarded as unary operations like very, rather, little, extremely, They form a formalism sufficient to immediately handle linguistic information and to soundly construct computational objects, including fuzzy sets, to represent the inherent semantics of their words. Based on this advantage, HAs were apply to many fields such as fuzzy control, e.g., [31,32,33,34,35,36] classification and regression problems [37,38], computing with words [39,40], image processing [41], and so on.…”

Section: Introductionmentioning

confidence: 99%

Enrollment Forecasting Based on Linguistic Time Series

Hieu

Hồ

Lân

2020

JCC

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Dealing with the time series forecasting problem attracts much attention from the fuzzy community. Many models and methods have been proposed in the literature since the publication of the study by Song and Chissom in 1993, in which they proposed fuzzy time series together with its fuzzy forecasting model for time series data and the fuzzy formalism to handle their uncertainty. Unfortunately, the proposed method to calculate this fuzzy model was very complex. Then, in 1996, Chen proposed an efficient method to reduce the computational complexity of the mentioned formalism. Hwang et al. in 1998 proposed a new fuzzy time series forecasting model, which deals with the variations of historical data instead of these historical data themselves. Though fuzzy sets are concepts inspired by fuzzy linguistic information, there is no formal bridge to connect the fuzzy sets and the inherent quantitative semantics of linguistic words. This study proposes the so-called linguistic time series, in which words with their own semantics are used instead of fuzzy sets. By this, forecasting linguistic logical relationships can be established based on the time series variations and this is clearly useful for human users. The effect of the proposed model is justified by applying the proposed model to forecast student enrollment historical data.

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“…In [21], the authors point out that the structure of the hedge-algebra-based controller (HAC) is like the conventional FC, but it is simpler and more convenient. As a result, the HAC was applied in optimal fuzzy control of an inverted pendulum [22], in active vibration control of building structures subjected to seismic excitations [23][24][25][26], and in voltage control of a self-excited induction generator [27]. However, it was not yet applied in the field of grid synchronization.…”

Section: Introductionmentioning

confidence: 99%

Hedge-Algebra-Based Phase-Locked Loop for Distorted Utility Conditions

Vukadinović

Nguyen

et al. 2019

Journal of Control Science and Engineering

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This paper presents the first application of the hedge-algebra theory in the field of grid synchronization. For this purpose, an optimized hedge-algebra controller (HAC) is developed and incorporated within the three-phase phase-locked loop (PLL) with moving average filters (MAFs) inside its feedback loop. Optimized fuzziness parameters and linguistic rule base of the HAC are obtained by a genetic algorithm using the integral of absolute error as the performance index during optimization. Calculated optimal parameter values of the HAC depend on the most frequently occurring disturbance in the electric grid. Two different PLL structures are proposed, depending on the types of disturbances occurring in the electric grid. The first structure is the conventional synchronous reference frame PLL with the nonadaptive MAF (i.e., MAF without order adjustment), but with the PI/PID controller in the phase loop replaced by the developed HAC. Such PLL structure is suitable for all analyzed disturbance types, expect for step-changes in the grid frequency. The second PLL structure introduces the adaptive MAF (i.e., MAF with order adjustment) and a new feedback signal in the output stage of the controller to achieve zero steady-state error in the case of step-changes in the grid frequency. The disturbance rejection capability of the two developed PLLs with the HAC (HAC-PLLs) is tested separately and compared experimentally with the PID- and fuzzy-controller-based PLLs.

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Explicit formula of hedge-algebras-based fuzzy controller and applications in structural vibration control

Cited by 33 publications

References 44 publications

Information and Mathematical Structures Contained in the Natural Language Word Domains and Their Applications

Information and Mathematical Structures Contained in the Natural Language Word Domains and Their Applications

Enrollment Forecasting Based on Linguistic Time Series

Hedge-Algebra-Based Phase-Locked Loop for Distorted Utility Conditions

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