Type-2 Fuzzy membership function design method through a piecewise-linear approach

Ibarra, Luis; Rojas, Mario; Ponce, Pedro; Molina, Arturo

doi:10.1016/j.eswa.2015.05.029

Cited by 9 publications

(3 citation statements)

References 39 publications

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“…The ambiguity and certainty of evaluation indexes can be mutually transformed (Ibarra et al., 2015; Zhang and Yang, 2012). In accordance with the criteria for index classification (Table 1) and the quantitative standards for drivability (Table 2), the membership degree function of the evaluation index was designed as in the equations (10)–(12) as the evaluation grade in the ambiguity rating where μi∈[0,1], i = 1, 2,…, 5 denotes the probability of different membership functions as shown in Figure 3.…”

Section: Fuzzy Dynamic Weight Evaluation Model Of Drivabilitymentioning

confidence: 99%

Application of fuzzy dynamic weights drivability evaluation model in tip-in condition

Huang

Liu

2018

Journal of Vibration and Control

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Only the subjective or objective method is employed to calculate the index weight in the evaluation of drivability, which makes the evaluation result less accurate. In this paper, a drivability evaluation model was proposed on the basis of fuzzy dynamic weights, and the drivability was evaluated in tip-in conditions. The evaluation indexes affecting drivability in tip-in conditions were determined using multi-dimensional analysis. The dynamic weight was built using an improved analytic hierarchy process and improved entropy method in accordance with the principle of “function driving and difference driving.” The fuzzy matrix was built by drawing upon the improved membership function of the evaluation index. Finally, the drivability evaluation model of the tip-in condition was built with dynamic weight and fuzzy matrix. The evaluation model was employed to evaluate the drivability of the vehicle, which obtained the drivability score. As the experiment results suggest, the evaluation model is accurate and effective in comparison with the real score and the score obtained from the fuzzy analytic hierarchy process. The evaluation model is employed to formulate a control strategy for a vehicle that will allow better drivability. Besides, the method makes the performance development of the vehicle more knowledgeable and agile.

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Section: Fuzzy Dynamic Weight Evaluation Model Of Drivabilitymentioning

confidence: 99%

Application of fuzzy dynamic weights drivability evaluation model in tip-in condition

Huang

Liu

2018

Journal of Vibration and Control

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“…However, in the fuzzy set theory application field, they are not investigated sufficiently in a systematic and comprehensive way. Authors of the analysed papers have focused on solving a particular task, like reducing computational complexity through decreasing the number of fuzzy rules (Ruiz-Garcia et al, 2019;Zhu et al, 2017;Harandi and Derhami, 2016;Bouchachia and Vanaret, 2014) or reducing MFs (Fan et al, 2019;Ibarra et al, 2015), etc. This lack of understanding of a general situation hampers progress in the analysed field since academics offer limited approaches (Ivarsson and Gorschek, 2011).…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Systematic Review Approach on Complexity Issues in Data-Driven Fuzzy Inference Systems Development

Kalibatiene¹,

Miliauskaitė²

2021

Informatica

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The data-driven approach is popular to automate learning of fuzzy rules and tuning membership function parameters in fuzzy inference systems (FIS) development. However, researchers highlight different challenges and issues of this FIS development because of its complexity. This paper evaluates the current state of the art of FIS development complexity issues in Computer Science, Software Engineering and Information Systems, specifically: 1) What complexity issues exist in the context of developing FIS? 2) Is it possible to systematize existing solutions of identified complexity issues? We have conducted a hybrid systematic literature review combined with a systematic mapping study that includes keyword map to address these questions. This review has identified the main FIS development complexity issues that practitioners should consider when developing FIS. The paper also proposes a framework of complexity issues and their possible solutions in FIS development.

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“…22,23 The set boundaries that are no longer crisp but fuzzy are defined by a function that assigns a degree of membership to each element when evaluated as a member of the set. 24 Due to the membership function, the system can express all the fuzzy concepts quantitatively. Furthermore, the calculated data will be used in the process of solving the fuzzy relation equation of rule reasoning.…”

Section: Adaptive Fuzzy/pid Compound Controllermentioning

confidence: 99%

Adaptive fuzzy/proportion integration differentiation (PID) compound control for unbalance torque disturbance rejection of aerial inertially stabilized platform

Zhou

Yuan

2016

International Journal of Advanced Robotic Systems

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This article describes an adaptive fuzzy/proportion integration differentiation (PID) compound control scheme to promote the disturbance rejection ability of an aerial inertially stabilized platform. To deal with the serious influence of predominant unbalance torque disturbance on the steady precision of inertially stabilized platform, dynamic modeling and simulation analysis are conducted, which reveal that the unbalance torque disturbance is nonlinear and time varying. Then, an adaptive fuzzy/PID compound controller is designed that can automatically adjust and control parameters of the system in real time. In this way, the effects of unbalance torque disturbance on control performance are suppressed greatly so that the pointing accuracy and stability are obviously improved. To validate the scheme, the simulations and experiments are conducted to a real three-axis inertially stabilized platform. The results show that under the environment of unbalance torque disturbance, the inertially stabilized platform could reach better dynamic performances by the compound scheme, leading to the high pointing accuracy and stability.

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Type-2 Fuzzy membership function design method through a piecewise-linear approach

Cited by 9 publications

References 39 publications

Application of fuzzy dynamic weights drivability evaluation model in tip-in condition

Application of fuzzy dynamic weights drivability evaluation model in tip-in condition

A Hybrid Systematic Review Approach on Complexity Issues in Data-Driven Fuzzy Inference Systems Development

Adaptive fuzzy/proportion integration differentiation (PID) compound control for unbalance torque disturbance rejection of aerial inertially stabilized platform

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