High-Speed Interval Type-2 Fuzzy System for Dynamic Crossover Parameter Adaptation in Differential Evolution and Its Application to Controller Optimization

Ochoa, Patricia; Castillo, Oscar; Soria, José Manuel Nieto

doi:10.1007/s40815-019-00723-w

Cited by 16 publications

(5 citation statements)

References 33 publications

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“…It simplifies a(qO) to a(q), and we can get: (3) where Q represents the sample number, and y(o) represents the output value of the qth sample. e fuzzy adaptive control system is composed of PID controller and control link, connected with the signal conversion mechanism, and then the analytic signal is input into the controller and control link, and finally the calibration value is obtained [17].…”

Section: Overview Of Fuzzy Controlmentioning

confidence: 99%

“…Ochoa et al used a new method to improve the speed of adaptive processing of dynamic parameters in differentiated evolutionary methods, which was proposed by Karnik and Mendel (KM) and which has an enhanced version called EKM and continuous versions called CKM and CEKM. In addition, there are these and other kinds of variants which cancel out the typological simplification process and thus reduce the computational cost to the first class going Fuzzification [3]. Valdez and Peraza described the methods and equations used to construct triangular and Gaussian interval membership functions and applied this method to the baseline implementation of a zone 2 ambiguous logic controller for the optimisation of a benchmark control problem.…”

Section: Introductionmentioning

confidence: 99%

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Biomedical Disabled Rehabilitation Analysis considering Fuzzy Parameter Adaptive PID Algorithm

Zhang

Zhao

2022

Mobile Information Systems

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Fuzzy parameter adaptation refers to an idea of adjusting parameters based on parameter deviation, deviation change rate and the relationship between the parameters. The PID control algorithm incorporates three algorithms: ratio, sigma, and lead. It is one of the most commonly used algorithms and has a wide range of applications. Embedded system is an application-centric computer system based on modern computer technology that can be flexibly dedicated according to user needs. Although it is convenient to use, it cannot perform large-scale operations and storage. This article aims to explore the role of fuzzy parameter adaptive PID algorithm in the rehabilitation of biomedical persons with disabilities. It is hoped that modern technology will be used to find a new direction for the rehabilitation of the disabled, so that the disabled can better survive in the society. This paper studies the existing classic real-time scheduling algorithms and traditional adaptive scheduling algorithms and analyzes their shortcomings when applied to embedded systems; when sorting out related concepts, clarified related concepts such as disabled persons, to provide tertiary level study for people at risk and higher education policies for persons with disabilities; it combines classic and fuzzy control to form fuzzy self-adaptation, realizes fuzzy self-adaptive control of the temperature value of high temperature sterilization, and improves the automation level of the system. The experimental results of this article show that 68 persons with disabilities need medical diagnosis, accounting for 52%; 15 persons with disabilities need physical correction, accounting for 12%; 29 persons with disabilities require acupuncture treatment, accounting for 22%; 18 persons with disabilities were in mental treatment, accounting for 14%; 57 people lost the ability to learn due to memory decline, accounting for 44%; 46 people were unable to learn due to physical disabilities, accounting for 35%; but there were still 17 people who were able to study normally, accounting for 13% of the total number of people surveyed; 10 people were unable to study due to other reasons, accounting for 8%.

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Section: Overview Of Fuzzy Controlmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Biomedical Disabled Rehabilitation Analysis considering Fuzzy Parameter Adaptive PID Algorithm

Zhang

Zhao

2022

Mobile Information Systems

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“…Additional aspects are also considered by these works, such as time windows [57,61,62], environmental aspects [59], multiple objectives [59], intermodal transportation [57,59] and an open VRP [63]. Additional applications of metaheuristics combined either with Monte Carlo simulation or fuzzy logic can be found in several fields, such as scheduling [64,65], controller optimization [66,67] parameter estimation [68], finance [69], facility location [70], etc.…”

Section: Simheuristics and Fuzzy Logic For Vehicle Routing Problems Under Uncertaintymentioning

confidence: 99%

Combining Heuristics with Simulation and Fuzzy Logic to Solve a Flexible-Size Location Routing Problem under Uncertainty

et al. 2021

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The location routing problem integrates both a facility location and a vehicle routing problem. Each of these problems are NP-hard in nature, which justifies the use of heuristic-based algorithms when dealing with large-scale instances that need to be solved in reasonable computing times. This paper discusses a realistic variant of the problem that considers facilities of different sizes and two types of uncertainty conditions. In particular, we assume that some customers’ demands are stochastic, while others follow a fuzzy pattern. An iterated local search metaheuristic is integrated with simulation and fuzzy logic to solve the aforementioned problem, and a series of computational experiments are run to illustrate the potential of the proposed algorithm.

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“…Another important part of our work is the utilization of general type-2 fuzzy logic, which works under the same concept as Type-1 and interval type-2 fuzzy logic systems, except that their mathematical functions contemplate different concepts since GT2FSs are well known for handling higher levels of uncertainty. There are different definitions about the mathematical functions used in a general type-2 fuzzy logic system, and for this work we are going to use the notation presented on [44][45][46][47]. The formulation of general type-2 fuzzy sets is presented in Equation (8).…”

Section: General Type-2 Fuzzy Systemsmentioning

confidence: 99%

Differential Evolution with Shadowed and General Type-2 Fuzzy Systems for Dynamic Parameter Adaptation in Optimal Design of Fuzzy Controllers

Ochoa

Castillo

Melín

et al. 2021

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This work is mainly focused on improving the differential evolution algorithm with the utilization of shadowed and general type 2 fuzzy systems to dynamically adapt one of the parameters of the evolutionary method. Previously, we have worked with both kinds of fuzzy systems in different types of benchmark problems and it has been found that the use of fuzzy logic in combination with the differential evolution algorithm gives good results. In some of the studies, it is clearly shown that, when compared to other algorithms, our methodology turns out to be statistically better. In this case, the mutation parameter is dynamically moved during the evolution process by using shadowed and general type-2 fuzzy systems. The main contribution of this work is the ability to determine, through experimentation in a benchmark control problem, which of the two kinds of the used fuzzy systems has better results when combined with the differential evolution algorithm. This is because there are no similar works to our proposal in which shadowed and general type 2 fuzzy systems are used and compared. Moreover, to validate the performance of both fuzzy systems, a noise level is used in the controller, which simulates the disturbances that may exist in the real world and is thus able to validate statistically if there are significant differences between shadowed and general type 2 fuzzy systems.

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High-Speed Interval Type-2 Fuzzy System for Dynamic Crossover Parameter Adaptation in Differential Evolution and Its Application to Controller Optimization

Cited by 16 publications

References 33 publications

Biomedical Disabled Rehabilitation Analysis considering Fuzzy Parameter Adaptive PID Algorithm

Biomedical Disabled Rehabilitation Analysis considering Fuzzy Parameter Adaptive PID Algorithm

Combining Heuristics with Simulation and Fuzzy Logic to Solve a Flexible-Size Location Routing Problem under Uncertainty

Differential Evolution with Shadowed and General Type-2 Fuzzy Systems for Dynamic Parameter Adaptation in Optimal Design of Fuzzy Controllers

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