Optimal Design of Fuzzy Systems Using Differential Evolution and Harmony Search Algorithms with Dynamic Parameter Adaptation

Castillo, Oscar; Valdez, Fevrier; Soria, José Manuel Nieto; Lee, Ji Eun; Geem, Zong Woo; Peraza, Cinthia; Ochoa, Patricia; Amador-Angulo, Leticia

doi:10.3390/app10186146

Cited by 14 publications

(7 citation statements)

References 46 publications

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“…Design of the Vocal Signal Processing Module. The audio signal processing module is designed for the DSP processor [19]. The module uses a stable DSP chip TMS320VC5402DSP suitable for voice signal operation, and DSP chip has low power consumption, is fast, can carry 2 MCBSPS (multichannel nonstop port), and is connected to CODEC (codec) with audio input, 8-bit upgraded host parallel port (HPI8), 4KBROM, and 16KBDARAM.…”

mentioning

confidence: 99%

Design of the Vocal Music Feature Recognition System Based on the Internet of Things Technology

Huang¹

2022

Journal of Sensors

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In order to meet the needs of vocal feature recognition, the author proposes a system design based on the Internet of things technology. The principle of the method is that the body sensory layer of the body puts the sound sensors in different positions, records the primary sound signal, and monitors and makes the sound signal using the TMS320VC5402 light red processor. The network transport layer audio signal processes and sends the voice signal database in the process layer. The sound characteristic analysis module in the application layer uses a real-time dynamic change algorithm to obtain the best similarity between the experimental model and the design, identify the characteristics of the sound set red, and identify the content of the voice feature, the music, and the emotional results of the song. Experiments have shown that the system is capable of recognizing speech in a noisy environment, with an accuracy of approximately 95%, resulting in better sound control and the ability to switch switches and remote control. The system, developed with the Internet of things technology, has been proven to improve voice recognition.

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confidence: 99%

Design of the Vocal Music Feature Recognition System Based on the Internet of Things Technology

Huang¹

2022

Journal of Sensors

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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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“…e principal fuzzy systems are Mandani and Takagi-Sugeno. In particular, the Mandani systems use various techniques that allow fuzzy set membership function tuning, such as genetic algorithms (GA) [16], adaptive neural networks [17,18], artificial bee colony optimization [19][20][21], ant colony optimization [22][23][24], and evolutionary algorithms [25][26][27].…”

Section: Introductionmentioning

confidence: 99%

Optimal Position Fuzzy Control of an Underactuated Robotic Finger

Espinosa-Garcia

Lugo-González

Téllez-Velázquez

et al. 2022

Mathematical Problems in Engineering

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In this paper, the optimal position control of an underactuated robotic finger is presented. Two trajectories, one for the proximal and the other for the medial phalanx, are proposed in order to emulate the finger’s flexion/extension movements. A Mandani fuzzy control is proposed due to the lack of a precise dynamical model of the system. In order to obtain the control parameters, an optimization strategy based on the membership functions is applied. Genetic algorithms (GA) are commonly used as an optimization method in diverse applications; however, in this case, the use of an autoadaptive differential evolution method is proposed in order to obtain a superior convergence behavior. Simulations of the virtual prototype are carried out using MATLAB/Simulink software to display the trajectory tracking. The results show that the maximum error between the proposed and obtained trajectories is 3.1352E − 04 rad.

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Optimal Design of Fuzzy Systems Using Differential Evolution and Harmony Search Algorithms with Dynamic Parameter Adaptation

Cited by 14 publications

References 46 publications

Design of the Vocal Music Feature Recognition System Based on the Internet of Things Technology

Design of the Vocal Music Feature Recognition System Based on the Internet of Things Technology

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

Optimal Position Fuzzy Control of an Underactuated Robotic Finger

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