scholarly journals Fuzzy Dynamic Parameter Adaptation in the Harmony Search Algorithm for the Optimization of the Ball and Beam Controller

2018 ◽  
Vol 2018 ◽  
pp. 1-16 ◽  
Author(s):  
Cinthia Peraza ◽  
Fevrier Valdez ◽  
Juan R. Castro ◽  
Oscar Castillo
Keyword(s):  
Fuzzy Systems ◽  
Search Algorithm ◽  
Harmony Search ◽  
Dynamic Parameter ◽  
Harmony Search Algorithm ◽  
Parameter Adaptation ◽  
Error Metrics ◽  
Interval Type ◽  
Following Error

This paper presents a method for dynamic parameter adaptation in the harmony search algorithm (HS) based on fuzzy logic. The adaptation is performed using Type 1 (FHS), interval Type 2 (IT2FHS), and generalized Type 2 (GT2FHS) fuzzy systems as the number of improvisations or iterations advances, achieving a better intensification and diversification. The main contribution of this work is the dynamic parameter adaptation using different types of fuzzy systems in the harmony search algorithm applied to optimization of the membership functions for a benchmark control problem; in this case it is focused on the ball and beam controller. Experiments are presented with the HS, FHS, IT2FHS, and GT2FHS with noise (uniform random number) and without noise for the controller, and the following error metrics are obtained: ITAE, ITSE, IAE, ISE, and RMSE, to validate the efficacy of the proposed methods.

scholarly journals High-Speed Interval Type-2 Fuzzy Systems for Dynamic Parameter Adaptation in Harmony Search for Optimal Design of Fuzzy Controllers

Mathematics ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 758
Author(s):  
Oscar Castillo ◽  
Fevrier Valdez ◽  
Cinthia Peraza ◽  
Jin Hee Yoon ◽  
Zong Woo Geem
Keyword(s):  
Fuzzy System ◽  
Fuzzy Systems ◽  
Random Noise ◽  
Computing Time ◽  
Harmony Search ◽  
Computational Cost ◽  
Dynamic Parameter ◽  
Parameter Adaptation ◽  
Interval Type

Fuzzy systems have become a good solution to the problem of fixed parameters in metaheuristic algorithms, proving their efficiency when performing dynamic parameter adaptations using type-1 and type-2 fuzzy logic. However, the computational cost of type-2 fuzzy systems when using the continuous enhanced Karnik–Mendel (CKM) algorithm for type-reduction, when applied to control and optimization, is too high. Therefore, it is proposed to use an approximation to the CKM algorithm in the type-2 fuzzy system for adjusting the pitch adjustment rate (PArate) parameter in the original harmony search algorithm (HS). The main contribution of this article is to verify that the implementation of the proposed methodology achieves results that are equivalent to the interval type-2 fuzzy system with the CKM algorithm, but in less computing time and also allowing an efficient dynamic parameter adaptation. It is noteworthy that this method is relatively new in the area of metaheuristics algorithms so there is a current interest to work with this methodology. The proposed method was used in optimizing the antecedents and consequents for an interval type-2 fuzzy controller of direct current motor. Experimental results without noise and then with uniform random noise numbers (Gaussian noise) in the controller were obtained to verify that the implementation is efficient when compared to conventional and other existing methods.

scholarly journals A New Fuzzy Harmony Search Algorithm Using Fuzzy Logic for Dynamic Parameter Adaptation

Algorithms ◽  
2016 ◽  
Vol 9 (4) ◽  
pp. 69 ◽  
Author(s):  
Cinthia Peraza ◽  
Fevrier Valdez ◽  
Mario Garcia ◽  
Patricia Melin ◽  
Oscar Castillo
Keyword(s):  
Fuzzy Logic ◽  
Search Algorithm ◽  
Harmony Search ◽  
Dynamic Parameter ◽  
Harmony Search Algorithm ◽  
Parameter Adaptation
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