Abstract
This article focuses on the dynamic parameter adaptation in the harmony search algorithm using Type-1 and interval Type-2 fuzzy logic. In particular, this work focuses on the adaptation of the parameters of the original harmony search algorithm. At present there are several types of algorithms that can solve complex real-world problems with uncertainty management. In this case the proposed method is in charge of optimizing the membership functions of three benchmark control problems (water tank, shower, and mobile robot). The main goal is to find the best parameters for the membership functions in the controller to follow a desired trajectory. Noise experiments are performed to test the efficacy of the method.
Highlights
At present there are different techniques to solve optimization problems [1,2,3,4]
The proposed method is based on the original harmony search algorithm, which mimics the process of music improvisation, which has been widely used to solve different problems, as shown in [5,6,7,8,9]
This section presents the results obtained by optimizing the membership functions using the dynamic parameter adaptation with Type-1 and interval Type-2 fuzzy logic. This methodology was dynamic parameter adaptation with Type-1 and interval Type-2 fuzzy logic. This methodology was applied to the three benchmark problems shown in Section 4, where the objective is to follow a applied to the three benchmark problems shown in Section 4, where the objective is to follow a desired desired trajectory, and 30 experiments were carried out with disturbances and without disturbances trajectory, 30 experiments carried out (HS), with disturbances and without disturbances with the with theand original algorithm ofwere harmony search
Summary
At present there are different techniques to solve optimization problems [1,2,3,4]. This article focuses on the optimization of parameters to achieve the tracking of a trajectory applied to benchmark control problems. The proposed method is called fuzzy harmony search algorithm (FHS) that performs an adaptation of parameters with Type-1 and interval Type-2 fuzzy logic and it is used to optimize fuzzy tracking controllers so that they follow desired trajectories for benchmark control problems. In 1965 Zadeh proposed the concepts of a fuzzy set in [20], fuzzy logic in [21], and the concept of a membership functions in [22] Based on these concepts, complex problems can be solved by using fuzzy rules to represent an expert knowledge of a problem in a more natural way using linguistic variables. The main contribution of this paper is the optimization of the values of the membership function of the fuzzy system of the three benchmark control problems presented and the stability obtained in the trajectory tracking of each case. This article is organized as follows: Section 2 gives a description of the original harmony search algorithm, Section 3 shows the fuzzy harmony search algorithm with dynamic parameter adaptation, Section 4 describes the benchmark control problems, Section 5 describes the simulation results, Section 6 shows the statistical comparison, and Section 7 presents conclusions
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