Optimal Fuzzy Controller Design for Autonomous Robot Path Tracking Using Population-Based Metaheuristics

Mancilla, Alejandra; García-Valdéz, Mario; Castillo, Oscar; Merelo, J. J.

doi:10.3390/sym14020202

Cited by 22 publications

(4 citation statements)

References 46 publications

(40 reference statements)

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“…Sharma et al extends diagnostic approach to investigate the medical diagnosis [28]. Mancilla et al designed fuzzy controller for optimization of autonomous robot path tracking [24]. In the sequence, Gupta et al reviewed fuzzy logic based systems in the medical diagnosis [13].…”

Section: Related Workmentioning

confidence: 99%

Generalized Fuzzy Technique and Its Consistent Assessment in Multi-criteria Decision Making of Medical Decisions

Kumar,

Sharma

2024

Preprint

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Multi-criteria decision making (MCDM) is introduced using trapezoidal vague numbers (TVNs) in medicine. Initially concepts of centroid and signed distance are generalized for TVNs. We also provide some desirable properties of the proposed distance measure. The decision making involves the medical diagnostic problem to reduce the vagueness and non-specificity from its environment. In this MCDM, each symptom is classified into some criteria. States of the patients, weights for the existing symptoms are assumed as vague point entries and relations of symptom criteria and diseases are considered using trapezoidal vague number entries. The usefulness of the developed approach is when it shows its capability and validity of the delivery. A numerical computation is illustrated with the whole procedure of the decision making. To show the capability and distinctness of the proposed methodology, a comparative discussion for outcomes is given with pre existing method. Present method coincides with existing fuzzy based method for the initial diagnosis while possibility differences for patient P1 and patient P2 range from 1–16.3% by the method based on existing traditionally fuzzy approach and in present approach these differences range from 2.15–7.46%. In the present approach, addition to the membership, another function called non membership is taken that contributes the upper bound of membership. Between these two memberships the hesitation part is dealt sophisticatedly. Also consideration of trapezoidal vague number as membership grade than the point estimation handles the blur cloud of association effectively.

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Section: Related Workmentioning

confidence: 99%

Generalized Fuzzy Technique and Its Consistent Assessment in Multi-criteria Decision Making of Medical Decisions

Kumar,

Sharma

2024

Preprint

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“…In previous work [14], we established that tuning the MFs of fuzzy controllers using population-based metaheuristics demands the extensive use of computational resources. This demand stems from establishing the fitness of all candidate solutions, which requires running several simulations [15,16] for each candidate; this is a problem inherent to population-based algorithms. However, because evolutionary algorithms evaluate candidate solutions in isolation; they are a perfect match for their parallel execution.…”

Section: Introductionmentioning

confidence: 99%

Distributed and Asynchronous Population-Based Optimization Applied to the Optimal Design of Fuzzy Controllers

et al. 2023

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Designing a controller is typically an iterative process during which engineers must assess the performance of a design through time-consuming simulations; this becomes even more burdensome when using a population-based metaheuristic that evaluates every member of the population. Distributed algorithms can mitigate this issue, but these come with their own challenges. This is why, in this work, we propose a distributed and asynchronous bio-inspired algorithm to execute the simulations in parallel, using a multi-population multi-algorithmic approach. Following a cloud-native pattern, isolated populations interact asynchronously using a distributed message queue, which avoids idle cycles when waiting for other nodes to synchronize. The proposed algorithm can mix different metaheuristics, one for each population, first because it is possible and second because it can help keep total diversity high. To validate the speedup benefit of our proposal, we optimize the membership functions of a fuzzy controller for the trajectory tracking of a mobile autonomous robot using distributed versions of genetic algorithms, particle swarm optimization, and a mixed-metaheuristic configuration. We compare sequential versus distributed implementations and demonstrate the benefits of mixing the populations with distinct metaheuristics. We also propose a simple migration strategy that delivers satisfactory results. Moreover, we compare homogeneous and heterogenous configurations for the populations’ parameters. The results show that even when we use random heterogeneous parameter configuration in the distributed populations, we obtain an error similar to that in other work while significantly reducing the execution time.

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“…To solve these challenging problem, researchers have proposed many methods, including the analytical method [15], Jacobian-based method [16], neural network method [17][18][19], numerical method [20,21], and swarm intelligence algorithm [22,23]. The analytical method [24] directly uses math formulas to describe the relationship between the end point and the driving joints based on the basic structure of the robot.…”

Section: Introductionmentioning

confidence: 99%

A Review and Comparative Study of Differential Evolution Algorithms in Solving Inverse Kinematics of Mobile Manipulator

Qiao

2023

Symmetry

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Mobile manipulator robots have become important pieces of equipment due to the high mobility of mobile subsystems and the high flexibility of manipulator subsystems. Considering the increasing degrees of freedom and the need to avoid singular locations, one of the most challenging problems is solving the inverse kinematics problem of mobile manipulator robots (IKMM). Of all the popular optimization algorithms, the differential evolution (DE) algorithm is the most effective method for quickly solving the IKMM problem with sufficient solutions. Currently, many strategies have been proposed for DE algorithms to improve the performance of solving mathematical problems; some symmetry strategies or symmetry functions have been introduced to DE algorithms. However, the effects of various DE algorithms on solving the actual IKMM lack a comprehensive explanation. Therefore, we divide various DE algorithms into three categories considering the control parameter selection and compare the specific optimization of various DE algorithms. Then, we compare the performance of various DE algorithms when solving the inverse kinematics problems of mobile manipulators with different degrees of freedom. Considering the effectiveness and the speed of the DE algorithm on the IKMM problem, we determine the best DE algorithm by comparing the error and time required to reach 100 random mission points and tracking the typical trajectories. Finally, the best-performing DE method is further improved by studying the selection of fundamental parameters in the best DE algorithm. Valuable conclusions are obtained from these experimental simulations, which can help with choosing an algorithm that is suitable for solving the inverse kinematics problem of mobile manipulator robots in practice.

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Optimal Fuzzy Controller Design for Autonomous Robot Path Tracking Using Population-Based Metaheuristics

Cited by 22 publications

References 46 publications

Generalized Fuzzy Technique and Its Consistent Assessment in Multi-criteria Decision Making of Medical Decisions

Generalized Fuzzy Technique and Its Consistent Assessment in Multi-criteria Decision Making of Medical Decisions

Distributed and Asynchronous Population-Based Optimization Applied to the Optimal Design of Fuzzy Controllers

A Review and Comparative Study of Differential Evolution Algorithms in Solving Inverse Kinematics of Mobile Manipulator

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