Research Article Optimal Position Fuzzy Control of an Underactuated Robotic Finger Francisco J. Espinosa Garcia , 1,2 Esther Lugo-Gonz ´ alez , 3 Arturo Tell´ ez-Vel´ azquez , 4 Manuel Arias-Montiel , 3 and Marco Ceccarelli 2 1 Postgraduate Division, Technological University of the Mixteca, Huajuapan de Le´ on 69000, Mexico 2 LARM 2, University of Rome Tor Vergata, Rome 00133, Italy 3 Institute of Electronics and Mechatronics, Technological University of the Mixteca, Huajuapan de Le´ on 69000, Mexico 4 Institute of Computing, Technological University of the Mixteca, Huajuapan de Le´ on 69000, Mexico Correspondence should be addressed to Manuel Arias-Montiel; mam@mixteco.utm.mx Received 18 March 2022; Revised 27 May 2022; Accepted 28 June 2022; Published 20 July 2022 Academic Editor: Ardashir Mohammadzadeh Copyright © 2022 Francisco J. Espinosa Garcia et al. is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 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 op- timization 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. e results show that the maximum error between the proposed and obtained trajectories is 3.1352E − 04 rad. 1. Introduction Currently, control development for robotic hands continues to be a topic of interest as researchers seek to recreate human hand interaction with their environment when developing prototypes and their interaction with the environment. is objective is difficult to achieve due to the challenging nature of controlling robotic hands, as they are relatively complex mechatronic systems, which allow the user to hold, ma- nipulate, and make use of different objects and tools. As a possible solution, some researchers have focused on im- proving control tasks in order to generate a robust grasp to reliably hold any object. In addition, the selection criteria of actuators are an important factor because the size, weight, and torque are variables that must be considered. Generally, the control systems have a closed-loop structure, since they seek to reduce errors so that the hand finger can maintain a specific desired position [1, 2], by using pneumatic [3–5] and touch [6–8] sensors. In the literature, the most common control schemes are the proportional-integral-derivative (PID) control [9–11] and fuzzy control [12–14]. Controllers based on fuzzy logic are an alternative solution that does not require a mathematical model such as the PID [15]. A fuzzy logic controller (FLC) is a heuristic approach composed of a rules base proposed by the designer. e FLC is a nonlinear system with a knowledge based on fuzzy If-en rules, and in most cases, the fuzzy rules are proposed by an expert who knows the process. In order to generate an output, mem- bership functions are used to specify the degree of mem- bership based on inputs. FLC must have a flexible behavior to adapt to various situations, as well as being robust to maintain the state of the desired output. e implementation of FLC is fairly common for solving problems, where (a) the systems are partially defined, (b) systems with variables that cannot be measured, and (c) system with large disturbances [12, 14, 16]. e principal fuzzy systems are Mandani and Hindawi Mathematical Problems in Engineering Volume 2022, Article ID 2091337, 12 pages https://doi.org/10.1155/2022/2091337