Abstract
This work presents a comparison between three Mandani controllers (trial and error, optimized with Genetic Algorithms (GA), and Differential Evolution (DE)) and a traditional PID controller in the trajectory tracking application in the sagittal/frontal planes of an ankle, considering a disturbance that simulates the existence of an irregularity in the walking surface. The controller rulebase design uses only the error signals and the error derivative. For the implementation of the mentioned controllers, a co-simulation is presented using the MatLAb fuzzy Toolbox, Simulink PID block of Matlab, and Adams View. From the results obtained, a comparison is made to determine the computation time and the position error to choose the best one for the tracking the trajectories of an ankle prosthesis.
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References
Kwak, H., Kim, D., Park, G.: A new fuzzy inference technique for singleton type-2 fuzzy logic systems. Int. J. Adv. Robot. Syst. 9, 1–7 (2012)
Farfán-Martínez, R., Ruz-Hernández, J., Rullán-Lara, J.: Control Difuso Tipo 2 en el Enfoque de Lyapunov Aplicado a un Servomecanismo. In: Sexto Coloq. Interdiscip. Dr. - Univ. Pop. Autónoma del Estado Puebla, pp. 1–9 (2013)
Mamdani, E., Assilian, S.: An experiment in linguistic synthesis with a fuzzy logic controller. Int. J. Man Mach. Stud. 7(1), 1–13 (1975)
Takagi, T., Sugeno, M.: Fuzzy identification of systems and its applications to modeling and control. Readings Fuzzy Sets Intell. Syst. 1, 387–403 (1993)
Fernandez, C., Pantano, N., Godoy, S., Serrano, E., Scaglia, G.: Optimización de parámetros utilizando los métodos de Monte Carlo y Algoritmos Evolutivos. Aplicación a un controlador de seguimiento de trayectoria en sistemas no lineales. Revista Iberoamericana de Automática e Informática industrial 16, 89–99 (2019)
Mitra, S., Maulik, P., Chowdhury, S., Chowdhory, S.P.: ANFIS based automatic voltage regulator with hybrid learning algorithm. In: 2007 42nd International Universities Power Engineering Conference, vol. 1, pp. 397–401 (2007)
Mazzucco, M.M., Bolzan, A., Barcia, R.M., Machado, R.A.: Application of genetic algorithms to the adjustment of the supports of fuzzy sets in a mamdani controller. Braz. J. Chem. Eng. 17, 625–638 (2000)
A-Darraji, I., Kılıç, A., Kapucu, S.: Mechatronic design and genetic algorithm based MIMO fuzzy control of adjustable stiffness tendon driven finger. Mech. Sci. 9, 277–296 (2018)
Pishkenari, H.N., Mahboobi, S.H., Alasty, A.: Optimum synthesis of fuzzy logic controller for trajectory tracking by differential evolution. Sci. Iran. Trans. B Mech. Eng. 18, 261–267 (2011)
Xia, C., Guo, P., Shi, T., Wan, M.: Speed control of brushless DC motor using genetic algorithm based fuzzy controller. In: Proceedings of the 2004 International Conference on Intelligent Mechatronics and Automation, pp. 460–464 (2004)
Orlowska-Kowalska, T., Szabat, K.: Optimization of fuzzy-logic speed controller for DC drive system with elastic joints. IEEE Trans. Ind. Appl. 40(4), 1138–1144 (2004)
Ö-ztürk, N., Çelik, E.: Speed control of permanent magnet synchronous motors using fuzzy controller based on genetic algorithms. Elsevier Electr. Power Energy Syst. 43, 889–898 (2012)
Ashu, A., Sanjeev, K.A.: Design of fractional order PID controller for DC motor using evolutionary optimization techniques. WSEAS Trans. Syst. Control 9, 171–182 (2014)
Sung-Kwun, O., Wook-Dong, K., Witold, P.: Design of optimized cascade fuzzy controller based on differential evolution: simulation studies and practical insights. ELSEVIER Eng. Appl. Artif. Intell. 25, 520–532 (2012)
Nguyen, H.T.: A First Course in Fuzzy and Neural Control, vol. 1. Chapman & Hall/CRC, Boca Raton (2003)
Viladot Voegeli, A.: Anatomía funcional y biomecánica del tobillo y el pie. Rev. Española Reumatol. 30(9), 469–477 (2003)
Lippert, L.S.: Ankle Joint and Foot. Clinical kinesiology and Anatomy, vol. 5. F. A. Davis Co., Philadelphia (2011)
Jie, C., Sorin, S., Schneck, C.: The three-dimensional kinematics and flexibility characteristics of the human ankle and subtalar joints-part I: kinematics. Engineering 110(2), 364–373 (1988)
Begg, R.K., Sparrow, W.A.: Ageing effects on knee and ankle joint angles at key events. J. Med. Eng. Technol. 30(6), 382–389 (2006)
Parkinson, A., Balling, R., Hedengren, J.: Optimization Methods for Engineering Design. Applications and Theory, pp. 2–3. Brigham Young University, Provo (2013)
Téllez-Velázquez, A., et al.: A feasible genetic optimization strategy for parametric interval type-2 fuzzy logic systems. Int. J. Fuzzy Syst. 20, 1–23 (2017)
Cuevas Jiménez, E., Usuna Enciso, J., Olivia Navarro, D., Díaz Córtes, M.: OPTIMIZACIÓN Algoritmos programados con MATLAB. Alfaomega (2016)
Ogata, K.: Modern Control Engineering, 4th edn. Prentice Hall, Upper Saddle River (2002)
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Ambrocio-Delgado, R., Téllez-Velázquez, A., Lugo-González, E., Espinosa-Garcia, F. (2021). Optimized Fuzzy Control with Genetic Algorithms and Differential Evolution for Tracking the Trajectories of an Ankle Prosthesis. In: Batyrshin, I., Gelbukh, A., Sidorov, G. (eds) Advances in Soft Computing. MICAI 2021. Lecture Notes in Computer Science(), vol 13068. Springer, Cham. https://doi.org/10.1007/978-3-030-89820-5_26
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