Designing a controller on the basis of a fuzzy output system for guiding a link of a robotic manipulator arm

Authors: Goldinova K.A.
Published in issue: #11(16)/2017
DOI: 10.18698/2541-8009-2017-11-193

Category: Mechanical Engineering and Machine Science | Chapter: Robots, Mechatronics, and Robotic Systems

Keywords: simulation, fuzzy logic, drive, rules, controller, control system, robotic manipulator arm, fuzzification
Published: 30.10.2017

As an applied science, fuzzy logic boasts a wide range of applications and helps to solve a large number of control-related problems. In control engineering, fuzzy simulation makes it possible to obtain more relevant results as compared to those based on traditional control algorithms. We suggest a way to design a control system for the elbow joint of a robotic arm, based on fuzzy logic. We list the advantages of this method, its fundamentals and a specific application example. In order to assess the performance of the method, we present the results of simulating a robotic arm in the SimMechanics library before and after introducing a fuzzy controller.


[1] Zadeh L.A. The concept of a linguistic variable and its application to approximate reasoning Elsevier, 1973. (Russ. ed.: Ponyatie lingvisticheskoy peremennoy i ego primenenie dlya prinyatiya priblizhennykh resheniy. Moscow, Mir publ., 1976, 165 p.).

[2] Kudinov Yu.I. Fuzzy control systems. Izvestiya Akademii nauk. Tekhnicheskaya kibernetika, 1990, no. 5, pp. 196–206.

[3] Lokhin V.M. Intellektual’nye sistemy avtomaticheskogo upravleniya [Intelligence systems of automatic control]. Moscow, Fizmatlit publ., 2001, 576 p.

[4] Asai K., Vatada D., Ivai p. Prikladnye nechetkie sistemy [Fuzzy application systems]. Moscow, Mir publ., 1993, 368 p.

[5] Boshlyakov A.A., Rubtsov V.I. Synthesis of fuzzy regulator for servo drive. Inzhenernyy zhurnal: nauka i innovatsii [Engineering Journal: Science and Innovation], 2013, no. 8. URL: http://engjournal.ru/catalog/pribor/robot/936.html.

[6] Leonenkov A.V. Nechetkoe modelirovanie v srede MATLAB i fuzzyTECH [Fuzzy programming in MATLAB and fuzzyTECH]. Sankt-Petersburg, BKhV-Peterburg publ., 2005, 736 p.

[7] Zakharov V.I., Ul’yanov V.S. Fuzzy models of intelligent industrial regulators and control systems: research organization, engineering economics, and application aspects. Izvestiya Akademii nauk. Tekhnicheskaya kibernetika, 1992, no. 5, pp. 171–196.

[8] MATLAB. Available at: http://matlab.ru/ (accessed 28 June 2017).