Preview

Mekhatronika, Avtomatizatsiya, Upravlenie

Advanced search

Fuzziy Digital Filter for Robotic Manipulator Operation

https://doi.org/10.17587/mau.20.244-250

Abstract

In this article it is described the operation principle of a robotic manipulator ARMino device and the connection diagram of its electrical components. The device includes: An Arduino Mega control board, four servos, four potentiometers, a prototyping board, a computer. Turning the shafts on the potentiometer adjusts the position of the servo spindles. When the voltage on the potentiometer’s pin changes, the voltage at the analog inputs of the microcontroller changes. Then, in the microcontroller, the voltage is scaled to the value of the servo rotation angle. After that, the joints of the robotic manipulator are rotated. During the operation of the ARMino robotiс arm, a contact bounce problem appeared, significantly reducing the accuracy of positioning and the smooth movement of the ARMino joints. To solve this problem, a digital filter was developed. This article describes the digital filter working algorithm, which consists of four steps. One of the steps consists on finding the digital filter coefficients, which regulate the signal voltage level transmitted to the servo motors, and its transition process time which forms the signal edge. The main problem developing a digital filter is that the standard procedure of finding the digital filter coefficients, the coefficients are given by a recommended range of values, which complicates choosing from this range, a single value and transmitting it to the servos. To solve this problem, a fuzzy digital filter was developed, the algorithm of which consists of six steps. The first step determines the input variables degree of truth. The second step is to calculate the degrees of truth of the fuzzy rules preconditions. The third step is to calculate the degrees of truth of the fuzzy rules conclusions by using the process of finding the maximum values. The fourth step is the defuzzification stage in which a precise value of the fuzzy digital filter coefficient is calculated. The fifth step is the output voltage transmitted to the servos. In the sixth step, the output voltage in the microcontroller is converted to the angle value and the servo is given the command to rotate. This article presents numerical simulation of the fuzzy digital filter algorithm, using as an example the servo responsible of the ARMino base rotation. Experimental studies on the functioning of the fuzzy digital filter have been carried out, confirming the expediency of its use. The graphics of the transition process of the robotic manipulator base movement without and with the use of a digital filter are given.

About the Authors

M. V. Bobyr
South-West State University
Russian Federation

Corresponding autor: Bobyr Maxim V., Doctor of technical sciences, Professor of the department of computer technology, South-West State University, Kursk, 305040, Russian Federation



M. Yu. Luneva
South-West State University
Russian Federation
Kursk, 305040


C. A. Nolivos
South-West State University
Russian Federation
Kursk, 305040


References

1. Goritov A. N. Upravlenie robotom-manipulyatorom v srede s nepolnoj informatsiej (Managing a robotic manipulator in an environment with incomplete information), Mekhatronika, Avtomatizatsiya, Upravlenie, 2014, no. 6, pp. 19—23.

2. Nusratov O. K., Dzhafarov P. S., Zeynalov E. R., Mustafayeva A. M., Jafarov S. M. Аnaliticheskij metod sinteza regulyatora s nechetkoj TS-model’yu dlya upravleniya manipulyatorom robota s gibkim soedineniem (Analytical method for synthesizing a regulator with a fuzzy TS-model for operating a robotic manipulator with a flexible connection), Mekhatronika, Avtomatizatsiya, Upravlenie, 2011, no. 8, pp. 10—14 (in Russian).

3. Korotkov A. L., Korolev D. M., Kitaev N. A. Komplekt modulej mobil’noj robototekhniki dlya maketirovaniya i otladki algoritmov upravleniya (Set of modules of mobile robotics for prototyping and debugging of operation algorithms), Mekhatronika, Avtomatizatsiya, Upravlenie, 2018, vol. 19, no. 3, pp. 175—182 (in Russian).

4. Available at: http://electricalschool.info (date of access 08.05.2018).

5. Kondratiev N. O., Kuznetsov K. A., Trubin V. G. Input device based on a mechanical incremental encoder EC11, Automation and Software Engineering, 2017, no. 2, pp. 39—45 (in Russian).

6. Available at: http://iarduino.ru (date of access 16.05.18).

7. Available at: http://www.teh-lib.ru/cimpu/cifrovye-filtry. html (date of access 17.05.18)

8. Bobyr M. V. Аdaptivnaya sistema upravleniya mobil’nym robotom na osnove nechetkoj logiki (An adaptive control system for a mobile robot based on fuzzy logic), Mekhatronika, Avtomatizatsiya, Upravlenie, 2015, no. 7, pp. 449—455 (in Russian).

9. Yushchenko A. S. Metody nechetkoj logiki v upravlenii mobil’nymi manipulyatsionnymi robotami (Fuzzy logic methods in the management of mobile manipulation robots), Vestnik MSTU. Bauman, 2012, pp. 29—43 (in Russian).

10. Ho Pham Huy Anh, Kyoung Kwan Ahn Hybrid control of a pneumatic artificial muscle (PAM) robot arm using an inverse NARX fuzzy model, Engineering Applications of Artificial Intelligence, 2011, no. 24, pp. 697—716.

11. Bobyr M. V., Titov V. S., Milostnaya N. A. Prognozirovanie raboty mekhatronnykh sistem na osnove myagkikh nechetkikh baz znanij (Work prediction of mechatronic systems based on soft fuzzy knowledge data bases), Mekhatronika, Avtomatizatsiya, Upravlenie, 2014, no. 10, pp. 8—14 (in Russian).

12. Yuksel Hacioglu, Yunus Ziya Arslan, Nurkan Yagis MIMO fuzzy sliding mode controlled dual arm robot in load transportation, Journal of the Franklin Institute, 2011, no. 348, pp. 1886—1902.

13. Bobyr M. V., Milostnaya N. A., Kulabuhov S. A. A method of defuzzification based on the approach of areas’ ratio, Applied Soft Computing Journal, 2017, no. 10, pp. 19—32.

14. Bobyr M. V., Kulabukhov S. A., Milostnaya N. A. Teaching a neuro-fuzzy system based on the area difference method, Artificial intelligence and decision making, 2016, no. 4, pp. 15—26.

15. Barmak Baigzadehnoe, Zahra Rahmani, Alireza Khosravi, Behrooz Rezaie On position/force tracking control problem of cooperative robot manipulators using adaptive fuzzy backstepping approach, ISA Transactions, 2017, no. 70, pp. 432—446.


Review

For citations:


Bobyr M.V., Luneva M.Yu., Nolivos C.A. Fuzziy Digital Filter for Robotic Manipulator Operation. Mekhatronika, Avtomatizatsiya, Upravlenie. 2019;20(4):244-250. (In Russ.) https://doi.org/10.17587/mau.20.244-250

Views: 786


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


ISSN 1684-6427 (Print)
ISSN 2619-1253 (Online)