Implementation of Sliding Surface Moving Anfis Based Sliding Mode Control to Rotary Inverted Pendulum

Author:

AYDIN Muhammet1ORCID,YAKUT Oğuz2ORCID

Affiliation:

1. FIRAT ÜNİVERSİTESİ

2. FIRAT UNIVERSITY

Abstract

This study covers the control of the pendulum angle by taking into account the dynamic equations and motor dynamics of the rotary inverted pendulum system, with the help of state variables in the Matlab program, by using the sliding mode control method with sliding surface moving and the adaptive neural fuzzy inference system together. The sliding mode control method with a changing sliding surface is a part of the control structure. The slope of the sliding surface was calculated using the adaptive neural fuzzy inference technique. The optimum values of the coefficients in the adaptive neural-fuzzy inference system structure have been calculated by genetic algorithm. The finding of the coefficients, the sum of the squares of the errors chosen as the objective function. The input of the adaptive neural fuzzy inference system structure consists of the error of the pendulum and the derivative of the error of the pendulum. The gradient of the sliding surface of the sliding mode control structure is the output of the adaptive neural fuzzy inference system structure. According to the findings, the pendulum angle achieved the appropriate reference value after 1.5 seconds, with an error of around zero. It obtained that the engine torque value reaches up to 50 Nm. From here, it is seen that the motor torque values used in practical applications and the motor torque values as a result of this study overlap.

Publisher

Igdir University

Reference22 articles.

1. Altinoz, OT, Yilmaz, AE, Weber, GW, 2010. Chaos Particle Swarm Optimized Pid Controller for the Inverted Pendulum System. Second International Conference on Engineering Optimization, 6-9 September 2010, Lisbon, Portugal.

2. Awtar, S, King, N, Allen, T, Bang, I, Hagan, M, Skidmore, D, Craig, K, 2002. Inverted Pendulum Systems: Rotary and Arm-Driven-a Mechatronic System Design Case Study. Mechatronics, 12 (2): 357-370.

3. Aydin, M, Yakut, O, Tutumlu, H, 2019. Implementation of the Network-Based Moving Sliding Mode Control Algorithm to the Rotary Inverted Pendulum System. Journal of Engineering and Technology, 3 (1): 32-41.

4. Aydin, M, Yakut, O, 2022. Application of Fuzzy Sliding Mode Control with Moving Sliding Surface to Rotary Inverted Pendulum. Journal of Advanced Research in Natural and Applied Sciences, 8(3).

5. Bogdanov, A, 2004. Optimal Control of a Double Inverted Pendulum on a Cart. Health and Science University Technical Report. CSE-04-006, Oregon Graduate Institute School of Science and Engineering, Oregon, United States of America.

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