Optimasi Parameter Membership Function pada Sistem Kendali Robot Balancing Menggunakan Algoritma Genetika
Keywords:
robot balancing, logika fuzzy, algoritma genetika, optimasi parameter, kontrol cerdas.Abstract
Penelitian ini mengembangkan sistem kendali robot balancing berbasis logika fuzzy dengan optimasi parameter menggunakan algoritma genetika. Sistem dirancang menggunakan mikrokontroler ESP32 dan sensor MPU6050 untuk mengukur sudut kemiringan dan kecepatan sudut, dengan motor DC sebagai aktuator. Parameter fungsi keanggotaan berbentuk segitiga (a, b, c) dioptimasi secara offline melalui algoritma genetika dengan fungsi fitness yang mempertimbangkan settling time (ts), overshoot (Mp), dan steady-state error (ess). Hasil simulasi menunjukkan peningkatan performa signifikan: settling time berkurang 52.2% (dari 2.3s ke 1.1s), overshoot turun 36% (dari 7.5% ke 4.8%), dan error steady-state berkurang 50% (dari 1.8° ke 0.9%). Analisis phase portrait membuktikan stabilitas global sistem dalam rentang ±90°, sementara heatmap 3D mengungkap hubungan nonlinier yang smooth antara variabel input-output. Implementasi real-time pada prototipe robot berhasil memvalidasi hasil simulasi dengan frekuensi sampling 100 Hz. Penelitian ini memberikan kontribusi metodologi optimasi desain kontroler cerdas yang dapat diaplikasikan pada sistem dinamis nonlinier lainnya.
References
Santoso, B. Hariadi, R. Hartayu, et al., "Pengaruh Penyesuaian Parameter Membership Function pada Sistem Kendali Robot Balancing Berbasis Fuzzy Logic", JEETech, vol. 7, no. 2, pp. 45-60, 2024.
Goldberg, D.E., Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley, 1989.
Odry, Á., et al., "Fuzzy control of self-balancing robots: A control laboratory project", Computer Applications in Engineering Education, vol. 28, no. 3, pp. 512-535, 2020.
Ren, G., et al., "Design of Interval Type-2 Fuzzy Controllers for Active Magnetic Bearing Systems", IEEE/ASME Transactions on Mechatronics, vol. 25, no. 5, pp. 2449-2459, 2020.
Torres-Salinas, H., et al., "Fuzzy Logic and Genetic-Based Algorithm for a Servo Control System", Micromachines, vol. 13, no. 4, 2022.
Huang, H., et al., "An Applied Type-3 Fuzzy Logic System: Practical Matlab Simulink and M-Files for Robotic, Control, and Modeling Applications", Symmetry, vol. 15, no. 2, 2023.
Noor, N.M., et al., "Study the Performance of Two-Wheeled Balancing Mobile Robot Using Fuzzy PD Controller", Journal of Mechanical Engineering, vol. 46, pp. 164-174, 2023.
Fahmizal, et al., "Logika Fuzzy pada Robot Inverted Pendulum Beroda Dua", Jurnal Teknologi Informasi dan Ilmu Komputer, vol. 4, no. 4, pp. 244-252, 2017.
Kumari, S., and Swain, S.K., "Optimal control based PID tuning for control of four quadrant chopper fed DC motor", 2018 Technologies for Smart-City Energy Security and Power (ICSESP), 2018.
Chen, X., et al., "Fuzzy Logic Based Logical Query Answering on Knowledge Graphs", Proceedings of the AAAI Conference on Artificial Intelligence, vol. 36, no. 4, 2022.
Almadi, A.I.M., et al., "A Fuzzy-Logic Approach Based on Driver Decision-Making Behavior Modeling and Simulation", Sustainability, vol. 14, no. 14, 2022.
Shao, S., et al., "DCNN-Based Multi-Signal Induction Motor Fault Diagnosis", IEEE Transactions on Instrumentation and Measurement, vol. 69, no. 6, pp. 2658-2669, 2020.
Anitha, T., et al., "Hybrid Fuzzy PID Controller for Pressure Process Control Application", 2019 IEEE Student Conference on Research and Development (SCOReD), 2019.
Fan, A., et al., "Energy management strategies and comprehensive evaluation of parallel hybrid ship based on improved fuzzy logic control", IEEE Transactions on Transportation Electrification, 2023.
Karakurt, H.B., and Koçak, C., "Increasing quality of service in wireless local area networks through fuzzy logic based feedback control method", Wireless Networks, vol. 29, no. 5, pp. 2217-2233, 2023.
Díaz-Téllez, J., et al., "ROS-based Controller for a Two-Wheeled Self-Balancing Robot", Journal of Robotics and Control, vol. 4, no. 4, 2023.
Hendriansyah, H., et al., "Increasing the Efficiency of Electrical Load Calculations Using the Gauss-Seidel Method with Fuzzy Logic", Circuit: Jurnal Ilmiah Pendidikan Teknik Elektro, vol. 8, no. 2, 2024.
Hartayu, R., et al., "Desain Simulasi Robot Kesetimbangan Dua Roda Dengan Kecerdasan Buatan", Jurnal Sains dan Informatika, vol. 6, no. 2, pp. 175-182, 2020.
Santoso, et al., "Design and Build Two Wheel Balancing Robot Simulation with Fuzzy PID", International Conference on Advanced Engineering and Technology, 2024.
Mitchell, M., An Introduction to Genetic Algorithms. MIT Press, 1998.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Santoso Santoso, Ratna Hartayu, Kurnia Paranita Kartika Riyanti, Ahmad Ridho’i, Wahyu Setyo Pambudi, M Ary Heryanto
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
