Desain Simulasi Robot Kesetimbangan Dua Roda Dengan Kecerdasan Buatan
Article Sidebar
Main Article Content
Abstract
Dalam penelitian dijelaskan salah satu metode alternatif analisa kontrol pada robot kesetimbangan dua roda dengan menggunakan progam simulasi. Program simulasi menggunakan software Matlab. Penelitian ini menghasilkan analisa simulasi kontrol, berupa analisa data sensor gyroscope, simulasi PID dan logika fuzzy. Pada simulasi PID nilai kestabilan didapat pada Kp=100, Ki=200, Kd=10, hasil analisa data gyroscope didapat nilai minimum pada 0,074616, nilai maksimum 0,110321, dengan nilai rata-rata 0,092469, standar deviasi 0,025247, jumlah data 0,184937. Penerapan logika fuzzy pada deteksi sudut dan pemberian nilai PWM, menghasilkan data kestabilan nilai konstanta PID. Penelitian ini diharapkan menjadi acuan pemberian nilai kontrol pada robot, dan untuk penelitian berikutnya dapat dikembangkan dengan menambahkan filter komplement atau kalman untuk menghasilkan kestabilan gerak robot.
Article Details
References
M. H. Weik, ‘manipulating industrial robot’, in Computer Science and Communications Dictionary, Boston, MA: Springer US, 2000, pp. 972–972.
V. D. Tugaev and V. Ya. Kulibaba, ‘Introduction of an industrial robot in a machine shop’, Metallurgist, vol. 30, no. 10, pp. 380–381, Oct. 1986, doi: 10.1007/BF00741414.
P. Frankovský, L. Dominik, A. Gmiterko, I. Virgala, P. Kurylo, and O. Perminova, ‘Modeling of Two-Wheeled Self-Balancing Robot Driven by DC Gearmotors’, Int. J. Appl. Mech. Eng., vol. 22, no. 3, pp. 739–747, Aug. 2017, doi: 10.1515/ijame-2017-0046.
C. Gonzalez, I. Alvarado, and D. M. L. Peña, ‘Low cost two-wheels self-balancing robot for control education’, IFAC-Pap., vol. 50, no. 1, pp. 9174–9179, Jul. 2017, doi: 10.1016/j.ifacol.2017.08.1729.
T. A. Mai, T. S. Dang, D. N. Anisimov, and E. Fedorova, ‘Fuzzy-PID Controller for Two Wheels Balancing Robot Based on STM32 Microcontroller’, in 2019 International Conference on Engineering Technologies and Computer Science (EnT), Moscow, Russia, Mar. 2019, pp. 20–24, doi: 10.1109/EnT.2019.00009.
S. Santoso and S. Mursyid, ‘KONTROL PROPORTIONAL INTEGRAL (PI) PADA ROBOT LINE FOLLOWER’, J. Sains Dan Inform., vol. 1, no. 1, pp. 10–10, Sep. 2017.
A. Odry and R. Fuller, ‘Comparison of Optimized PID and Fuzzy Control Strategies on a Mobile Pendulum Robot’, in 2018 IEEE 12th International Symposium on Applied Computational Intelligence and Informatics (SACI), Timisoara, May 2018, pp. 000207–000212, doi: 10.1109/SACI.2018.8440947.
Y. Xin, B. Xu, H. Xin, J. Xu, and L. Hu, ‘The Computer Simulation and Real-Time Control for the Inverted Pendulum System Based on PID’, in Communication Systems and Information Technology, vol. 100, M. Ma, Ed. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011, pp. 729–736.
H. Yun, J. Bang, J. Kim, and J. Lee, ‘High speed segway control with series elastic actuator for driving stability improvement’, J. Mech. Sci. Technol., vol. 33, no. 11, pp. 5449–5459, Nov. 2019, doi: 10.1007/s12206-019-1039-x.
C.-H. Huang, W.-J. Wang, and C.-H. Chiu, ‘Design and Implementation of Fuzzy Control on a Two-Wheel Inverted Pendulum’, IEEE Trans. Ind. Electron., vol. 58, no. 7, pp. 2988–3001, Jul. 2011, doi: 10.1109/TIE.2010.2069076.
Ş. Yıldırım and E. Arslan, ‘ODE (Open Dynamics Engine) based stability control algorithm for six legged robot’, Measurement, vol. 124, pp. 367–377, Aug. 2018, doi: 10.1016/j.measurement.2018.03.057.
F. Fahmizal, G. Setyawan, M. Arrofiq, and A. Mayub, ‘Logika Fuzzy Pada Robot Inverted Pendulum Beroda Dua’, J. Teknol. Inf. Dan Ilmu Komput., vol. 4, no. 4, p. 244, Dec. 2017, doi: 10.25126/jtiik.201744484.
S. Noga, ‘Kinematics and dynamics of some selected two-wheeled mobile robots’, Arch. Civ. Mech. Eng., vol. 6, no. 3, pp. 55–70, Jan. 2006, doi: 10.1016/S1644-9665(12)60241-6.
A. Chhotray, M. K. Pradhan, K. K. Pandey, and D. R. Parhi, ‘Kinematic Analysis of a Two-Wheeled Self-Balancing Mobile Robot’, p. 8.
L. A. Zadeh, ‘Fuzzy logic—a personal perspective’, Fuzzy Sets Syst., vol. 281, pp. 4–20, Dec. 2015, doi: 10.1016/j.fss.2015.05.009.
L. A. Zadeh, ‘Toward extended fuzzy logic—A first step’, Fuzzy Sets Syst., vol. 160, no. 21, pp. 3175–3181, Nov. 2009, doi: 10.1016/j.fss.2009.04.009.
M. K. Medynskaya, ‘Fuzzy set theory. The concept of fuzzy sets’, in 2015 XVIII International Conference on Soft Computing and Measurements (SCM), St. Petersburg, Russia, May 2015, pp. 30–31, doi: 10.1109/SCM.2015.7190402.
K. Sadegh-Zadeh, ‘Advances in fuzzy theory’, Artif. Intell. Med., vol. 15, no. 3, pp. 309–323, Mar. 1999, doi: 10.1016/S0933-3657(98)00060-8.
R. Bimarta, A. E. Putra, and A. Dharmawan, ‘Balancing Robot Menggunakan Metode Kendali Proporsional Integral Derivatif’, IJEIS Indones. J. Electron. Instrum. Syst., vol. 5, no. 1, p. 89, May 2015, doi: 10.22146/ijeis.7157.
G.-R. Yu, Y.-K. Leu, and H.-T. Huang, ‘PSO-based fuzzy control of a self-balancing two-wheeled robot’, in 2017 Joint 17th World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems (IFSA-SCIS), Otsu, Japan, Jun. 2017, pp. 1–5, doi: 10.1109/IFSA-SCIS.2017.8023296.
N. Cameron, ‘Robot Car’, in Arduino Applied, Berkeley, CA: Apress, 2019, pp. 467–497.
T. Anitha, G. Gopu, M. Nagarajapandian, and P. A. M. Devan, ‘Hybrid Fuzzy PID Controller for Pressure Process Control Application’, in 2019 IEEE Student Conference on Research and Development (SCOReD), Bandar Seri Iskandar, Malaysia, Oct. 2019, pp. 129–133, doi: 10.1109/SCORED.2019.8896276.
T. Pan and Y. Zhu, ‘Using Sensors with the Arduino’, in Designing Embedded Systems with Arduino, Singapore: Springer Singapore, 2018, pp. 45–100.
C.-F. Hsu and B.-K. Lee, ‘FPGA-based adaptive PID control of a DC motor driver via sliding-mode approach’, Expert Syst. Appl., vol. 38, no. 9, pp. 11866–11872, Sep. 2011, doi: 10.1016/j.eswa.2011.02.185.
I. Kecskés and P. Odry, ‘Optimization of PI and Fuzzy-PI Controllers on Simulation Model of Szabad(ka)-II Walking Robot’, Int. J. Adv. Robot. Syst., vol. 11, no. 11, p. 186, Nov. 2014, doi: 10.5772/59102.