Bir SCARA Robot Manipülatörün Konum Kontrolü için SMC Denetleyici Parametrelerini Belirlemeye Yönelik Arı Algoritması Yaklaşımı
Year 2022,
Issue: 33, 267 - 273, 31.01.2022
Sinan İlgen
,
Akif Durdu
,
Erdi Gülbahçe
,
Abdullah Çakan
,
Mete Kalyoncu
Abstract
Bu çalışmada, SCARA tip bir robot manipülatörün konum kontrolü, Arı algoritması kullanılarak parametre optimizasyonuna dayanan kayan kipli kontrol (SMC) yöntemi kullanılarak incelenmiştir. SCARA manipülatörün modellenmesi MSC Adams'ta yapılmış ve kontrol uygulaması MATLAB yazılımında gerçekleştirilmiştir. SCARA manipülatörün sayısal modeli, MSC Adams yazılımı üzerinde sanal bir prototip kurularak elde edilmiştir. Ayrıca, oluşturulan sanal prototipin doğruluğunu kontrol etmek için SCARA manipülatörün ters kinematik denklemleri Matlab/Simulink yazılımı kullanılarak oluşturulmuştur. Ek olarak, daha iyi sonuçlar elde etmek için SMC kontrolcünün parametreleri Arı Algoritması ile optimize edilmiştir. Ardından MSC Adams-MATLAB eş zamanlı simülasyonu kullanılarak sanal prototip üzerinde sistemin kontrolcü performansı incelenmiştir. Ayrıca, parametre optimizasyonu için bir başka meta-sezgisel yöntem olan Genetik Algoritma kullanılmış ve elde edilen sonuçlar ile Arı Algoritmasının performansı karşılaştırılmıştır. Sonuç olarak, Arı Algoritmasının robotik sistemlerin kontrolü ile ilgili çalışmalarda kullanılabilir olduğu gözlemlenmiştir.
References
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- Demydyuk, М., & Hoshovs’ka, N. (2019). Parametric Optimization of the Transport Operations of a Two-Link Manipulator. Journal of Mathematical Sciences, 238(2), 174-188.
- Erdogmus, P., & Toz, M. (2012). Heuristic optimization algorithms in robotics. In Serial and Parallel Robot Manipulators-Kinematics, Dynamics, Control and Optimization (pp. 311-338): InTech Publisher.
- Go, S. J., & Lee, M. C. (2001). Design of a fuzzy-sliding mode controller for a SCARA robot to reduce chattering. Journal of Mechanical Science and Technology, 15(3), 339-350.
- İlgen, S. (2019). Robot manipülatörlerin performanslarına yönelik kontrol uygulamaları. Yüksek Lisans Tezi, Lisansüstü Eğitim Enstitüsü, Konya Teknik Üniversitesi.
- İlgen, S., Durdu, A., Gülbahçe, E., & Çakan, A. (2018). Sliding Mode Control of a Two-link Robot Manipulator Using Adams & Matlab Software. Paper presented at the 2018 6th International Conference on Control Engineering & Information Technology (CEIT).
- Loucif, F., Kechida, S., & Sebbagh, A. (2020). Whale optimizer algorithm to tune PID controller for the trajectory tracking control of robot manipulator. Journal of the Brazilian Society of Mechanical Sciences Engineering, 42(1), 1-11.
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- Ogulmuş, A. S., Çakan, A., & Tınkır, M. (2016). Modeling And Position Control Of Scara Type 3D Printer. International Journal Of Scientific Technology Research, 5, 140-143.
- Ölgün, M., & Tilki, U. (2020). Neural Network Based Sliding Mode Controller with Genetic Algorithm for Two Link Robot Manipulator. European Journal of Science and Technology, 120-129. doi:10.31590/ejosat.araconf16
- Oliveira, J., Oliveira, P. M., Boaventura-Cunha, J., & Pinho, T. (2017). Chaos-based grey wolf optimizer for higher order sliding mode position control of a robotic manipulator. Nonlinear Dynamics, 90(2), 1353-1362.
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- Pham, D. T., Ghanbarzadeh, A., Koç, E., Otri, S., Rahim, S., & Zaidi, M. (2006). The bees algorithm—a novel tool for complex optimisation problems. In Intelligent production machines and systems (pp. 454-459): Elsevier.
- Qiang, L., Xuhua, S., Ting, L., Xiaoxia, C., & Jianpei, Z. (2019). Multi-objective optimization based self tuning robot manipulator Controller. Paper presented at the 2019 Chinese Control And Decision Conference (CCDC).
- Raheem, F. A., & Hameed, U. I. (2019). Heuristic D* Algorithm Based on Particle Swarm Optimization for Path Planning of Two-Link Robot Arm in Dynamic Environment. Al-Khwarizmi Engineering Journal, 15(2), 108-123.
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- Saygılı, Ç. (2006). Design and animation of a Scara type robot. Master thesis of Mechanical Eng. Dept. of Selçuk University,
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- Sen, M. A., & Kalyoncu, M. (2016). Optimal tuning of a LQR controller for an inverted pendulum using the bees algorithm. J Autom Control Eng, 4(5).
- Soltanpour, M. R., & Khooban, M. H. (2013). A particle swarm optimization approach for fuzzy sliding mode control for tracking the robot manipulator. Nonlinear Dynamics, 74(1), 467-478.
- Surapong, N., & Mitsantisuk, C. (2016). Position and force control of the SCARA robot based on disturbance observer. Procedia Computer Science, 86, 116-119.
- Tarmizi, M. R. (2014). Design and modelling of 6 DOF revolute robot using fuzzy PID controller. Universiti Tun Hussein Onn Malaysia,
- Urrea, C., Cortés, J., & Pascal, J. (2016). Design, construction and control of a SCARA manipulator with 6 degrees of freedom. Journal of applied research and technology, 14(6), 396-404.
- Urrea, C., & Kern, J. (2012). Modeling, simulation and control of a redundant SCARA-type manipulator robot. International Journal of Advanced Robotic Systems, 9(2), 58.
- Wang, N., Liu, J., Wei, S., Xu, Z., & Zhang, X. (2014). The control system design of a SCARA robot. Paper presented at the International Conference on Intelligent Robotics and Applications.
- Zhou, Z., Wang, C., Zhu, Z., Wang, Y., & Yang, D. (2019). Sliding mode control based on a hybrid grey-wolf-optimized extreme learning machine for robot manipulators. Optik, 185, 364-380.
The Bees Algorithm Approach to Determining SMC Controller Parameters for the Position Control of a SCARA Robot Manipulator
Year 2022,
Issue: 33, 267 - 273, 31.01.2022
Sinan İlgen
,
Akif Durdu
,
Erdi Gülbahçe
,
Abdullah Çakan
,
Mete Kalyoncu
Abstract
In this study, position control of a SCARA robot manipulator is investigated using the sliding mode control (SMC) method based on parameter optimization using The Bees Algorithm. The modeling the SCARA manipulator is conducted in MSC Adams and the control implementation is carried out in MATLAB software. The numerical model of the SCARA manipulator is acquired by setting up a virtual prototype on MSC Adams software. In addition, the inverse kinematic equations of the SCARA manipulator are formed using Matlab/Simulink software in order to check the accuracy of the created virtual prototype. In addition, the SMC controller parameters are optimized with The Bees Algorithm to get better results. Then, the control performance of the system is examined on the virtual prototype using MSC Adams-MATLAB co-simulation. Moreover, Genetic Algorithm, another meta-heuristic method, is used for parameter optimization and the performance of The Bees Algorithm is compared with the results obtained. As a result, it has been observed that The Bees Algorithm can be used in studies related to the control of robotic systems.
References
- Beşkirli, M., & Tefek, M. F. (2019). Parçacık Sürü Optimizasyon Algoritması Kullanılarak Optimum Robot Yolu Planlama. European Journal of Science and Technology, 201-213. doi:10.31590/ejosat.637832
- Bruzzone, L., & Bozzini, G. (2011). A statically balanced SCARA-like industrial manipulator with high energetic efficiency. Meccanica, 46(4), 771-784.
- Demydyuk, М., & Hoshovs’ka, N. (2019). Parametric Optimization of the Transport Operations of a Two-Link Manipulator. Journal of Mathematical Sciences, 238(2), 174-188.
- Erdogmus, P., & Toz, M. (2012). Heuristic optimization algorithms in robotics. In Serial and Parallel Robot Manipulators-Kinematics, Dynamics, Control and Optimization (pp. 311-338): InTech Publisher.
- Go, S. J., & Lee, M. C. (2001). Design of a fuzzy-sliding mode controller for a SCARA robot to reduce chattering. Journal of Mechanical Science and Technology, 15(3), 339-350.
- İlgen, S. (2019). Robot manipülatörlerin performanslarına yönelik kontrol uygulamaları. Yüksek Lisans Tezi, Lisansüstü Eğitim Enstitüsü, Konya Teknik Üniversitesi.
- İlgen, S., Durdu, A., Gülbahçe, E., & Çakan, A. (2018). Sliding Mode Control of a Two-link Robot Manipulator Using Adams & Matlab Software. Paper presented at the 2018 6th International Conference on Control Engineering & Information Technology (CEIT).
- Loucif, F., Kechida, S., & Sebbagh, A. (2020). Whale optimizer algorithm to tune PID controller for the trajectory tracking control of robot manipulator. Journal of the Brazilian Society of Mechanical Sciences Engineering, 42(1), 1-11.
- Nadir, B., & Mohammed, O. (2018). Optimization the Trajectories of Robot Manipulators Along Specified Task. International Journal of Intelligent Engineering Systems, 11(1), 11-19.
- Ogulmuş, A. S., Çakan, A., & Tınkır, M. (2016). Modeling And Position Control Of Scara Type 3D Printer. International Journal Of Scientific Technology Research, 5, 140-143.
- Ölgün, M., & Tilki, U. (2020). Neural Network Based Sliding Mode Controller with Genetic Algorithm for Two Link Robot Manipulator. European Journal of Science and Technology, 120-129. doi:10.31590/ejosat.araconf16
- Oliveira, J., Oliveira, P. M., Boaventura-Cunha, J., & Pinho, T. (2017). Chaos-based grey wolf optimizer for higher order sliding mode position control of a robotic manipulator. Nonlinear Dynamics, 90(2), 1353-1362.
- Pham, D., Ghanbarzadeh, A., Koc, E., Otri, S., Rahim, S., & Zaidi, M. J. T. N., Manufacturing Engineering Centre, Cardiff University, UK. (2005). The bees algorithm.
- Pham, D., & Kalyoncu, M. (2009). Optimisation of a fuzzy logic controller for a flexible single-link robot arm using the Bees Algorithm. Paper presented at the 2009 7th IEEE International Conference on Industrial Informatics.
- Pham, D., Koç, E., Kalyoncu, M., & Tınkır, M. (2008). Hierarchical PID controller design for a flexible link robot manipulator using the bees algorithm. Methods, 25, 32.
- Pham, D. T., Ghanbarzadeh, A., Koç, E., Otri, S., Rahim, S., & Zaidi, M. (2006). The bees algorithm—a novel tool for complex optimisation problems. In Intelligent production machines and systems (pp. 454-459): Elsevier.
- Qiang, L., Xuhua, S., Ting, L., Xiaoxia, C., & Jianpei, Z. (2019). Multi-objective optimization based self tuning robot manipulator Controller. Paper presented at the 2019 Chinese Control And Decision Conference (CCDC).
- Raheem, F. A., & Hameed, U. I. (2019). Heuristic D* Algorithm Based on Particle Swarm Optimization for Path Planning of Two-Link Robot Arm in Dynamic Environment. Al-Khwarizmi Engineering Journal, 15(2), 108-123.
- Şahin, Y. (2006). PID control application of trajectory control of a Scara type robot. Mater Thesis, Dept. Mechanical Eng. Dept., Selçuk University.
- Saygılı, Ç. (2006). Design and animation of a Scara type robot. Master thesis of Mechanical Eng. Dept. of Selçuk University,
- Sen, M. A., & Kalyoncu, M. (2015). Optimisation of a PID controller for an inverted pendulum using The Bees Algorithm. Paper presented at the Applied Mechanics and Materials.
- Sen, M. A., & Kalyoncu, M. (2016). Optimal tuning of a LQR controller for an inverted pendulum using the bees algorithm. J Autom Control Eng, 4(5).
- Soltanpour, M. R., & Khooban, M. H. (2013). A particle swarm optimization approach for fuzzy sliding mode control for tracking the robot manipulator. Nonlinear Dynamics, 74(1), 467-478.
- Surapong, N., & Mitsantisuk, C. (2016). Position and force control of the SCARA robot based on disturbance observer. Procedia Computer Science, 86, 116-119.
- Tarmizi, M. R. (2014). Design and modelling of 6 DOF revolute robot using fuzzy PID controller. Universiti Tun Hussein Onn Malaysia,
- Urrea, C., Cortés, J., & Pascal, J. (2016). Design, construction and control of a SCARA manipulator with 6 degrees of freedom. Journal of applied research and technology, 14(6), 396-404.
- Urrea, C., & Kern, J. (2012). Modeling, simulation and control of a redundant SCARA-type manipulator robot. International Journal of Advanced Robotic Systems, 9(2), 58.
- Wang, N., Liu, J., Wei, S., Xu, Z., & Zhang, X. (2014). The control system design of a SCARA robot. Paper presented at the International Conference on Intelligent Robotics and Applications.
- Zhou, Z., Wang, C., Zhu, Z., Wang, Y., & Yang, D. (2019). Sliding mode control based on a hybrid grey-wolf-optimized extreme learning machine for robot manipulators. Optik, 185, 364-380.