Investigation of Steel Slabs Marker Robotic Arm Control Parameters in Noise and Disturbance Absence/Presence
الموضوعات :
1 - Department of Mechanical Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran
الکلمات المفتاحية: Marker Robot, Steel Slabs, Robot Dynamics, Robot Control,
ملخص المقالة :
At Mobarakeh Steel Company, the writing on steel slabs is currently performed by manual labor, which has several negative consequences. To address this issue, a project has been initiated to implement robots instead. A robotic arm with five degrees of freedom (three related to the arm and two related to the wrist) has been developed to write letters and numbers on the steel slabs. This article details the design, dynamics, and control of the robotic arm. The dynamics were solved using the Newton-Euler method, while the robot's control was calculated using the computed torque method. Additionally, the robustness of the designed controller against noise and disturbances was evaluated. The effectiveness of the controller's performance was demonstrated through simulations. Furthermore, the robot's path was examined to ensure it did not cross any singular points. The results indicated that the robot's passage through its singular point was monitored, and it was confirmed that the robot did not cross the singular point.
[1] Goel, R. and Gupta, P. 2020. Robotics and industry. A Roadmap to Industry 4.0, Smart Production, Sharp Business and Sustainable Development. Springer-IEREK, 157-169. doi: 10.1007/978-3-030-14544-6.
[2] Day, C.-P. 2018. Robotics in the industry-their role in intelligent manufacturing. Engineering. 4(4): 440-445. doi: 10.1016/j.eng.2018.07.012.
[3] Bragança, S., Costa, E. and Castellucci, I. and Arezes, P.M. 2019. Occupational and Environmental Safety and Health. A brief overview of the use of collaborative robots in industry 4.0: Human role and safety. Springer. doi: 10.1007/978-3-030-14730-368.
[4] Tantawi, K.H., Sokolov, A. and Tantawi, O. 2019. Advances in industrial robotics: From industry 3.0 automation to industry 4.0 collaboration. Proceedings of 4th Technology Innovation Management and Engineering Science International Conference (TIMES-iCON). doi:10.1109/TIMES-iCON47539.2019.9024658.
[5] Javaid, M., Haleem, A., Singh, R.P. and Suman, R. 2021. Substantial capabilities of robotics in enhancing industry 4.0 implementation. Cognitive Robotics. 1(1): 58-75. doi: 10.1016/j.cogr.2021.06.001.
[6] Kerber, E., Heimig, T., Stumm, S., Oster, L., Brell-Cokcan, S. and Reisgen, U. 2018. Towards robotic fabrication in joining of steel. Proc. ISARC. Proceedings of the International Symposium on Automation and Robotics in Construction. doi: 10.22260/ISARC2018/0062.
[7] Hollerbach, J.M. 1979. Understanding Manipulator Control by Synthesizing Human Handwriting. Springer.
[8] Suh, S.-H., Lee, J.-J., Choi, Y. J. and Lee, S. K. 1993. A prototype integrated robotic painting system: Software and hardware development. Proceedings of 1993 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'93). doi:10.1109/IROS.1993.583145.
[9] Antonio, J.K. 1994. Optimal trajectory planning for spray coating. Proceedings of the IEEE international conference on robotics and automation. doi: 10.1109/ROBOT.1994.351125.
[10] Asakawa, N. and Takeuchi, Y. 1997. Teachingless spray-painting of sculptured surfaces by an industrial robot. Proc. Proceedings of international conference on robotics and automation. doi: 10.1109/ROBOT.1997.619061.
[11] Hertling, P., Hog, L., Larsen, R., Perram, J.W. and Petersen, H.G. 1996. Task curve planning for painting robots. I. Process modeling and calibration. IEEE Transactions on Robotics and Automation. 12(2): 324-330. doi: 10.1109/70.488951.
[12] Mahdieh, M.S. 2023. Improving surface integrity of electrical discharge machined ultra-fined grain al-2017 by applying rc-type generator. Proceedings of the Institution of Mechanical Engineers. Part E: Journal of Process Mechanical Engineering. 1(1): 1-9. doi: 10.1177/09544089231202329.
[13] Mahdieh, M.S. and Esteki, M.R. 2022. Feasibility investigation of hydroforming of dental drill body by fem simulation. Journal of Modern Processes in Manufacturing and Production. 11(2): 71-83. doi: 20.1001.1.27170314.2022.11.2.7.5
[14] Mahdieh, M.S. and Monjezi, A. 2022. Investigation of an innovative cleaning method for the vertical oil storage tank by fem simulation. Iranian Journal of Materials Forming. 9(4): 5-12. doi: 10.22099/ijmf.2022.43842.1229
[15] Mahdieh, M.S., Nazari, F., Mussa, T.A. and Salehi, H.T. 2023. A study on stamping of airliner’s tail connector part through fem simulation. Journal of Simulation and Analysis of Novel Technologies in Mechanical Engineering. 15(3): 5-13.
[16] Mahdieh, M.S., Zadeh, H.M.B. and Reisabadi, A.Z. 2023. Improving surface roughness in barrel finishing process using supervised machine learning. Journal of Simulation and Analysis of Novel Technologies in Mechanical Engineering. 15(2): 5-15. doi: 20.1001.1.27834441.2023.15.2.1.0.
[17] Mahdieh, M. S., Nazari, F. and Khairullah, A.R. 2024. A study on the effects of different pad materials on brake system performance of a high-capacity elevator by fem simulation. International Journal of Advanced Design and Manufacturing Technology. 65(4): 61-68. doi: 10.30486/ADMT.2023.873808.
[18] Vakili Sohrforozani, A., Farahnakian, M., Mahdieh, M.S., Behagh, A.M. and Behagh, O. 2019. A study of abrasive media effect on deburring in barrel finishing process. Journal of Modern Processes in Manufacturing and Production. 8(3): 27-39. doi:10.30495/ADMT.2020.1889912.1165.
[19] Vakili Sohrforozani, A., Farahnakian, M., Mahdieh, M.S., Behagh, A.M. and Behagh, O. 2020. Effects of abrasive media on surface roughness in barrel finishing process. ADMT Journal. 13(3): 75-82. doi:10.30495/ADMT.2020.1889912.1165.
[20] Foley, F., O’Donoghue, C. and Walsh, J. 2023. Optimizing the implementation of a robotic welding system. Journal of Modern Processes in Manufacturing and Production. 12(2): 39-52. dor: 20.1001.1.27170314.2023.12.2.3.8.
[21] Hasanabadi, A. 2022. Path optimization of moving object in presence of obstacles using messy genetic algorithm for n-dimensional space. Journal of Modern Processes in Manufacturing and Production. 11(3): 51-60. dor: 20.1001.1.27170314.2022.11.3.5.5.
[22] Deylami, A. 2021. Stability of robust lyapunov based control of flexible-joint robots using voltage control strategy revisited. Journal of Modern Processes in Manufacturing and Production. 10(4): 13-25. dor: 20.1001.1.27170314.2021.10.4.1.6.
[23] Mallahi Kolahi, P. and Mosayebi, M. 2021. Optimal trajectory planning for an industrial mobile robot using optimal control theory. Journal of Modern Processes in Manufacturing and Production. 10(3): 25-34. dor: 20.1001.1.27170314.2021.10.3.4.7.
[24] Deylami, A. 2021. Tracking control of robots revisited based on taylor series and asymptotic expansion. Journal of Modern Processes in Manufacturing and Production. 10(2): 63-70. dor: 20.1001.1.27170314.2021.10.2.6.7.
[25] Moshayedi, A.J., Xu, G., Liao, L. and Kolahdooz, A. 2021. Gentle survey on mir industrial service robots: Review & design. Journal of Modern Processes in Manufacturing and Production. 10(1): 31-50. dor: 20.1001.1.27170314.2021.10.1.3.2.
[26] Craig, J.J. 2006. Introduction to Robotics: Mechanics and Control, 4th edition, Pearson.
[27] Westervelt, E.R., Grizzle, J.W., Chevallereau, C., Choi, J.H. and Morris, B. 2018. Feedback Control of Dynamic Bipedal Robot Locomotion. CRC Press. doi: 10.1109/TAC.2008.918096.