Drive axis controller optimization of production machines based on dynamic models

The paper deals with the creation and implementation of a methodology for optimizing the parameters of cascade control of the machine tool axis drives. The first part presents the identification of a dynamic model of the axis based on experimental data from measuring the axis dynamics. The second pa...

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Published in:	International journal of advanced manufacturing technology Vol. 115; no. 4; pp. 1277 - 1293
Main Authors:	Halamka, Vojtěch, Moravec, Jan, Beneš, Petr, Neusser, Zdeněk, Koubek, Jan, Kozlok, Tomáš, Valášek, Michael, Šika, Zbyněk
Format:	Journal Article
Language:	English
Published:	London Springer London 01-07-2021 Springer Nature B.V
Subjects:	CAE) and Design Cascade control Computer-Aided Engineering (CAD Control theory Controllers Dynamic models Engineering Industrial and Production Engineering Machine tools Mechanical Engineering Media Management Optimization Original Article Parameter identification Speed control State space models Tuning Speed controller Speed controller parameters Machine tool Speed control loop Drive axis Cascade control Identification Optimization of cascade control Control quality criterions
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Abstract	The paper deals with the creation and implementation of a methodology for optimizing the parameters of cascade control of the machine tool axis drives. The first part presents the identification of a dynamic model of the axis based on experimental data from measuring the axis dynamics. The second part describes the controller model, selection of optimization objective functions, and optimization of constraint conditions. The optimization of controllers is tuned by simulation using identified state-space model. Subsequently, the optimization procedure is implemented on the identified model, and the found control parameters are used on a real machine tool linear axis with different loads. The implementation of the proposed complex procedure on a real horizontal machine tool proved the advantage of simultaneous tuning of all parameters using optimization methods. The strategy solves the problem of mutual interaction of all control law parameters disabling effective usability of gradual sequential tuning. The methodology was developed on a speed control loop, the tuning of which is usually the most difficult due to the close interaction with the dynamic properties of the machine mechanics. The whole procedure is also applicable to the position and current control loop.
AbstractList	The paper deals with the creation and implementation of a methodology for optimizing the parameters of cascade control of the machine tool axis drives. The first part presents the identification of a dynamic model of the axis based on experimental data from measuring the axis dynamics. The second part describes the controller model, selection of optimization objective functions, and optimization of constraint conditions. The optimization of controllers is tuned by simulation using identified state-space model. Subsequently, the optimization procedure is implemented on the identified model, and the found control parameters are used on a real machine tool linear axis with different loads. The implementation of the proposed complex procedure on a real horizontal machine tool proved the advantage of simultaneous tuning of all parameters using optimization methods. The strategy solves the problem of mutual interaction of all control law parameters disabling effective usability of gradual sequential tuning. The methodology was developed on a speed control loop, the tuning of which is usually the most difficult due to the close interaction with the dynamic properties of the machine mechanics. The whole procedure is also applicable to the position and current control loop.
Author	Kozlok, Tomáš Halamka, Vojtěch Valášek, Michael Koubek, Jan Moravec, Jan Neusser, Zdeněk Beneš, Petr Šika, Zbyněk
Author_xml	– sequence: 1 givenname: Vojtěch surname: Halamka fullname: Halamka, Vojtěch organization: Department of Mechanics Biomechanics and Mechatronics, Faculty of Mechanical Engineering, Czech Technical University in Prague – sequence: 2 givenname: Jan surname: Moravec fullname: Moravec, Jan organization: Department of Production Machines and Equipment, Faculty of Mechanical Engineering, Czech Technical University in Prague – sequence: 3 givenname: Petr surname: Beneš fullname: Beneš, Petr organization: Department of Mechanics Biomechanics and Mechatronics, Faculty of Mechanical Engineering, Czech Technical University in Prague – sequence: 4 givenname: Zdeněk surname: Neusser fullname: Neusser, Zdeněk organization: Department of Mechanics Biomechanics and Mechatronics, Faculty of Mechanical Engineering, Czech Technical University in Prague – sequence: 5 givenname: Jan surname: Koubek fullname: Koubek, Jan organization: Department of Production Machines and Equipment, Faculty of Mechanical Engineering, Czech Technical University in Prague – sequence: 6 givenname: Tomáš surname: Kozlok fullname: Kozlok, Tomáš organization: TOS Varnsdorf a. s – sequence: 7 givenname: Michael surname: Valášek fullname: Valášek, Michael organization: Department of Mechanics Biomechanics and Mechatronics, Faculty of Mechanical Engineering, Czech Technical University in Prague – sequence: 8 givenname: Zbyněk orcidid: 0000-0002-5492-7704 surname: Šika fullname: Šika, Zbyněk email: Zbynek.Sika@fs.cvut.cz organization: Department of Mechanics Biomechanics and Mechatronics, Faculty of Mechanical Engineering, Czech Technical University in Prague
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Keywords	Speed controller Speed controller parameters Machine tool Speed control loop Drive axis Cascade control Identification Optimization of cascade control Control quality criterions
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References	Khosravi M, Behrunani V, Myszkor P, Smith RS, Rupenyan A, Lygeros J (2021) Performance-driven cascade controller tuning with Bayesian optimization. IEEE Transactions on Industrial Electronics. https://doi.org/10.1109/TIE.2021.3050356 Gawronski WK (2004) Advanced structural dynamics and active control of structures, New York: Springer-Verlag New York. https://doi.org/10.1007/978-0-387-72133-0 Bubák A (2004) Increasing the dynamics and accuracy of machine tool feed axes. Dissertation, Czech Technical University in Prague (in Czech) Lee C-Y, Hwang S-H, Nam E, Min B-K (2020) Identification of mass and sliding friction parameters of machine tool feed drive using recursive least squares method. Int J Adv Manuf Technol 109(9):2831–2844. https://doi.org/10.1007/s00170-020-05858-x Farrage A, Uchiyama N (2020) Improvement of motion accuracy and energy consumption for industrial feed drive systems using adaptive sliding mode control. ISA Trans 106:382–391. https://doi.org/10.1016/j.isatra.2020.06.025 Wong WW-S, Erkorkmaz K (2010) Constrained identification of virtual CNC drives using a genetic algorithm. Int J Adv Manuf Technol 50(1):275–288. https://doi.org/10.1007/s00170-009-2496-7 Olgac N, Holm-Hansen BT (1994) A novel active vibration absorption technique: delayed resonator. J Sound Vib 176(1):93–104. https://doi.org/10.1006/jsvi.1994.1360 Kim H, Okwudire CE (2020) Simultaneous servo error pre-compensation and feedrate optimization with tolerance constraints using linear programming. Int J Adv Manuf Technol 109(3):809–821. https://doi.org/10.1007/s00170-020-05651-w Turhan MH, Tseng GWG, Erkorkmaz K, Fidan B (2020) Dynamic model identification for CNC machine tool feed drives from in-process signals for virtual process planning. Mechatronics 72:102445. https://doi.org/10.1016/j.mechatronics.2020.102445 Erkorkmaz K, Altintas Y (2001) High speed CNC system design. Part III: high speed tracking and contouring control of feed drives. Int J Mach Tools Manuf 41(11):1637–1658. https://doi.org/10.1016/S0890-6955(01)00004-9 Sencer B, Ishizaki K (2015) Smooth polynomial interpolation for point-to-point trajectories with vibration avoidance. IECON 2015 - 41st Annual Conference of the IEEE Industrial Electronics Society 002070-002075. https://doi.org/10.1109/IECON.2015.7392406 Msukwa MR, Nshama EW, Uchiyama N (2020) Contouring control based on reference adjustment and uncertainty compensator for precision motion of industrial feed drive systems. 2020 IEEE 29th International Symposium on Industrial Electronics (ISIE) 89-94. https://doi.org/10.1109/ISIE45063.2020.9152478 Kehne S, Fey M, Brecher C, Herfs W (2020) Control of the static and dynamic stiffness of feed drive axes by using an external force sensor. 2020 International Conference on Electrical Machines (ICEM) 1081-1085. https://doi.org/10.1109/ICEM49940.2020.9271036 Neugebauer R, Hofmann S, Hellmich A, Schlegel H (2011) Time-based method for the combined identification of velocity-loop parameters. Archive of Mechanical Engineering 58(2):175–184 Margolis BWL, Farouki RT (2020) Inverse dynamics toolpath compensation for CNC machines based on model predictive control. Int J Adv Manuf Technol 109(7):2155–2172. https://doi.org/10.1007/s00170-020-05719-7 Katayma T (2005) Subspace methods for system identification, London: Springer- Verlag. https://doi.org/10.1007/1-84628-158-X Chen C, Cheng C (2005) Integrated design for a mechatronic feed drive system of machine tools. Proceedings, 2005 IEEE/ASME International Conference on Advanced Intelligent Mechatronics 588-593. https://doi.org/10.1109/AIM.2005.1511046 Moravec J, Šika Z (2019) Tuning of position control loop of machine tools based on experimentally identified mechanical model. Computational mechanics 2019: Proceedings of computational Mechanics 2019: 35th conference with international participation 127-128 Halamka V (2019) Optimization of control of machine drive axis. Masters thesis, Czech Technical University in Prague (in Czech) Msukwa MR, Nshama EW, Uchiyama N (2020) Adaptive sliding mode control with feedforward compensator for energy-efficient and high-speed precision motion of feed drive systems. IEEE Access 8:43571–43581. https://doi.org/10.1109/ACCESS.2020.2977395 Erkorkmaz K, Altintas Y (2001) High speed CNC system design. Part II: modeling and identification of feed drives. Int J Mach Tools Manuf 41(10):1487–1509. https://doi.org/10.1016/S0890-6955(01)00003-7 Yang H, Wang Z, Zhang T, Du F (2020) A review on vibration analysis and control of machine tool feed drive systems. Int J Adv Manuf Technol 107:503–525. https://doi.org/10.1007/s00170-020-05041-2 Elbeheiry EM, Elmaraghy WH, Elmaraghy HA (2005) A structured linear quadratic gaussian based control design algorithm for machine tool controllers including both feed drive and process dynamics. J Vib Control 11(7):949–983. https://doi.org/10.1177/1077546305055542 Sekler P, Voß M, Verl A (2012) Model-based calculation of the system behavior of machine structures on the control device for vibration avoidance. Int J Adv Manuf Technol 58(9):1087–1095. https://doi.org/10.1007/s00170-011-3450-z Beneš P, Valášek M, Šika Z, Zavřel J, Pelikán J (2019) SHAVO control: the combination of the adjusted command shaping and feedback control for vibration suppression. Acta Mech 230(5):1891–1905. https://doi.org/10.1007/s00707-019-2363-z KhaderNModal parameters of a rotating multiple-disk-shaft system from simulated frequency response dataApplied and Computational Mechanics201481187198 Rebelein C, Vlacil J, Zaeh MF (2017) Modeling of the dynamic behavior of machine tools: influences of damping, friction, control and motion. Prod Eng 11(1):61–74. https://doi.org/10.1007/s11740-016-0704-5 Šika Z, Vyhlídal T, Neusser Z (2021) Two-dimensional delayed resonator for entire vibration absorption. J Sound Vib 500:116010. https://doi.org/10.1016/j.jsv.2021.116010 Moravec J (2014) Minimization of errors and irregular motion of machine tool feed drive axes. Dissertation, Czech Technical University in Prague (in Czech) Souček P (2004) Servomechanisms in production machines, Prague: ČVUT (in Czech) Houck C, Joines J, Kay A (1994) A genetic algorithm for function optimization: a MATLAB implementation, North California State University Chen S-Y, Chien Z-J, Wang W-Y, Chiang H-H (2020) Contour tracking control of a linear motors-driven X-Y-Y stage using auto-tuning cross-coupled 2DOF PID control approach. Appl Sci 10(24):9036. https://doi.org/10.3390/app10249036 Jamaludin IW, Wahab NA, Khalib NS, Sahlan S, Ibrahim Z, Rahmat MF (2013) N4SID and MOESP subspace identification methods. 2013 IEEE 9th International Colloquium on Signal Processing and its Applications 140-145. https://doi.org/10.1109/CSPA.2013.6530030 Poshtan J, Mojallali H (2020) Subspace system identification. Iranian Journal of Electrical and Electronic Engineering 1(1):11-17 Kraus K, Šika Z, Beneš P, Krivošej J, Vyhlídal T (2020) Mechatronic robot arm with active vibration absorbers. J Vib Control 26(13-14):1145–1156. https://doi.org/10.1177/1077546320918488 7160_CR17 7160_CR18 7160_CR19 N Khader (7160_CR20) 2014; 8 7160_CR2 7160_CR3 7160_CR4 7160_CR5 7160_CR6 7160_CR7 7160_CR8 7160_CR9 7160_CR21 7160_CR22 7160_CR23 7160_CR24 7160_CR25 7160_CR26 7160_CR1 7160_CR27 7160_CR28 7160_CR29 7160_CR30 7160_CR31 7160_CR10 7160_CR32 7160_CR11 7160_CR33 7160_CR12 7160_CR34 7160_CR13 7160_CR35 7160_CR14 7160_CR15 7160_CR16
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SubjectTerms	CAE) and Design Cascade control Computer-Aided Engineering (CAD Control theory Controllers Dynamic models Engineering Industrial and Production Engineering Machine tools Mechanical Engineering Media Management Optimization Original Article Parameter identification Speed control State space models Tuning
Title	Drive axis controller optimization of production machines based on dynamic models
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