Abstract
Mechanical vibrations represent one of the key issues in the development of direct drives with a complex mechanical structure, i.e., with non-stiff connections between motor and driven mechanisms and with variable moments of inertia. A solution for motion control in relation to a direct drive, with highly dynamic performance, coupled with multi-mass mechanical load is proposed in the chapter. Due to high resonance frequencies that are difficult to be actively damped by the control system, an original solution is proposed, which is based on damping the highest resonance frequencies with a specially selected and tuned filter, leaving the damping of the lowest frequencies to the control system. In the first part of this chapter, the identification method is presented, along with robust notch filters, which are tuned for the whole range of parameter variability. Due to variable moment of inertia, two robust control methods are proposed in the second and third parts of this chapter: one is based on an adaptive neural speed controller, while the other is based on a terminal sliding mode control (SMC). The online learning neural speed controller is based on the resilient back propagation (RPROP) algorithm. A modified terminal sliding control law is proposed for a system with delays and unmodelled dynamics. The advantages of both solutions are verified on the basis of experiment investigations.
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Janiszewski D (2011) Real-time control of drive with elestic coupling based on motor position measured only. In: IEEE international symposium on industrial electronics (ISIE), pp 1931–1936
Szabat K, Than T-V, Kaminski M (2015) A modified fuzzy luenberger observer for a two-mass drive system. IEEE Trans Ind Inform 11(2):531–539
Brock S, Łuczak D (2011) Speed control in direct drive with non-stiff load. In: Proceedings IEEE international symposium on industrial electronics (ISIE), Gdańsk, Poland, pp 1937–1942
Kazmierkowski MP, Orlowska-Kowalska T (2002) NN state estimation and control in converter-fed induction motor drives. In: Soft computing in industrial electronics, vol 110. Springer International Publishing, Heidelberg, pp 45–94 (ch 2)
Pajchrowski T, Zawirski K, Nowopolski K (2014) A neural speed controller trained on-line by means of modified RPROP algorithm. IEEE Trans Ind Inform PP(99):1
Bartoszewicz A, Nowacka-Leverton A (2009) Time-varying sliding modes for second and third order systems. Springer International Publishing, New York
Liu J, Wang X (2011) Advanced sliding mode control for mechanical systems. Springer International Publishing, Beijing
Utkin V, Lee H (2006) Chattering problem in sliding mode control systems. IEEE international workshop on variable structure systems, VSS 2006, pp 346–350
Sabanovic A (2011) Variable structure systems with sliding modes in motion control—a survey. IEEE Trans Ind Inform 7(2):212–223
Yu X, Man Z (1996) On finite time mechanism: terminal sliding modes. In: Proceedings of variable structure systems, VSS ’96, pp 164–167
Feng Y, Yu X, Man Z (2002) Non-singular terminal sliding mode control of rigid manipulators. Automatica 38(12):2159–2167
Brock S (2011) Sliding mode control of a permanent magnet direct drive under non-linear friction. COMPEL Int J Comput Math Electr Electron Eng 30(3):853–863
Luczak D (2014) Mathematical model of multi-mass electric drive system with flexible connection. In: 19th international conference on methods and models in automation and robotics (MMAR), pp 590–595
Saarakkala SE, Hinkkanen M (2015) Identification of two-mass mechanical systems using torque excitation: design and experimental evaluation. IEEE Trans Ind Appl 51(5):4180–4189
Luczak D (2012) Tunable digital filter structures for resonant frequency effect reduction in direct drive. In: 8th international symposium on communication systems, networks digital signal processing (CSNDSP), Poznan, Poland, pp 1–6
Riedmiller M, Braun H (1993) A direct adaptive method for faster backpropagation learning: the RPROP algorithm. In: IEEE international conference on neural networks, vol 1. 28 March–1 April, pp 586–591
Pajchrowski T, Zawirski K, Nowopolski K (2015) Application of adaptive neural controller for drive with elastic shaft and variable moment of inertia. In: 17th conference on power electronics and applications, EPE’15-ECCE Europe, Geneva, Switzerland, 8–10 Sept
Brock S (2013) Hybrid PI sliding mode position and speed controller for direct drive. In: Mechatronics. Springer International Publishing, Switzerland, pp 741–748
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Appendix
Appendix
Data of investigated drive
Parameters of PMSM | Unit | Value |
---|---|---|
Minimum moment of inertia Maximum moment of inertia Torque constant Rated load torque Rated value of speed Rated current in q axis Rated voltage | kg m2 kg m2 Nm/A Nm rev/s A V | 0.75 5.83 17.5 50 2.41 2.85 310 |
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Brock, S., Łuczak, D., Pajchrowski, T., Zawirski, K. (2017). Selected Methods for a Robust Control of Direct Drive with a Multi-mass Mechanical Load. In: Kabziński, J. (eds) Advanced Control of Electrical Drives and Power Electronic Converters. Studies in Systems, Decision and Control, vol 75. Springer, Cham. https://doi.org/10.1007/978-3-319-45735-2_4
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DOI: https://doi.org/10.1007/978-3-319-45735-2_4
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