Disturbance observer–based prescribed adaptive control for rate-dependent hysteretic systems
Yangming Zhang
School of Automation Science and Electrical Engineering, Beihang University, Beijing, China
Search for more papers by this authorCorresponding Author
Peng Yan
School of Automation Science and Electrical Engineering, Beihang University, Beijing, China
Key Laboratory of High-efficiency and Clean Mechanical Manufacture, Ministry of Education, School of Mechanical Engineering, Shandong University, Jinan, China
Correspondence
Peng Yan, School of Automation Science and Electrical Engineering, Beihang University, Beijing 100083, China.
Email: [email protected]
Search for more papers by this authorYangming Zhang
School of Automation Science and Electrical Engineering, Beihang University, Beijing, China
Search for more papers by this authorCorresponding Author
Peng Yan
School of Automation Science and Electrical Engineering, Beihang University, Beijing, China
Key Laboratory of High-efficiency and Clean Mechanical Manufacture, Ministry of Education, School of Mechanical Engineering, Shandong University, Jinan, China
Correspondence
Peng Yan, School of Automation Science and Electrical Engineering, Beihang University, Beijing 100083, China.
Email: [email protected]
Search for more papers by this authorSummary
In this paper, a disturbance observer–based prescribed adaptive control approach is proposed for ultra-high-precision tracking of a class of hysteretic systems with both high-order matched and mismatched disturbances. Considering the adverse effects of asymmetric and rate-dependent hysteresis nonlinearities, a polynomial-based rate-dependent Prandtl-Ishlinskii model is first developed to characterize their behaviors, and inverse model based compensation is also constructed. Furthermore, the resulting inverse compensation error is analytically given, and a novel disturbance observer with adaptive control techniques is designed to handle the bounded disturbances, including the inverse compensation error and the high-order matched and mismatched disturbances. Comparative experiments on a multiaxis nano servo stage are finally conducted to demonstrate the effectiveness of the proposed control architecture, where substantial performance improvement over existing results are achieved on various tracking scenarios.
REFERENCES
- 1Salapaka SM, De T, Sebastian A. A robust control based solution to the sample-profile estimation problem in fast atomic force microscopy. Int J Robust Nonlinear Control. 2005; 15(16): 821-837.
- 2Devasia S, Eleftheriou E, Moheimani SOR. A survey of control issues in nanopositioning. IEEE Trans Control Syst Technol. 2007; 15(5): 802-823.
- 3Zou Q, Devasia S. Preview-based optimal inversion for output tracking: application to scanning tunneling microscopy. IEEE Trans Control Syst Technol. 2004; 12(3): 375-386.
- 4Mynderse JA, Chiu GTC. Two-degree-of-freedom hysteresis compensation for a dynamic mirror actuator. IEEE/ASME Trans Mechatron. 2016; 21(1): 29-37.
- 5Chen X, Su CY, Fukuda T. Adaptive control for the systems preceded by hysteresis. IEEE Trans Autom Control. 2008; 53(4): 1019-1025.
- 6Cao Y, Chen XB. A survey of modeling and control issues for piezo-electric actuators. J Dyn Syst Meas Control. 2015; 137: 014001-1-014001-13.
- 7Fleming AJ, Moheimani SOR. A grounded-load charge amplifier for reducing hysteresis in piezoelectric tube scanners. Rev Sci Instrum. 2005; 76(7):073707-1-073707-5.
- 8Zhou J, Wen CY, Zhang Y. Adaptive backstepping control of a class of uncertain nonlinear systems with unknown backlash-like hysteresis. IEEE Trans Autom Control. 2004; 49(10): 1751-1759.
- 9Leang KK, Devasia S. Design of hysteresis-compensating iterative learning control for piezo-positioners: application to atomic force microscopes. Mechatronics. 2006; 16(3-4): 141-158.
- 10Chen Z, Zheng J, Zhang HT, Ding H. Tracking of piezoelectric actuators with hysteresis: a nonlinear robust output regulation approach. Int J Robust Nonlinear Control. 2016. https://doi.org/10.1002/rnc.3702
- 11Song G, Zhao J, Zhou X, De Abreu-García JA. Tracking control of a piezoceramic actuator with hysteresis compensation using inverse Preisach model. IEEE/ASME Trans Mechatron. 2005; 10(2): 198-209.
- 12Webb GV, Lagoudas DC, Kurdila AJ. Hysteresis modeling of SMA actuators for control applications. J Intell Mater Syst Struct. 1998; 9(6): 432-448.
- 13Krejc̆í P, Kuhnen K. Inverse control of systems with hysteresis and creep. IEE P-Contr Theory Appl. 2001; 148(3): 185-192.
- 14Edardar M, Tan X, Khalil HK. Design and analysis of sliding mode controller under approximate hysteresis compensation. IEEE Trans Control Syst Technol. 2015; 23(2): 598-608.
- 15Liu S, Su CY, Li Z. Robust adaptive inverse control of a class of nonlinear systems with Prandtl-Ishlinskii hysteresis model. IEEE Trans Autom Control. 2014; 59(8): 2170-2174.
- 16Gu GY, Zhu LM, Su CY. Modeling and compensation of asymmetric hysteresis nonlinearity for piezoceramic actuators with a modified Prandtl-Ishlinskii model. IEEE Trans Ind Electron. 2014; 61(3): 1583-1595.
- 17Li Z, Su CY, Chen X. Modeling and inverse adaptive control of asymmetric hysteresis systems with applications to magnetostrictive actuator. Control Eng Practice. 2014; 33: 148-160.
- 18Li P, Yan F, Ge C, et al. A simple fuzzy system for modelling of both rate-independent and rate-dependent hysteresis in piezoelectric actuators. Mech Syst Signal Proc. 2013; 36(1): 182-192.
- 19Tan UX, Latt WT, Widjaja F, Shee CY, Riviere CN, Ang WT. Tracking control of hysteretic piezoelectric actuator using adaptive rate-dependent controller. Sens Actuator A-Phys. 2009; 150(1): 116-123.
- 20Gan J, Zhang X. Modeling of rate-dependent hysteresis in piezoelectric actuators based on a modified Prandtl-Ishlinskii model. Int J Appl Electromagn Mech. 2015; 49(4): 557-565.
- 21Leang KK, Zou Q, Devasia S. Feedforward control of piezoactuators in atomic force microscope systems. IEEE Control Syst Mag. 2009; 29(1): 70-82.
- 22Shieh HJ, Hsu CH. An adaptive approximator-based backstepping control approach for piezoactuator-driven stages. IEEE Trans Ind Electron. 2008; 55(4): 1729-1738.
- 23Bechlioulis CP, Rovithakis GA. Adaptive control with guaranteed transient and steady state tracking error bounds for strict feedback systems. Automatica. 2009; 45(2): 532-538.
- 24Bechlioulis CP, Rovithakis GA. Prescribed performance adaptive control for multi-input multi-output affine in the control nonlinear systems. IEEE Trans Autom Control. 2010; 55(5): 1220-1226.
- 25Brokate M, Sprekels J. Hysteresis and Phase Transitions. New York, NY:Springer-Verlag; 1996.
- 26Oh JH, Bernstein DS. Piecewise linear identification for the rate-independent and rate-dependent Duhem hysteresis models. IEEE Trans Autom Control. 2007; 52(3): 576-582.
- 27Xiao S, Li Y. Modeling and high dynamic compensating the rate-dependent hysteresis of piezoelectric actuators via a novel modified inverse Preisach model. IEEE Trans Control Syst Technol. 2013; 21(5): 1549-1557.
- 28Ang WT, Khosla PK, Riviere CN. Feedforward controller with inverse rate-dependent model for piezoelectric actuators in trajectory-tracking applications. IEEE/ASME Trans Mechatron. 2007; 12(2): 134-142.
- 29Al Janaideh M, Rakheja S, Su CY. Experimental characterization and modeling of rate-dependent hysteresis of a piezoceramic actuator. Mechatronics. 2009; 19(5): 656-670.
- 30Al Janaideh M, Krejc̆í P. Inverse rate-dependent Prandtl-Ishlinskii model for feedforward compensation of hysteresis in a piezomicropositioning actuator. IEEE/ASME Trans Mechatron. 2013; 18(5): 1498-1507.
- 31Liu Y, Zhao Z, He W. Boundary control of an axially moving system with high acceleration/deceleration and disturbance observer. J Franklin Inst. 2017; 354(7): 2905-2923.
- 32Liu Y, Zhao Z, He W. Stabilization of an axially moving accelerated/decelerated system via an adaptive boundary control. ISA Trans. 2016; 64: 394-404.
- 33He W, Ge SS. Vibration control of a nonuniform wind turbine tower via disturbance observer. IEEE/ASME Trans Mechatron. 2015; 20(1): 237-244.
- 34Liu Y, Zhao Z, He W. Boundary control of an axially moving accelerated/decelerated belt system. Int J Robust Nonlinear Control. 2016; 26(17): 3849-3866.
- 35Polycarpou MM, Ioannou PA. A robust adaptive nonlinear control design. Automatica. 1996; 32(3): 423-427.
- 36Epitropakis MG, Tasoulis DK, Pavlidis NG, Plagianakos VP, Vrahatis MN. Enhancing differential evolution utilizing proximity-based mutation operators. IEEE Trans Evol Comput. 2011; 15(1): 99-119.