Model-based nonlinear control of hydraulic servo systems: Challenges, developments and perspectives

doi:10.1007/s11465-018-0464-3

Front. Mech. Eng.

2018, Vol. 13

Issue (2) : 179-210 https://doi.org/10.1007/s11465-018-0464-3

REVIEW ARTICLE

Model-based nonlinear control of hydraulic servo systems: Challenges, developments and perspectives

Jianyong YAO(

)

School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China

Download: PDF(1266 KB) HTML
Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks

Abstract

Hydraulic servo system plays a significant role in industries, and usually acts as a core point in control and power transmission. Although linear theory-based control methods have been well established, advanced controller design methods for hydraulic servo system to achieve high performance is still an unending pursuit along with the development of modern industry. Essential nonlinearity is a unique feature and makes model-based nonlinear control more attractive, due to benefit from prior knowledge of the servo valve controlled hydraulic system. In this paper, a discussion for challenges in model-based nonlinear control, latest developments and brief perspectives of hydraulic servo systems are presented: Modelling uncertainty in hydraulic system is a major challenge, which includes parametric uncertainty and time-varying disturbance; some specific requirements also arise ad hoc difficulties such as nonlinear friction during low velocity tracking, severe disturbance, periodic disturbance, etc.; to handle various challenges, nonlinear solutions including parameter adaptation, nonlinear robust control, state and disturbance observation, backstepping design and so on, are proposed and integrated, theoretical analysis and lots of applications reveal their powerful capability to solve pertinent problems; and at the end, some perspectives and associated research topics (measurement noise, constraints, inner valve dynamics, input nonlinearity, etc.) in nonlinear hydraulic servo control are briefly explored and discussed.

Keywords hydraulic servo system adaptive control robust control nonlinear friction disturbance compensation repetitive control noise alleviation constraint control

Corresponding Author(s): Jianyong YAO

Just Accepted Date: 13 September 2017 Online First Date: 06 November 2017 Issue Date: 16 March 2018

Cite this article:

Jianyong YAO. Model-based nonlinear control of hydraulic servo systems: Challenges, developments and perspectives[J]. Front. Mech. Eng., 2018, 13(2): 179-210.

URL:

https://academic.hep.com.cn/fme/EN/10.1007/s11465-018-0464-3
https://academic.hep.com.cn/fme/EN/Y2018/V13/I2/179

Fig.1 The schematic diagram of the hydraulic servo system. (a) Servo-valve controlled double rod hydraulic cylinder; (b) servo-valve controlled bidirectional hydraulic motor

Fig.2 Tracking performance of VFPI and FBL for 1°–20 Hz motion. (a) Trajectory tracking; (b) tracking errors of FBL and VFPI

Tab.1 Performances summary with 1° amplitude testing

Fig.3 Tracking performance under PID controller

Fig.4 Tracking performance under ARC controller

Fig.5 Tracking performance of ARISE for normal motion

Fig.6 Tracking errors of ARC and PID for normal motion

Fig.7 Parameter estimation of ARISE for normal motion

Fig.8 Tracking performance of ARISE for slow motion

Fig.9 Tracking errors of ARC and PID controllers for slow motion

Fig.10 Tracking performance of ARISE for fast motion

Fig.11 Tracking errors of ARC and PID controllers for fast motion

Fig.12 Tracking errors of APC, ARC, FLC and PID for normal motion

Tab.2 Performance indices for normal tracking case

Fig.13 Parameter estimation of APC for normal motion

Tab.3 Performance indices for fast tracking case

Fig.14 Tracking errors of ARC and APC controllers for fast motion

Tab.4 Performance indices in normal tracking case

Fig.15 Tracking performance of ALuGre for normal motion

Fig.16 Tracking errors of the other three controllers for normal motion

Tab.5 Performance indices in slow tracking case

Fig.17 Tracking performance of ALuGre for slow motion

Fig.18 Tracking errors of the other three controllers for slow motion

Fig.19 Tracking errors of OFRC and PI controllers in normal case. (a) Tracking errors during the whole period in normal case; (b) tracking errors during the last two cycles in normal case

Tab.6 Performance indices in normal case

Fig.20 Tracking errors of OFRC and PI controllers in slow tracking case. (a) Tracking errors during the whole period in slow tracking case; (b) comparison of tracking errors

Tab.7 Performance indices in slow tracking case

Fig.21 Tracking errors of OFRC in fast tracking case with disturbance

Fig.22 Tracking errors with z₁(0)= ?1

Fig.23 Velocity output with z₁(0)= ?1

Fig.24 Acceleration output with z₁(0)= ?1

Fig.25 Dead-zone effects and its smooth inverse

Fig.26 Multi-valued effects of an example of hysteresis

1	Merritt H E. Hydraulic Control Systems. New York: Wiley, 1967
2	Yao B, Bu F, Reedy J, et al.Adaptive robust motion control of single-rod hydraulic actuators: Theory and experiments. IEEE/ASME Transactions on Mechatronics, 2000, 5(1): 79–91 https://doi.org/10.1109/3516.828592
3	Krstic M, Kanellakopoulos I, Kokotovic P V. Nonlinear and Adaptive Control Design. New York: Wiley, 1995
4	Armstrong-Hélouvry B, Dupont P, Canudas de Wit C. A survey of models, analysis tools and compensation methods for the control of machines with friction. Automatica, 1994, 30(7): 1083–1138 https://doi.org/10.1016/0005-1098(94)90209-7
5	Canudas de Wit C, Olsson H, Astrom K J, et al.A new model for control of systems with friction. IEEE Transactions on Automatic Control, 1995, 40(3): 419–425 https://doi.org/10.1109/9.376053
6	Swevers J, Al-Bender F, Ganseman C G, et al.An integrated friction model structure with improved presliding behavior for accurate friction compensation. IEEE Transactions on Automatic Control, 2000, 45(4): 675–686 https://doi.org/10.1109/9.847103
7	Yao J, Jiao Z, Ma D, et al.High-accuracy tracking control of hydraulic rotary actuators with modelling uncertainties. IEEE/ASME Transactions on Mechatronics, 2014, 19(2): 633–641 https://doi.org/10.1109/TMECH.2013.2252360
8	Yao J, Deng W, Jiao Z.RISE-based adaptive control of hydraulic systems with asymptotic tracking. IEEE Transactions on Automation Science and Engineering, 2017, 14(3): 1524–1531 https://doi.org/10.1109/TASE.2015.2434393
9	Lischinsky P, Canudas de Wit C, Morel G. Friction compensation for an industrial hydraulic robot. IEEE Control Systems Magazine, 1999, 19 (1): 25–32 https://doi.org/10.1109/37.745763
10	Swaroop D, Hedrick J K, Yip P P, et al.Dynamic surface control for a class of nonlinear systems. IEEE Transactions on Automatic Control, 2000, 45(10): 1893–1899 https://doi.org/10.1109/TAC.2000.880994
11	Yip P P, Hedrick J K. Adaptive dynamic surface control: A simplified algorithm for adaptive backstepping control of nonlinear systems. International Journal of Control, 1998, 71(5): 959–979 https://doi.org/10.1080/002071798221650
12	Farrell J A, Polycarpou M, Sharma M, et al.Command filtered backstepping. IEEE Transactions on Automatic Control, 2009, 54(6): 1391–1395 https://doi.org/10.1109/TAC.2009.2015562
13	Dong W, Farrell J A, Polycarpou M M, et al.Command filtered adaptive backstepping. IEEE Transactions on Control Systems Technology, 2012, 20(3): 566–580 https://doi.org/10.1109/TCST.2011.2121907
14	Guan C, Pan S. Adaptive sliding mode control of electro-hydraulic system with nonlinear unknown parameters. Control Engineering Practice, 2008, 16(11): 1275–1284 https://doi.org/10.1016/j.conengprac.2008.02.002
15	Guan C, Pan S. Nonlinear adaptive robust control of single-rod electro-hydraulic actuator with unknown nonlinear parameters. IEEE Transactions on Control Systems Technology, 2008, 16(3): 434–445 https://doi.org/10.1109/TCST.2007.908195
16	Mintsa H A, Venugopal R, Kenne J P, et al.Feedback linearization-based position control of an electrohydraulic servo system with supply pressure uncertainty. IEEE Transactions on Control Systems Technology, 2012, 20(4): 1092–1099 https://doi.org/10.1109/TCST.2011.2158101
17	Yao J, Yang G, Jiao Z. High dynamic feedback linearization control of hydraulic actuators with backstepping. Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, 2015, 229: 728–737 https://doi.org/10.1177/0959651815581555
18	Yao J, Jiao Z, Yao B, et al.Nonlinear adaptive robust force control of hydraulic load simulator. Chinese Journal of Aeronautics, 2012, 25(5): 766–775 https://doi.org/10.1016/S1000-9361(11)60443-3
19	Yang G, Yao J, Le G, et al.Adaptive integral robust control of hydraulic systems with asymptotic tracking. Mechatronics, 2016, 40: 78–86 https://doi.org/10.1016/j.mechatronics.2016.10.007
20	Deng W, Yao J. Adaptive integral robust control and application to electromechanical servo systems. ISA Transactions, 2017, 67: 256–265 https://doi.org/10.1016/j.isatra.2017.01.024
21	Yang G, Yao J, Le G, et al.Asymptotic output tracking control of electro-hydraulic systems with unmatched disturbances. IET Control Theory & Applications, 2016, 10(18): 2543–2551 https://doi.org/10.1049/iet-cta.2016.0702
22	Yao B, Xu L. On the design of adaptive robust repetitive controllers. In: Proceedings of 2001 ASME International Mechanical Engineering Congress and Exposition. New York: ASME, 2001, 1–9
23	Yao J, Jiao Z, Ma D. A practical nonlinear adaptive control of hydraulic servomechanisms with periodic-like disturbances. IEEE/ASME Transactions on Mechatronics, 2015, 20(6): 2752–2760 https://doi.org/10.1109/TMECH.2015.2409893
24	Yao J, Deng W, Jiao Z. Adaptive control of hydraulic actuators with LuGre model based friction compensation. IEEE Transactions on Industrial Electronics, 2015, 62(10): 6469–6477 https://doi.org/10.1109/TIE.2015.2423660
25	Xu L, Yao B. Adaptive robust control of mechanical systems with nonlinear dynamic friction compensation. International Journal of Control, 2008, 81(2): 167–176 https://doi.org/10.1080/00207170701390132
26	Tan Y, Kanellakopoulos I. Adaptive nonlinear friction compensation with parametric uncertainties. In: Proceedings of the 1999 American Control Conference. San Diego: IEEE, 1999, 2511–2515 https://doi.org/10.1109/ACC.1999.786505
27	Zheng Q, Gao L, Gao Z. On stability analysis of active disturbance rejection control for nonlinear time-varying plants with unknown dynamics. In: Proceedings of 2007 46th IEEE Conference on Decision and Control. New Orleans: IEEE, 2007, 3501–3506 https://doi.org/10.1109/CDC.2007.4434676
28	Yao J, Jiao Z, Ma D. Extended-state-observer-based output feedback nonlinear robust control of hydraulic systems with backstepping. IEEE Transactions on Industrial Electronics, 2014, 61(11): 6285–6293 https://doi.org/10.1109/TIE.2014.2304912
29	Tee K P, Ge S S, Tay E H. Barrier Lyapunov function for the control of output-constrained nonlinear systems. Automatica, 2009, 45(4): 918–927 https://doi.org/10.1016/j.automatica.2008.11.017
30	Ngo K B, Mahony R, Jiang Z P. Integrator backstepping using barrier functions for systems with multiple state constraints. In: Proceedings of 44th IEEE Conference on Decision and Control, 2005 and 2005 European Control Conference. Seville: IEEE, 2005, 8306–8312 https://doi.org/10.1109/CDC.2005.1583507
31	Deng W, Yao J, Jiao Z. Adaptive backstepping motion control of hydraulic actuators with velocity and acceleration constraints. In: Proceedings of 2014 IEEE Chinese Guidance, Navigation and Control Conference (CGNCC). Yantai: IEEE, 2014, 219–224 https://doi.org/10.1109/CGNCC.2014.7007238
32	Sadegh N, Horowitz R. Stability and robustness analysis of a class of adaptive controllers for robot manipulators. International Journal of Robotics Research, 1990, 9(3): 74–92 https://doi.org/10.1177/027836499000900305

[1]	Dan ZHANG,Bin WEI. Convergence performance comparisons of PID, MRAC, and PID+MRAC hybrid controller[J]. Front. Mech. Eng., 2016, 11(2): 213-217.
[2]	Syed Ali AJWAD,Jamshed IQBAL,Muhammad Imran ULLAH,Adeel MEHMOOD. A systematic review of current and emergent manipulator control approaches[J]. Front. Mech. Eng., 2015, 10(2): 198-210.
[3]	Jie LIU,Youmin HU,Bo WU,Kaibo ZHOU,Mingfeng GE. An adaptive sliding mode control technology for weld seam tracking[J]. Front. Mech. Eng., 2015, 10(1): 95-101.
[4]	Xueyan TANG, I-Ming CHEN. Robust control of XYZ flexure-based micromanipulator with large motion[J]. Front Mech Eng Chin, 2009, 4(1): 25-34.

Viewed

Full text

Abstract

Cited

Shared

Discussed