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

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.

Key words： hydraulic servo system; adaptive control; robust control; nonlinear friction; disturbance compensation; repetitive control; noise alleviation; constraint control

Acknowledgements

This work was supported in part by the National Natural Science Foundation of China (Grant No. 51675279), the China Postdoctoral Science Foundation funded project (Grant Nos. 2014M551593 and 2015T80553), and the Natural Science Foundation of Jiangsu Province in China (Grant No. BK20141402). The author also wants to express his appreciation to Prof. B. Yao for hosting his visit at Purdue University from October 2010 to October 2011, and the guidance in adaptive and robust design.

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