Affiliation:
1. Jiangsu Key Laboratory of Mine Mechanical and Electrical Equipment, School of Mechanical and Electrical Engineering, China University of Mining and Technology, Xuzhou, China
Abstract
High-accuracy motion tracking of hydraulic systems is of great significance in industrial applications. Nevertheless, dynamic nonlinearity, modeling uncertainty, generalized disturbance, and measurement noise are inevitably existed in hydraulic systems, which severely deteriorates the practical control performance. Aimed at enhancing the motion-tracking accuracy of hydraulic systems, a novel command filtered adaptive backstepping controller with extended state observer is proposed in this article. On the basis of the established system’s nonlinear model, the extended state observer utilizing only position output feedback information is first designed to estimate the system’s unmeasurable states, and time-varying disturbances of the hydraulic system are also obtained for subsequent active disturbance compensation. Next, a second-order command filter is constructed to generate specific command signals and their derivatives, which significantly simplifies the controller design process by avoiding complicated analytical differential calculations in contrast to traditional adaptive backstepping algorithm. Subsequently, with consideration of system’s nonlinearity, parametric uncertainty, and time-varying disturbance, the developed extended state observer and command filter are introduced into the adaptive backstepping design process of the proposed controller, and theoretical stability of the proposed controller is guaranteed via Lyapunov analysis. Finally, the effectiveness and superiority of the proposed controller are demonstrated by comparative experimental results.
Funder
Natural Science Foundation of Jiangsu Province
program for changjiang scholars and innovative research team in university
priority academic program development of jiangsu higher education institutions
National Natural Science Foundation of China
national natural science foundation of china
Subject
Mechanical Engineering,Control and Systems Engineering
Cited by
10 articles.
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