Electrohydraulic servo systems (EHSS) are used for several engineering applications, and in particular, for efficient handling of heavy loads. These systems are characterized by pronounced nonlinearities and are also subject to parameter variations during operation, friction effects, and variable loads. Several studies have addressed the nonlinear nature of EHSS; however, only a few control schemes explicitly address friction and load disturbance effects along with parameter variations. Fuzzy and/or sliding mode versions of feedback linearizing controllers have been used to compensate for the external loads disturbances in the control of EHSS. However, real-time implementations issues limit the use of these techniques. While adaptive control using a feedback-linearization based controller structure has been shown to be effective in the presence of parameter variations, load and friction effects are typically not considered. In this paper, we present a nonlinear adaptive feedback linearizing position controller for an EHSS, which is robust to parameter uncertainty while achieving load disturbances rejection/attenuation and friction compensation. The adaptation law is derived using a Lyapunov approach. Simulation results using the proposed controller are compared to those using a nonadaptive feedback linearizing controller as well as a proportional-integral-derivative (PID) controller, in the presence of torque load disturbance, friction, and uncertainty in the hydraulic parameters. These results show improved tracking performance with the proposed controller. To address implementation concerns, simulation results with noise effects and valve saturation are also presented.
Adaptive Position Control of an Electrohydraulic Servo System With Load Disturbance Rejection and Friction Compensation
Angue-Mintsa, H., Venugopal, R., Kenné, J., and Belleau, C. (November 22, 2011). "Adaptive Position Control of an Electrohydraulic Servo System With Load Disturbance Rejection and Friction Compensation." ASME. J. Dyn. Sys., Meas., Control. November 2011; 133(6): 064506. https://doi.org/10.1115/1.4004776
Download citation file: