Nonlinear adaptive position tracking of an electro-hydraulic actuator

Abstract

This paper deals with position tracking control of a single-rod electro-hydraulic actuator subject to external disturbances and parameter uncertainties. In previous disturbance observer design methodologies for electro-hydraulic actuators, parameter uncertainties have been commonly regarded as disturbances and lumped together with external perturbations. However, in practical electro-hydraulic systems, system parameters are unknown and varying. If considerable parameter uncertainties exist in the system or if the disturbance dynamics induced by parameter uncertainties exceed the bandwidth of the disturbance observer, estimation accuracy will degrade, which will significantly affect system performance. To solve this problem, an extended disturbance observer is proposed in this paper to estimate disturbances while dealing with parameter uncertainties. In addition, a nonlinear position tracking controller is designed for position tracking based on the proposed disturbance observer using a backstepping technique. The proof of the stability of the overall closed-loop system is based on Lyapunov theory. The performance of the proposed controller is verified through simulations and experiments using a shock absorber as a load force generator. A detailed nonlinear physical model of the load force is developed and implemented in the simulation. The results show that the proposed nonlinear position tracking controller, together with the extended disturbance observer, provide excellent tracking performance in the presence of parameter uncertainties and external disturbances.

Adaptive Sliding Mode Control of a Nonlinear Electro-hydraulic Servo System for Position Tracking

“…In fact, the natural frequency of the servo valve in the experiment is much higher than that of the hydraulic cylinder. On the premise of not significantly reduce the model accuracy, the dynamics of the servo valve can be simplicity approximation by [16]:…”

“…where: ks and η are the gain coefficients, and both of them are positive constants. Furthermore, the switch gain η of sliding model control is given a moderate condition by: 0, D   (16) where: Eq. (16) ensures the system can suppress modeling uncertainty and external disturbance, which have special significance to the performance of the controller.…”

“…Compared with the traditional linear control methods, non-linear control methods and intelligent approaches demonstrate better sensitivity to both the non-linearity and uncertainty of electro-hydraulic system. Sliding mode control (SMC) [8][9][10], fuzzy control [11,12], adaptive control [4,[13][14][15][16] and neural network control [17,18] have been successfully utilized in EHSS to meet practical and different control demands, but these methods still have their own limitations. Adaptive control is an effective method to deal with control problems coming from uncertain nonlinear system, especially the system uncertainty caused by uncertain parameters [19,20].…”

RBF Neural Network Sliding Mode Control Method Based on Backstepping for an Electro-hydraulic Actuator

“…In recent years, many scholars have applied advanced control methods, such as adaptive, robust, sliding mode, and intelligent controls [8], to the electro-hydraulic servo control system to improve the control performance of the system, and have achieved varied results [9]. However, the work environment of the electro-hydraulic servo system of a launch vehicle is complex, that is, the load characteristics have many new characteristics, and the stability of the rocket control system requires the launch vehicle to have good dynamic characteristics [10].…”

PC‐based control and simulation of an electro‐hydraulic system

“…Many researchers are interested in the modeling, control, and development of hydraulic system components and in obtaining their characteristics. Several control techniques, from classical to intelligent, are applied to control the position, force or speed of these systems [3,6,10,14,[18][19][20]23,[25][26][27]29,30,32,33,[35][36][37][38]40]. Thus, understanding of these subjects, both theoretically and experimentally, plays an important role in engineering education.…”