Electro-hydrostatic actuator (EHA) has significance in a variety of industrial tasks. For the purpose of elevating the working performance, we put forward a sliding mode control strategy for EHA operation with a damping variable sliding surface. To start with, a novel sliding mode controller and an extended state observer (ESO) are established to perform the proposed control strategy. Furthermore, based on the modeling of the EHA, simulations are carried out to analyze the working properties of the controller. More importantly, experiments are conducted for performance evaluation based on the simulation results. In comparison to the widely used control strategies, the experimental results establish strong evidence of both overshoot suppression and system rapidity.

An electrohydrostatic actuator (EHA) is a basic mechanical/hydraulic system with deficiencies including significant nonlinearity and parametric uncertainties. In line with the challenges of designing a high-precision control strategy, an adaptive damping variable sliding mode controller is established, which extends our previous work on EHA control. The proposed controller integrates variable-damping sliding mode control, parametric adaptation, and an extended state observer. The parametric uncertainties are effectively captured and compensated by employing an adaptive control law, while system uncertainties are reduced, and disturbances are estimated and compensated with a fast and stable response. We evaluated the proposed control strategy on a variety of position tracking tasks. The experimental results demonstrate that our controller significantly outperforms the widely used methods in overshoot suppression, settling time, and tracking accuracy.

This paper proposed a method of online walking pattern generation based on key parameters of off-line typical walking patterns for humanoid robot. The key parameters include hip parameters, step length, walking cycle and so on. The offline walking pattern generation method is based on ZMP. The design of the system software of humanoid BHR-2 is also described in this paper, in order to ensure the real task can be finished on time, the process of online walking patterns generation is placed outside the processor which used for real-time control. The effectiveness of the proposed method is confirmed by simulations and experiments with our developed humanoid robot with 32 DOF

A dynamic load simulator, which can reproduce on-ground aerodynamic hinge moment of control surface, is an essential rig for the performance and stability test of an aircraft actuation system. In this paper, an observer-based backstepping adaptive control (OBAC) strategy with an improved friction model is proposed to deal with the force tracking problem of an electro-mechanical actuator under the influence of nonlinear friction and lumped disturbances. First, The LuGre friction model is improved by introducing the load effect of electrical linear load simulator (ELLS), and both dynamic and static parameters are identified with experimental data. Then, the ELLS system is divided into a loading subsystem and actuation subsystem for backstepping controller deign. The estimation of the position disturbance is obtained using an extended state observer and used for feedforward compensation for the loading subsystem. To reject the disturbance of friction parameter uncertainties for actuation subsystem, a friction scale factor with a reasonable adaptive updating law is introduced during the friction compensation process. Finally, the stability of the whole closed-loop system is demonstrated using a Lyapunov-based method, and experiments are performed to validate the effectiveness of the developed algorithm.