In this paper, the command filter-based adaptive fuzzy finite-time output feedback control (FOFC) is investigated for the Electro-hydraulic servo system. For the uncertainties in the system, we utilize the fuzzy logic systems (FLSs) to estimate these uncertain nonlinearities and fuzzy state observer is established to approximate the unmeasurable hydraulic cylinder stem speed and the internal cylinder force. Then, a command filter-based finite time output feedback control is proposed to achieve high tracking precision, where the tracking errors can be regulated into a small neighborhood around the equilibrium proved by the Lyapunov finite-time stability theory. Moreover, a command filter is introduced to avoid the explosion of complexity in the backstepping procedure, where a compensation mechanism is developed to compensate for filter errors. Finally, simulation results are provided to demonstrate the effectiveness of the proposed control.

The integration of variable stiffness materials and structures into soft robots is a popular trend, allowing soft robots to switch between soft and rigid states in different situations. This concept combines the advantages of rigid mechanisms and soft robots, resulting in not only excellent flexibility but also tunable stiffness for high load capacity and fast and precise operation. Here, a stiffness-tunable soft actuator based on wire/fiber jamming structure is proposed, where the fiber-reinforced soft actuator is responsible for the bending motion, and the jamming structure acts as a stiffness-tunable layer controlled by vacuum pressure. The primary design objective of this study is to fabricate a jamming structure with wide-range stiffness, universal adaptability and high dexterity. Thus, the behaviors of wire/fiber jamming structures with different layouts, materials and wire arrangements are analyzed, and a theoretical model is developed to predict the effect of geometric parameters. Experimental characterizations show that the stiffness can be significantly enhanced in the bending direction, while the stiffness is smaller in the torsion direction. Additionally, by integrating Velcro strips into the design, a quick and detachable scheme for the stiffness-tunable soft actuator is achieved. Application examples exhibit high load capacity and good shape adaptability.

The extended state observer (ESO) has been widely used in the state and perturbation estimation of the electro-hydraulic servo system. It was found that there was a controlled quantity in the transfer function between the perturbation estimation value and the disturbance. This indicates that the traditional linear ESO’s estimation of the disturbance is affected by the change in the control input. To solve this problem, a new structure ESO for a hydraulic system (LHYESO) was designed by introducing the hydraulic system’s load pressure and system model. The corresponding frequency domain analysis results show that it eliminates the control input in the transfer function and reduces the dependence of the high-frequency domain range of the perturbation estimation on the significant observer gain. To improve the estimation speed, a finite-time convergent ESO for hydraulic systems (FTHYESO) was proposed based on the structure of LHYESO, and it was proved that the observation error converged to a sufficiently small value during a finite time. Moreover, a finite-time backstepping controller has been designed by using the Lyapunov method to guarantee the rapidity and precise response of the hydraulic servo system. Finally, the experiment results show the effectiveness of the proposed method.

Valve-controlled servosystems are widely used in dynamic tracking, but, not properly studied, nonlinearity, perturbation of internal parameters, and external disturbance have significant impacts on the control performance and challenge in the controller design. This study, with consideration of the finite pressure gain of actual servovalves, proposes a new unified nonlinear model of the valve-controlled servosystem. Based on a U-control platform, this study makes the control strategy design independent from the nonlinear plant, and a virtual nominal plant is presented to eliminate the unmodeled high-frequency characteristics, acquire the desired control performance, and enable the control variable to be explicitly expressed. Then, there follows, designing the U-model-based finite-time control in the valve-controlled systems. Simulation demonstrations show the consistency with theoretical development that the valve-controlled system can smoothly track the command signal within the specified time, and the phase lag is eliminated. Moreover, U-model’s application effectively copes with the system chattering, and with the maximum of 1 m/s the dynamic position error caused by discretization of the controller is reduced to less than 0.15%, which can satisfy the demand of general valve-controlled servosystems.

To address the issues of derivative explosion in traditional backstepping control and the strong nonlinearity of hydraulic systems, this paper develops an adaptive neural network control method tailored for electro-hydraulic load simulators. Neural networks are employed to handle external disturbances, modeling uncertainties, and the derivatives of virtual control inputs. First, the precise state-space equations of the system are derived. Next, the approximation property of neural networks is used to design an adaptive backstepping controller, and the symmetric barrier Lyapunov function is used to prove the boundedness of the controller and control parameters. Finally, experiments are conducted to verify the effectiveness and reliability of the control algorithm. The results demonstrate that the proposed control algorithm exhibits excellent tracking performance and effectively reduces control errors.