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The purpose of this paper is to design a third-order linear active disturbance rejection controller (LADRC) to improve the response characteristics and robustness of the electrohydraulic servo system.

The LADRC was designed by replacing the nonlinear functions in each part of ADRC with linear functions or linear combinations, and the parameters of each part of the LADRC were connected with their bandwidth through the pole configuration method to reduce the required tuning parameters, and used an improved grey wolf optimizer to tune the LADRC parameters.

The anti-interference control simulation and experiment on the LADRC, ADRC and proportion integration differentiation (PID) were carried out to test the robustness, anti-interference ability and superiority of the designed LADRC. The simulation and experiment results showed that the LADRC control and anti-interference control had excellent performance, and because of its simple structure and fewer parameters, LADRC was easier to implement and had a better control effect and anti-interference.

For the problems of parameter perturbation, unknown interference and inaccurate model in the electrohydraulic position servo system, the designed third-order LADRC has good tracking accuracy and anti-interference, has few parameters and is conducive to promotion.

Sinusoidal signals are often used as the inputs of the six degree of freedom (DOF) motion simulator platforms. The purpose of this paper is to propose a fuzzy incremental controller (FIC) to improve sinusoidal signal tracking performances of an electrohydraulic Gough-Stewart platform (GSP).

An FIC is proposed to control an electrohydraulic GSP without any model parameters. The FIC output can be self-organized by only using the hydraulic actuator position information. The control rules are determined by a systematic deterministic method.

Experimental results show that the proposed FIC is valid and can achieve better tracking performances compared with classical PID controller and a decoupling controller (a model-based controller).

An FIC using a systematic deterministic rule-base determination method is proposed to improve sinusoidal signal tracking performances of electrohydraulic GSP.

Electrohydraulic servos have been widely applied to the task of precisely positioning heavy loads. Common examples from the military field are radar antenna and rocket engine swivelling drives. In the commercial area large machine tool position controls are a prime example. Even with relatively substantial driving linkages, the inertia of these loads frequently results in low natural frequency of the output load‐driver structure. Very commonly this is combined with extremely small natural damping forces. Natural frequencies from 5 to 20 c.p.s. with damping ratios in the oder of 0·05 critical are typical. This combination of resonance with low damping creates a severe stability and performance problem for the electrohydraulic servo drive. Efforts to deal with this problem have centred on introducing artificial damping. In the past this has been done either by use of a controlled piston by‐pass leakage path or by use of a load force feedback path. The former technique is simple but wasteful with respect to power and inherently involves serious performance compromises. The latter technique can be arranged to be unassailable on theoretical grounds. However, it leads to severe system complication and large incremental hardware requirements. Questions of a reliability penalty are raised. A new technique has been developed which possesses all the performance advantages of load feedback without serious increase in complexity. Called Dynamic Pressure Feedback, this technique involves only a modification of servo valve component. It utilizes for feedback purposes the inherently high load forces developed as piston differential pressures, insuring reliable operation. The pressures needed are already available at the valve. No new hydraulic or electrical connexions are added. The performance advantages adduced for the Dynamic Pressure Feedback Servo Valve have been confirmed in carefully controlled comparative tests on a typical load system. Correspondence of test data with analytical prediction is good. A sufficient number of Dynamic Pressure Feedback Servo Valves have been produced on a pilot production line and installed in several applications in the field to insure producibility and design reliability.

The purpose of this paper is to apply a intelligent algorithm to conduct the force tracking control for electrohydraulic servo system (EHSS). Specifically, the adaptive neuro-fuzzy inference system (ANFIS) is selected to improve the control performance for EHSS.

Two types of input–output data were chosen to train the ANFIS models. The inputs are the desired and actual forces, and the output is the current. The first type is to set a sinusoidal signal for the current to produce the actual driving force, and the desired force is chosen as same as the actual force. The other type is to give a sinusoidal signal for the desired force. Under the action of the PI controller, the actual force tracks the desired force, and the current is the output of the PI controller.

The models built based on the two types of data are separately named as the ANFIS I controller and the ANFIS II controller. The results reveal that the ANFIS I controller possesses the best performance in terms of overshoot, rise time and mean absolute error and show adaptivity to different tracking conditions, including sinusoidal signal tracking and sudden change signal tracking.

This paper is the first time to apply the ANFIS to optimize the force tracking control for EHSS.

This paper aims to present an adaptive sliding mode control (ASMC) for tunnel boring machine cutterhead telescopic system with uncertainties to achieve a high-precision trajectory in complex strata. This method could be applied to solve the problems caused by linear and nonlinear model uncertainties.

First, an integral-type sliding surface is defined to reduce the static tracking error. Second, a projection type adaptation law is designed to approximate the linear and nonlinear redefined parameters of the electrohydraulic system. Third, a nonlinear robust term with a continuous approximation function is presented for handling load force uncertainty and reducing sliding mode chattering. Moreover, Lyapunov theory is applied to guarantee the stability of the closed-loop system. Finally, the effectiveness of the proposed controller is proved by comparative experiments on a scaled test rig.

The linear and nonlinear model uncertainties lead to large variations in the dynamics of the mechanism and the tracking error. To achieve precise position tracking, an adaptation law was integrated into the sliding mode control which compensated for model uncertainties. Besides, the inherent sliding mode chattering was reduced by a continuous approximation function, while load force uncertainty was solved by a nonlinear robust feedback. Therefore, a novel ASMC for tunnel boring machine cutterhead telescopic system with uncertainties can improve its tracking precision and reduce the sliding mode chattering.

To the best of the authors’ knowledge, the ASMC is proposed for the first time to control the tunnel boring machine cutterhead telescopic system with uncertainties. The presented control is effective not only in control accuracy but also in parameter uncertainty.

This paper’s aim is modeling and simulation of an advanced controller design for a novel mechatronics system that consists of a hydrostatic journal bearing with servo control. The proposed mechatronic system has more worth in tribology applications as compared to the traditional hydrostatic bearing which has limited efficiency and poor performance because of lower stiffness and load-carrying capacity. The proposed mechatronic system takes advantage of active lubrication to improve stiffness, rotor’s stability and load-carrying capacity.

The current work proposes extended state observer-based controller to control the active lubrication for hydrostatic journal bearing. The advantage of using observer is to estimate unknown state variables and lumped effects because of unmodeled dynamics, model uncertainties, and unknown external disturbances. The effectiveness of the proposed mechatronic system is checked against the traditional hydrostatic bearing.

Proposed mechatronics active hydrostatic journal bearing system is checked against traditional hydrostatic journal bearing. It is found that novel active hydrostatic journal bearing with servo control has good tribology performance factors such as stiffness, less rotor vibration, no wear and friction under starting conditions and high load-carrying capacity under different conditions of spindle speed, temperature, initial oil pressure and external disturbance. The result shows that proposed mechatronics system has more worth in rotary tribology applications.

The current manuscript designs a novel active hydrostatic journal bearing system with servo control. The mathematical model has advantages in term of estimating unknown state variables and lumped effects because of unmodeled dynamics, model uncertainties and unknown external disturbances. The result shows improvement in dynamic characteristics of a hydrostatic journal bearing under different dynamic conditions.

The purpose of this paper is to present a direct force control which uses two closed-loop controller for one-degree-of-freedom human-machine system to synchronize the human position and machine position, and minimize the human-machine force. In addition, the friction is compensated to promote the performance of the human-machine system.

The dynamic of the human-machine system is mathematically modeled. The control strategy is designed using two closed-loop controllers, including a PID controller and a PI controller. The frictions, which exist in the rotary joint and the hydraulic wall, are compensated separately using the Friedland’s observer and Dahl’s observer.

When human-machine system moves at low velocity, there exists a significant amount of static friction that hinders the system movements. The simulation results show that the system gives a better performance in human-machine position synchronization and human-machine force minimization when the friction is compensated.

The acquired results are based on simulation not experiment.

This paper is the first to apply the electrohydraulic servo systems to both actuate the human-machine system, and use the direct force control strategy consisting of two closed-loop controllers. It is also the first to compensate the friction both in the robot joint and hydraulic wall.

To control one of the joints during the actual movement of the hydraulically driven quadruped robot, all the other joints in the leg need to be locked. Once the joints are unlocked, there is a coupling effect among the joints. Therefore, during the normal exercise of the robot, the movement of each joint is affected by the coupling of other joints. This brings great difficulties to the coordinated motion control of the multi-joints of the robot. Therefore, it is necessary to reduce the influence of the coupling of the hydraulically driven quadruped robot.

To solve the coupling problem with the joints of the hydraulic quadruped robot, based on the principle of mechanism dynamics and hydraulic control, the dynamic mathematical model of the single leg mechanism of the hydraulic quadruped robot is established. On this basis, the coupling dynamics model of the two joints of the thigh and the calf is derived. On the basis of the multivariable decoupling theory, a neural network (NN) model reference decoupling controller is designed.

The simulation and prototype experiment are carried out between the thigh joint and the calf joint of the hydraulic quadruped robot, and the results show that the proposed NN model reference decoupling control method is effective, and this method can reduce the cross-coupling between the thigh and the calf and improve the dynamic characteristics of the single joint of the leg.

The proposed method provides technical support for the mechanical–hydraulic cross-coupling among the joints of the hydraulic quadruped robot, achieving coordinated movement of multiple joints of the robot and promoting the performance and automation level of the hydraulic quadruped robot.

On the basis of the theory of multivariable decoupling, a new decoupling control method is proposed, in which the mechanical–hydraulic coupling is taken as the coupling behavior of the hydraulic foot robot. The method reduces the influence of coupling of system, improves the control precision, realizes the coordinated movement among multiple joints and promotes the popularization and use of the hydraulically driven quadruped robot.

The symmetrical valve is usually used in the hydraulic servo control system to control the asymmetrical cylinder, but this system’s structure involves asymmetry, and so its dynamic characteristics are asymmetrical, which causes issues in the control system of symmetric response. The purpose of this paper is to achieve the aim of symmetric control.

In this paper, the authors proposed a method that combined wavelet neural network (WNN) and model reference adaptive control. The reference model determined the dynamic response that the system was expected to achieve, and the WNN adaptive control made the system follow the reference model to achieve the purpose of symmetric control.

The experimental results show that the method can achieve a more accurate symmetric control and position control compared with the solutions via the classical PID control.

The proposed combination of the WNN and the reference model can effectively compensate for the asymmetry of dynamic response of the asymmetric cylinder in forward and return directions, which can be extended to deal with other classes of applications.

This study aims to minimize the risk of costly failures of flight tests during the path tracking control design, and a noble approach has been proposed in this study to put the whole vehicle-in-the simulation loop. Working with the real system is essential for developing intelligent and data-driven controllers for multirotor drones which needs learning the drones' nonlinear complicated dynamics. The vehicle-in-the-loop (VIL) platform developed in this paper is a safe and effective solution to deal with this problem.

To avoid risky flight test during controller design, the multirotor is hinged to a shaft that allows the multirotor's angular motion but restricts translational motion. The test-bed includes the real system attitude dynamics and the simulation of the position dynamics to model the complete flight based on real-time reactions of the vehicle. For the authors' case study, a hexacopter angular motion provides the real-time attitude data in translational motion simulation loop. To test the set-up, a proportional-integral-derivative (PID) and a brain emotional learning-based intelligent controller (BELBIC) is implemented for tracking of circle and 8-shape flight trajectories.

The results show that the platform helps the intelligent controller to learn the system dynamics without worrying about the failure in the early stages of the design and in the real-world flight test. Although the hexacopter translational dynamics is modeled in simulation, the authors still have highly accurate attitude dynamics matching the requirement of the control loop design. The comparison of the two controllers also shows that the performance of BELBIC is better than PID in this test.

The research background is reviewed in the introduction section. The other sections are originally developed in this paper.