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The purpose of this paper is to improve the performance of control loop suffering from control valve stiction. Control valve stiction is considered as of one of the main causes of oscillation in process variables, which require performing costly unplanned maintenance and process shutdown. An adaptive solution to handle valve stiction while maintaining safety and quality until next planned maintenance is highly desirable to save considerable cost and effort.

This paper implements a new stiction compensation method built using adaptive inverse model techniques and intelligent control theories. Finite impulse response (FIR) model, which is known to be robust, as a compensator for stiction. The parameters of FIR model are tuned in an adaptive way using differential evolution (DE) technique. The performance of proposed method is compared with other two compensation techniques.

The new method showed excellent performance of the DE–FIR compensator compared to other dynamic inversion methods in terms of minimizing process variability, energy saving and valve stem aggressiveness.

The compensation ability for all compensators reduces with the increase of stiction severity, thus the over shoot case always shows the worst result. In future works, other optimization techniques will be explored to find the appropriate technique that can extend the FIR model size with smallest computation time that can improve the performance of the compensator in over shoot case. In addition, the estimation of the valve residual life based on the level of stiction and effort required by the controller should be considered.

The presented approach represents an original contribution to the literature. It performs stiction compensation without a need for a prior knowledge on the process or the valve models and guarantees a smooth control of the stem movement with a low control effort. The proposed approach differs from previous adaptive methods as it uses stable FIR models and DE to find the appropriate parameters of the inverse model and handle nonlinear behavior of stiction.

The purpose of this paper is to propose a control algorithm to improve the backdrivability performance of minimally invasive surgical robotic arms, so that precise manual manipulations of robotic arms can be performed in the preoperative operation.

First, the flexible-joint dynamic model of the 3-degree of freedom remote center motion (RCM) mechanisms of minimally invasive surgery (MIS) robot is derived and its dynamic parameters and friction parameters are identified. Next, the angular velocities and angular accelerations of joints are estimated in real time by the designed Kalman filter. Finally, a control algorithm based on Kalman filter is proposed to enhance the backdrivability of RCM mechanisms by compensating for the internally generated gravitational, frictional and inertial resistances experienced during the positioning and orientating.

The parameter identification for RCM mechanisms can be experimentally evaluated from comparison between the measured torques and the reconstructed torques. The accuracy and convergence of the real-time estimation of angular velocity and acceleration of the joint by the designed Kalman filter can be verified from corresponding simulation experiments. Manual adjustment experiments and animal experiments validate the effectiveness of the proposed backdrivability control algorithm.

The backdrivability control algorithm presented in this paper is a universal method to enhance the manual operation performance of robots, which can be used not only in the medical robot preoperative manual manipulation but also in robot haptic interaction, industrial robot direct teaching and active rehabilitation training of rehabilitation robot and so on.

Compared with other backdrivability design methods, the proposed algorithm achieves good backdrivability for RCM mechanisms without using force sensors and accelerometers. In addition, this paper presents a new static friction compensation approach for a joint moving with very low velocity.

The purpose of this paper is to find a simple structure of motion controller for permanent magnet direct drive. Application of sliding mode controller theory and equivalent disturbance estimator creates proper non‐linear characteristics, which ensures controller robustness against friction.

The position and speed controller is based on robust design methodology introduced by a sliding mode technique. The paper proposes a combination of sliding mode controller and proportional integral (PI) equivalent disturbance estimator. The friction model is Coulomb friction with a large static friction effect. The double boundary layer is used to compensate the effect of stiction. The synthesis is performed using simulation techniques and subsequently the behaviour of a laboratory speed control system is validated in the experimental setup. The control algorithms of the system are performed by a microprocessor floating point DSP control system.

The proposed sliding mode controller structure with equivalent disturbance estimator guarantees expected robustness against friction. Experimental results show that the control approach can decrease the tracking error, enhance the system's robustness and attenuate high‐frequency chattering in the control signal.

The proposed controller was tested on a single machine under well‐defined conditions. Further investigations are required before any industrial applications.

The proposed controller synthesis and its results may be very helpful in robotic systems where non‐linear friction is a characteristic for many industrial robots and manipulators.

The method of sliding mode controller synthesis was proposed and validated by simulation and experimental investigations.

The patient-side manipulator (PSM) achieves high torque capability by combining harmonic servo system with high reduction ratio and low torque motor. However, high reduction ratio can increase inertia and decrease compliance of the manipulator. To enhance the backdrivability of the minimally invasive surgical robot, this paper aims to propose a resistance torque compensation algorithm.

A resistance torque compensation algorithm based on dynamics and Luenberger observer is proposed. The dynamics are established, considering joint flexibility and an improved Stribeck friction model. The dynamic parameters are experimentally identified by using the least squares method. With the advantages of clear structure, simple implementation and fast solution speed, the Luenberger observer is selected to estimate the unmeasured dynamic information of PSM and realize the resistance torque compensation.

For low-speed surgical robots, the centrifugal force term in the dynamic model can be simplified to reduce computational complexity. Joint flexibility and an improved Stribeck friction model can be considered to improve the accuracy of the dynamic model. Experiment results show that parameter identification and estimated results of the Luenberger observer are accurate. The backdrivability of the PSM is enhanced in ease and smoothness.

This algorithm provides potential application prospects for surgical robots to maintain high torque while remaining compliant. Meanwhile, the enhanced backdrivability of the manipulator helps to improve the safety of the preoperative manual adjustment.

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.

The purpose of this paper is to present a simple yet effective force control scheme for collaborative robots by addressing the problem of disturbance rejection in joint torque: inherent actuator flexibility and nonlinear friction.

In this paper, a joint torque controller with an extended state observer is used to decouple the joint actuators from the multi-rigid-body system of a constrained robot and compensate the motor friction. Moreover, to realize robot force control, the authors embed this controller into the impedance control framework.

Results have been given in simulations and experiments in which the proposed joint torque controller with an extended state observer can effectively estimate and compensate the total disturbance. The overall control framework is analytically proved to be stable, and further it is validated in experiments with a robot testbed.

With the proposed robot force controller, the robot is able to change its stiffness in real time and therefore take variable tasks without any accessories, such as the RCC or 6-DOF F/T sensor. In addition, programing by demonstration can be realized easily within the proposed framework, which makes the robot accessible to unprofessional users.

The main contribution of the presented work is the design of a model-free robot force controller with the ability to reject torque disturbances from robot-actuator coupling effect and motor friction, applicable for both constrained and unconstrained environments. Simulation and experiment results from a 7-DOF robot are given to show the effectiveness and robustness of the proposed controller.

Due to dynamic model is the basis of realizing various robot control functions, and it determines the robot control performance to a large extent, this paper aims to improve the accuracy of dynamic model for n-Degree of Freedom (DOF) serial robot.

This paper exploits a combination of the link dynamical system and the friction model to create robot dynamic behaviors. A practical approach to identify the nonlinear joint friction parameters including the slip properties in sliding phase and the stick characteristics in presliding phase is presented. Afterward, an adaptive variable-step moving average method is proposed to effectively reduce the noise impact on the collected data. Furthermore, a radial basis function neural network-based friction estimator for varying loads is trained to compensate the nonlinear effects of load on friction during robot joint moving.

Experiment validations are carried out on all the joints of a 6-DOF industrial robot. The experimental results of joint torque estimation demonstrate that the proposed strategy significantly improves the accuracy of the robot dynamic model, and the prediction effect of the proposed method is better than that of existing methods.

The proposed method extends the robot dynamic model with friction compensation, which includes the nonlinear effects of joint stick motion, joint sliding motion and load attached to the end-effector.

Examines the experience of Thorn Automation in the field of magnetometery in both defence and commercial markets. The cornerstone of their capability has come from using high performance fluxgate sensors. Looks at the different kinds of magnetometer available and describes their applications for a variety of remote sensing requirements including vehicle navigation and remote tracking.

Based on the inverse kinematics and task space dynamic model, this paper aims to design a high-precision trajectory tracking controller for a 2-DoF translational parallel manipulator (TPM) driven by linear motors.

The task space dynamic model of a 2-DoF TPM is derived using Lagrangian equation of the first type. A task space dynamic model-based feedforward controller (MFC) is designed, which is combined with a cascade PID/PI controller and velocity feedforward controller (VFC) to construct a hybrid PID/PI+VFC/MFC controller. The hybrid controller is implemented in MATLAB/dSPACE real-time control platform. Experiment results are given to validate the effectiveness and industrial applicability of the hybrid controller.

The MFC can compensate for the nonlinear dynamic characteristics of a 2-DoF TPM and achieve better tracking performance than the conventional acceleration feedforward controller (AFC).

The task space dynamic model-based hybrid PID/PI+VFC/MFC controller is proposed for a 2-DoF linear-motor-driven TPM, which reduces the tracking error by at least 15 percent compared with conventional hybrid PID/PI+VFC/AFC controller. This control scheme can be extended to high-speed and high-precision trajectory tracking control of other parallel manipulators by reprogramming the feedforward signals of traditional cascade PID/PI controller.

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.