Position Control Of Manipulator Research Articles

Hardware-in-the-loop simulation for estimation of position control performance of machine tool feed drive

One of the most important measures for improving the performance of a machine tool is to set its controller parameters appropriately. The setting of these parameters is typically done by an expert when the machine tool is initially installed. Although parameter tuning is crucial when there is a change in the operation conditions, it is a challenge faced by non-experts as improper settings can result in critical problems in the machine tools. Simulation software, which estimate the control performance and identify appropriate parameters, can be used for the easy customization of these parameters. However, it is difficult to accurately model a commercial controller owing to its complex structure and several hidden functions. This paper proposes a novel method that utilizes Hardware-In-the-Loop (HIL) simulation for estimating the position control performance of machine tool feed drives. HIL improves the simulation accuracy by integrating a real commercial controller into the simulation loop. The simulation error caused by the inaccuracy of the controller model is out of existence in the HIL simulation. The procedure of configuring the HIL simulation, from modeling and parameter identification of the machine tool feed drives, to organizing data exchange between the real controller and feed drive model, is extensively explained. The accuracy of the proposed HIL simulation is experimentally evaluated and applied for the estimation of position control performance, based on the controller parameters. The estimation of step response, failure mode, and effect analysis, as well as the evaluation of the control algorithm, are also performed using the HIL simulation. The results demonstrate that the HIL simulation can not only be used for the estimation of control performance but also for performance enhancement of machine tools.

Design and Experimental Characterization of a Shoulder-Elbow Exoskeleton With Compliant Joints for Post-Stroke Rehabilitation

This paper presents the design and experimental characterization of a 4-degree-of-freedom shoulder-elbow exoskeleton, NeuroExos Shoulder-elbow Module (NESM), for upper-limb neurorehabilitation and treatment of spasticity. The NESM employs a self-aligning mechanism based on passive rotational joints to smoothly self-align the robot's rotational axes to the user's ones. Compliant yet high-torque series-elastic actuators allow the NESM to safely interact with the user, particularly in response to sudden unpredicted movements, such as those caused by spastic contractions. The NESM control system provides a variety of rehabilitation exercises, enabling the customization of therapy to patients exhibiting a range of movement capabilities. Available exercises include passive mobilization, active-assisted, active-resisted, and active-disturbed training modes. The experimental characterization of two NESM actuation units demonstrated position and torque control performance suitable for use in neurorehabilitation applications, including up to 7 Hz of bandwidth in torque control. An algorithm for online detection of spastic contractions or sudden object collisions has been implemented and tested as well, with results suggesting that the current system can ensure safe interaction with patients.

Adaptive Backstepping Sliding Mode Fault Tolerant Control for Satellite Attitude under Actuator Faults

Modern spacecraft missions place stringent performance requirements on the reliability and stability of spacecraft attitude control system. However, during long-term in-orbit mission, actuators may suffer faults. In this paper, we proposed an adaptive fault tolerant control law for attitude control under actuator failures and external disturbances. Firstly, the attitude dynamic model under actuator faults and attitude kinematics are described. Then, in order to solve the attitude control problem under actuator faults and external disturbances, an adaptive backstepping sliding mode fault tolerant control scheme is designed. According to Lyapunov theory, the closed-loop system is proved to be globally asymptotically stable. Finally, the numerical simulation results demonstrate that the proposed adaptive controller can achieve anticipative attitude control performance, fault information estimation and well fault-tolerant capability.

Attitude controller design for the aerial trees-pruning robot based on nonsingular fast terminal sliding mode

In this article, the attitude control problem of a new-designed aerial trees-pruning robot is addressed. During the tree cutting process, the aerial trees-pruning robot will be disturbed by unknown external disturbances. At the same time, the model uncertainties will also affect the attitude controller. To overcome the above problems, an attitude controller is designed with a nonsingular fast terminal sliding mode method. First, the extended state observer is designed to estimate the modeling uncertainties and unknown disturbances. Then, the extended state observer-based nonsingular fast terminal sliding mode controller can make the tracking error of the attitude converge to zero in a finite time. Finally, a control allocation matrix switching strategy is proposed to solve the problem of the change of the aerial robot model in the cutting process. The final simulation and experimental results show that the extended state observer-based nonsingular fast terminal sliding mode controller designed in this article has good attitude control performance and can effectively overcome the modeling uncertainties and unknown disturbances. The attitude controller and control allocation matrix switching strategy ensure that the attitude angles of the aerial robot can quickly track the reference signals.

Bimanual control of position and force in people with multiple sclerosis: preliminary results.

Proprioceptive deficits are frequent and disabling symptoms of neurological diseases such as Multiple Sclerosis (MS). These deficits are poorly understood partly because of the limited sensitivity and reproducibility of clinical measures. However, their assessment is crucial in planning and evaluating rehabilitative treatments. Therefore, we designed a device and a protocol for assessing proprioceptive deficits by evaluating the position and force control performance. We focused on bimanual tasks, as most daily life activities require the combined use of both hands while MS induces coordination problems and often affects the two arms differently. Specifically, without being able to see their arms, subjects had (1) to reach with their hands a target positions holding objects of equal or different weights; (2) to exert equal isometric forces with the two hands in upward direction against rigid constraints at the same or different heights. For a first proof of concept of the feasibility we enrolled seven MS subjects with different levels of upper limb impairment and seven sex and age matched controls. We found that the ability to exert symmetric forces with both arms was significantly altered in all MS subjects, while position control decreased only for higher level of impairment. These preliminary findings suggest that in people with MS the ability to exert bilaterally required levels of force might be affected earlier compared to the ability to control hand position.

Motion Control of Three Links Robot Manipulator (Open Chain) with Spherical Wrist

Robot manipulator is a multi-input multi-output system with high complex nonlinear dynamics, requiring an advanced controller in order to track a specific trajectory. In this work, forward and inverse kinematics are presented based on Denavit Hartenberg notation to convert the end effector planned path from cartesian space to joint space and vice versa where a cubic spline interpolation is used for trajectory segments to ensure the continuity in velocity and acceleration. Also, the derived mathematical dynamic model is based on Eular Lagrange energy method to contain the effect of friction and disturbance torques beside the inertia and Coriolis effect. Two types of controller are applied ; the nonlinear computed torque control (CTC) and the simpler form of its Proportional Derivative plus Gravity (PD+G) where they are designed to reduce the tracking trajectory errors which tend to zero where the used Kp and Kv gains are 900,60. Also, the RMS errors for tracking a step input of CTC were equal to [2.5E-14, 4.4E-14, 5.0E-14, -4.7E-14, -3.9E-14, -4.6E-14] (deg) and of PD+G were equal to [-1.77E-5, -1.22E-6, -4.28E-6, -8.97E-6, -1.32E-5, 1.05E-5] (deg) for joints one to six, respectively. The results show that CTC is more accurate but requires additional acceleration input and is more computationally extensive and PD+G controller is performed with acceptable tracking errors in manipulator position control applications.

Modeling, online identification, and compensation control of single tendon sheath system with time-varying configuration

• The transmission models of single TSS with arbitrary route configurations are developed. • A tendon-sheath-based bending sensor is proposed for online parameter identification. • Two compensation strategies are developed to enhance the control accuracy of TSS without distal feedback. • The effectiveness is validated by trajectory tracking and frequency response experiments. Tendon sheath system (TSS) has been widely used in many applications with strict spatial limitations due to its flexibility, dexterity, and remote transmission ability. However, the inherent configuration-dependent nonlinearities between tendon and sheath seriously degrade the transmission performance and result in inaccurate force and position control. In this paper, the force and position transmission models of single TSS with arbitrary route configurations and terminal loads are developed based on the analysis of system friction and deformation. A tendon-sheath-based bending sensor is proposed for the online identification of accumulated bending angle. To enhance the accuracies of force control and position control with time-varying configuration, two control strategies are developed for the friction and deformation compensation without sensory feedback from distal end. An experimental setup of tendon sheath actuation is established to gain insights into the force and position transmission processes and evaluate the effectiveness of the developed transmission models and compensation controllers. The results of model validation experiments with sinusoidal force input show that the modeling errors of force and position transmission are less than 5% and 2.5%, respectively. Moreover, the trajectory tracking experiments and frequency response experiments are carried out, and the results demonstrate the feasibility of the proposed identification strategy and compensation controllers in improving control accuracy and ensuring control bandwidth of single TSS with time-varying bending angle.

Extended harmonic disturbance observer-based attitude control for flexible spacecraft with control moment gyroscopes

In the flexible spacecraft with control moment gyroscopes, there are multiple disturbances including not only internal disturbances from actuators and flexible appendages, but also external disturbances from space environment. These disturbances are characterized by a wide frequency range and may degrade attitude control performance to a great extent. In this paper, the lumped disturbance is modeled as a harmonic plus a polynomial model, and an extended harmonic disturbance observer (EHDO) is proposed to estimate the total disturbance. Since the rotor dynamic imbalance disturbance from control moment gyroscopes is described by an internal harmonic model, the lumped disturbance can be estimated precisely via EHDO even with a lower bandwidth. Afterwards, a backstepping-based composite controller is designed to compensate the disturbances by combining the output of EHDO and realize high-precision attitude control for flexible spacecraft with control moment gyroscopes. Simulation results are presented to demonstrate the effectiveness of the proposed method.

Manipulator Point Teaching System Design Integrated with Image Processing and Iterative Learning Control

This study proposes integrating a manipulator point teaching system with an image processing technique and the iterative learning control (ILC) method, which features multiple points teaching and positioning processes that are easily operated, rapid, and accurate. First, a teaching device is used to manipulate the manipulator, which brings the teaching target into the field of view of camera. The speed up robust feature (SURF) is then used to define the target feature. Then random sample consensus (RANSAC) is used to estimate the homography matrix in order to obtain the center position of the target feature. Subsequently, the manipulator position control command is calculated by referring to the center position. In terms of the computational method, this study uses the ILC method and refers to the manipulator position control command and moving error during iterative computation. Finally, the optimum position control command converges to the manipulator teaching point such that the manipulator can execute automatic and accurate continuous motion according to this teaching point. The method was applied to screw holes and the results show that the average convergence in positioning error is 70%, while the average final positioning error value is less than 15 μm. The experimental results show that the manipulator point teaching system proposed in this study is feasible.

Deadzone compensation control based on detection of micro flow rate in pilot stage of proportional directional valve

The pilot operated proportional directional valves (POPDVs) with a flow rate ranging from 100 to 1000 L/min are widely used in electro-hydraulic systems (EHSs). The deadzone of the pilot stage valve and its control compensation could significantly affect the position control performance for the main stage valve that could directly affect dynamics of EHSs In this paper, it is concluded that micro flow rates exist at the intermediate position of the valve based on the analysis of the continuity equation of the flow in the control chamber of the pilot stage. The micro flow rate is helpful to eliminate the discontinuity and unsmooth domain in the previous inverse deadzone compensation function. An improved deadzone detection method is proposed to calibrate the pilot valve flow characteristics which include the micro flow rate. This new method avoids the threshold selection of the main valve spool displacement which affects the detected deadzone values. Its detection processes are realized based on the pilot flow rate characterized by the speed of the main valve spool and the pilot valve displacement characterized by the solenoid current. The deadzone compensation control strategy based on the improved deadzone detection method is also designed. The experimental results using the steady-state position tracking and sinusoidal position tracking methods are verified. It is concluded that the tracking accuracy of the main valve spool position is effectively improved with this control strategy.

Objective monitoring of attentional states based on collaborative force-position control tasks

Accurate haptic interaction tasks require intensive activation of attentional resources. Exploring the relation between haptic channel and attention is not only conducive to understanding the interaction mechanism between human perception and cognition but is also important for the design of brain-computer interaction system based on haptic modality. In this paper, we built a virtual reality environment incorporating the multiregion force feedback and immersive visual displays and developed a collaborative force-position control task to monitor the attentional states objectively based on this platform. The force and position control performances of users at four different difficulty levels were used to measure the attentional level and attentional spotlight. The users subjective assessment showed that the task can effectively activate attentional resources. The experimental results showed that the task can be used as an attentional oscilloscope to monitor the changes in the attentional level and target of attentional spotlight with a high temporal resolution, providing a behavioral ground truth for exploring attentional biomarkers.

Vision-Based Tip Position Control of a Single-Link Robot Manipulator

Nowadays, robot manipulators are an important part of the automation and control sector, so they indicate the significance of the associated control methodologies. These finds broad applications in various areas, especially in medical, aerospace and industrial assembly processes. Rigid robot manipulators form an important class of manipulators where they interact with the environment physically. Robot manipulator is a non-collocated system that leads to inaccurate system performance. To solve the aforesaid issue, a vision sensor can be employed for direct measurement of tip position instead of the traditional mechanical sensors. The major objective of the work presented here is development of a vision-based method for controlling the tip position of a planar 2-DOF single-link rigid robot manipulator (2DSLRM) from one point to another. In this paper, to achieve the desired tip position, feedback is taken from an encoder and visual sensor from the tip of Single-Link Robot Manipulator (SLRM). The acquired results show that the developed control method improves tip position control performance of 2DSLRM as compared to the traditional mechanical sensors. Simulation and experiment have been performed to study the performance of the proposed tip position control of 2DSLRM.

Study on Variable Impedance Control of Hydraulic Manipulator Based on Double-Weighting-Factor Fuzzy Controller

To improve the force control and position control performance of the hydraulic series manipulator, the author presents a double-weighting-factor fuzzy variable impedance control method, in order to have the manipulator end track the expected force along the environmental surface. Based on the dynamic model of the three-degree-of-freedom hydraulic series manipulator, the contact space and free space of the impedance control are analysed. A fuzzy controller is designed while supposing that the environmental information is known, to get Bd and Kd adjusted. Considering the time-varying characteristics of the system, a fuzzy controller with double weighting factors is designed to enhance the self-adjusting capability and the performance of the fuzzy controller. The simulation result shows that the proposed method achieves a good tracking control of force and position when the environmental parameters are time-varying.

Finite-Time Control of Multirotor UAVs Under Disturbances

A new finite-time control method based on a sliding mode for a multirotor unmanned aerial vehicle (UAV) is developed to improve both the transient and steady-state responses, including overshoot and steady-state error in the presence of uncertainties and external disturbances. First, a virtual control with nonlinear sliding manifolds is designed to achieve position-tracking capability, as well as to guarantee the fast convergence of the UAV to a desired position. Furthermore, an ultimate control is developed for the desired attitude-tracking performance. Various uncertainties, including torque due to the discordance between the centre of mass and rotation and wind disturbances are considered. The Lyapunov stability theorem is then applied step-by-step to prove the asymptotically stable and finite-time convergence in position and attitude controllers. Second, the proposed controller is implemented in an open-source hardware platform for a quadrotor UAV. Both numerical and experimental results are compared to validate the tracking performance for attitude and position control, as well as robustness under disturbances.

Fuzzy intelligent control method for improving flight attitude stability of plant protection quadrotor UAV

At present, the attitude control method of plant protection UAV is the classical PID control, but there are some imperfections in the PID control, such as the contradiction between speediness and overshoot, the weak anti-jamming ability and adaptability. The physical parameters of plant protection UAV are time-varying, and the airflow also interferes with it. The control ability of classical PID is limited, and its control parameters are fixed, and its anti-jamming ability and adaptability are not strong. Therefore, a fuzzy adaptive PID controller is proposed in this paper. Fuzzy logic control is used to optimize the control parameters of PID in order to improve the dynamic and static performance and adaptability of attitude control of plant protection UAV. In the process of research, the mathematical model of UAV is established firstly, then the fuzzy adaptive PID is designed, and then the simulation is carried out in Simulink. The simulation results show that the fuzzy adaptive PID controller has better dynamic and static control performance and adaptability than the traditional PID controller. Therefore, the proposed control method has excellent application value in the attitude of plant protection UAV. Keywords: quadrotor UAV, attitude control, plant protect, fuzzy adaptive PID, Simulink DOI: 10.25165/j.ijabe.20191206.5108 Citation: He Z H, Gao W L, He X K, Wang M J, Liu Y L, Song Y, et al. Fuzzy intelligent control method for improving flight attitude stability of plant protection quadrotor UAV. Int J Agric & Biol Eng, 2019; 12(6): 110–115.

Robust Cascade Path-Tracking Control of Networked Industrial Robot Using Constrained Iterative Feedback Tuning

Industrial robots can be found in many manufacturing applications that suffer from imprecise position control of their own drive systems due to unknown external disturbances and parametric uncertainties. To address this problem, this paper proposes a robust cascade path-tracking control method to achieve better position control performance for a networked industrial robot. In the joint task space, the cascade control framework is formulated for the developed robotic actuation system, which consists of an inner speed loop and an outer position loop. Instead of exploring the conventional model-based approaches, a multiple degree-of-freedom constrained iterative feedback tuning (CIFT) method is presented to regulate the cascade controller by utilizing the monitored process data straightforwardly. With the integration of the normalized input constraints and position tracking error, the proposed CIFT method seeks an optimal solution to track the desired position profiles with satisfactory accuracy and improved robustness. Theoretical analysis is performed to verify the asymptotical convergence of the closed-loop system. Implemented on a real-time networked industrial robot, experimental results demonstrate that the proposed method can enhance the dynamic path tracking and system robustness during various operating situations.

Extended Disturbance Observer With Measurement Noise Reduction for Spacecraft Attitude Stabilization

The attitude stabilization of flexible spacecraft is significantly affected by environmental disturbances, elastic vibration of flexible appendages, and model uncertainties. These disturbances and uncertainties can be accurately estimated by the extended disturbance observer (EDO). However, the EDO is sensitive to measurement noise when high-order and large bandwidth are chosen. Thus, the output of the EDO will contain too much high-frequency noise which can degrade the attitude stability of the spacecraft and cause heavier chattering of the actuators. In order to suppress the effect of measurement noise, a noise reduction EDO (NREDO) is proposed in this paper. First, a dynamical model of disturbance is reconstructed by augmenting the integral of the virtual measurement of the lumped disturbance as a new state. Second, the NREDO is designed by utilizing the estimation error of the augmented state to update the observer estimates. Thereafter, the disturbance estimation accuracy is analyzed for the EDO and NREDO in the frequency domain in the presence of measurement noises. Finally, the simulations are conducted to verify the effectiveness of the proposed controller. The theoretical analysis and simulation results demonstrated that the NREDO can not only effectively suppress the effect of measurement noise, but also inherit the advantages of the EDO in avoiding redundant estimation of the system states and dealing with the nonlinear item of the spacecraft model. Improved attitude control performance can be achieved under the proposed NREDO-based controller.

Adaptive Linear Quadratic Attitude Tracking Control of a Quadrotor UAV Based on IMU Sensor Data Fusion.

In this paper, an infinite-horizon adaptive linear quadratic tracking (ALQT) control scheme is designed for optimal attitude tracking of a quadrotor unmanned aerial vehicle (UAV). The proposed control scheme is experimentally validated in the presence of real-world uncertainties in quadrotor system parameters and sensor measurement. The designed control scheme guarantees asymptotic stability of the close-loop system with the help of complete controllability of the attitude dynamics in applying optimal control signals. To achieve robustness against parametric uncertainties, the optimal tracking solution is combined with an online least squares based parameter identification scheme to estimate the instantaneous inertia of the quadrotor. Sensor measurement noises are also taken into account for the on-board Inertia Measurement Unit (IMU) sensors. To improve controller performance in the presence of sensor measurement noises, two sensor fusion techniques are employed, one based on Kalman filtering and the other based on complementary filtering. The ALQT controller performance is compared for the use of these two sensor fusion techniques, and it is concluded that the Kalman filter based approach provides less mean-square estimation error, better attitude estimation, and better attitude control performance.

Current-pressure-position triple-loop feedback control of electro-hydrostatic actuators for humanoid robots

ABSTRACTTo overcome the tradeoff between torque density and response of the backdrivable actuators, actuation by electro-hydrostatic actuators (EHA) is effective. While their backdrivability and energy efficiency was shown in the previous studies, their closed-loop dynamic behavior was not discussed in detail. In this paper, we present the analysis and experimental evaluation of the force control performance of the electro-hydrostatic actuator for the humanoid robot ‘Hydra’. We first present a simplified model of EHA and show that EHA can be simplified as a mass-spring-damper model if all values such as pump torque/velocity and fluid pressure/flow-rate are expressed in the equivalent value seen from the actuator. We also show the comparison between the model and experimentally acquired open-loop dynamic behavior. Then, the evaluation on the force measurement and control performance is shown. The static friction on the rod-seal was 0.46% of the maximum piston force, and with additional strain gauge information, the error can be reduced to 0.28% of the maximum force. We also show that our developed EHA has a pressure control bandwidth of 100 Hz in the fixed piston configuration, which is higher than other state-of-the-art series elastic actuators. In the last of paper, the joint level position and torque control performance of Hydra is examined.

Position‐sensorless adaptive positioning control system for IPMSMs

Position-sensorless positioning control system of interior permanent magnet synchronous motors (IPMSMs) has been energetically researched for high reliability and cost reduction. To achieve fast response of positioning servo systems, accurate parameters of IPMSMs are required. The parameters vary due to temperature and/or ageing, which results in degradation of the positioning control performance. Thus, this study proposes a position-sensorless adaptive positioning control system for IPMSMs using the dynamic certainty equivalence principle for stable parameter identification. In addition, comb filters are used for fast estimation instead of low-pass filters. Experiments are demonstrated to validate the effectiveness and the feasibility of the proposed method.