Maximum Displacement Error Research Articles

The Itappachi Universal Motion Platform for Accurate Dose Measurement in Thoracoabdominal Radiotherapy.

We developed the "Itappachi" universal motion platform for measuring radiation doses under simulated respiratory motion in radiation therapy. The interplay effect, resulting from respiratory motion, degrades dose delivery precision in advanced treatments such as volumetric modulated arc therapy. The Itappachi platform is designed for precise dose measurement in dynamic scenarios through its ability to simulate respiratory motion. The platform features a large surface (580 mm × 380 mm), capable of supporting weights up to 56.8 kg, and moves with an amplitude of ±25 mm. It requires no silicone oil for maintenance, and it is controlled via Wi-Fi using user-owned devices, thereby reducing costs. Its motion accuracy was confirmed, with a maximum displacement error of 0.12 mm. Using the platform, we conducted dose measurements with a Delta4 Phantom under static, moving without gated irradiation, and moving with gated irradiation conditions. Gamma index analysis revealed excellent agreement for static and dynamic gated conditions (99.4%), while significant dose degradation occurred in the non-gated dynamic condition (32.6%). The Itappachi platform provides a cost-effective and accurate solution for dose measurement under respiratory motion by which it supports improved quality assurance in radiation therapy.

Dynamic modeling and energy demand analysis of chain heavy load transfer system on marine mobile platform

ABSTRACT The demand for transferring the heavy load on marine mobile platform is steadily increasing, surpassing the capabilities of the current system. This paper introduces a chain heavy load transfer system and develops its dynamic model. This paper studies the sensitivity laws of the system’s energy demand to unknown parameters and proposes an adaptive mutation particle swarm optimization (AMPSO), whose identification accuracy is verified through comparative analysis. Experimental verification confirms the reliability of the system model while studying the influence of environmental loads on the system’s energy demand. The results demonstrate that the chain transfer system meets the requirements of marine mobile platforms, and the system model incorporates the primary influencing factors. Unknown parameters significantly influence the system’s energy demand, and the displacement error after parameter identification using AMPSO is 0.00056 rad, substantially enhancing the accuracy of model calculations. The model calculations of the system closely align with experimental measurements, with a maximum displacement error not exceeding 0.004 rad. Sway exerts a greater influence on the system’s energy demand compared to tilt. When tilt and sway are superimposed, the friction torque between the load and the track results in increased input torque and power for the vertical arrangement of the system, with a maximum torque of 328.6kN·m and maximum power of 400 kW.

Vehicle vibration test platform structure design and control strategy optimization

AbstractFor the needs of vehicle vibration test platform with high precision, large load capacity and fast response, the three‐dimensional model design and analysis of vehicle vibration test platform are carried out; in order to improve the motion performance of the platform, a vibration test plat‐form control strategy combining hybrid heuristic algorithm and PID control is proposed. Based on the designed 3D model parameters, the single‐channel mathematical model of the servo‐electric cylinder is derived and a hybrid heuristic algorithm PID optimization model is established to compare and analyze the control performance of the platform with the Ziegler‐Nichols method PID. The results show that the step system overshoot is 3.80% and the dynamic performance of the system is significantly improved when the hybrid heuristic algorithm PID control is used. The simulation system model of vehicle vibration test platform control is established, and the operation results show that the platform is closer to the input signal in the spatial position change curve when the hybrid heuristic algorithm PID control is used. Its maximum displacement error is 0.09 mm, and the motion accuracy of the system is improved by 61% compared with the Ziegler‐Nichols method PID control.

Modular approximate discrete modeling for blisk system with triple closed-loop equivalence method

At present, the lumped-parametric model is often used in the preliminary design of bladed disks. However, the lack of systematic modeling methods leads to high errors. In order to develop the systematic modeling method and improve the equivalence accuracy, this paper considers the comprehensive equivalence from the aspects of natural characteristics, transient forced responses, and steady-state forced responses under aerodynamic excitations. This paper includes two novelties. First, based on the modular equation of blisk system, an approximate discrete model is derived for computational efficiency. Second, a triple closed-loop equivalence method with modal weight optimization is developed innovatively for optimal equivalence parameters. The method can significantly improve the accuracy of element parameters in the lumped-parametric model and achieve the comprehensive equivalence to actual blisk. Compared with the existing equivalence method, the average errors of natural frequencies in the whole mode interval and in the high-density mode interval are reduced by 41.75 % and 36.76 %, respectively. The maximum and average displacement errors of the transient response are reduced by 51.76 % and 58.98 %, respectively. Furthermore, vibration characteristics of the mass and stiffness mistuned blisks are analyzed under traveling wake excitation during acceleration and deceleration processes by approximate discrete model and determined parameters.

Long-Travel 3-PRR Parallel Platform Based on Biomimetic Variable-Diameter Helical Flexible Hinges.

Technological advancements across various sectors are driving a growing demand for large-scale three-degree-of-freedom micro-nano positioning platforms, with substantial pressure to reduce footprints while enhancing motion range and accuracy. This study proposes a three-prismatic-revolute-revolute (3-PRR) parallel mechanism based on biomimetic variable-diameter helical flexible hinges. The resulting platform achieves high-precision planar motion along the X- and Y-axes, a centimeter-level translation range, and a rotational range of 35° around the Z-axis by integrating six variable-diameter flexible helical hinges that serve as rotational joints when actuated by three miniature linear servo drives. The drives are directly connected to the moving platform, thereby enhancing the compactness of the system. A kinematic model of the motion platform was established, and the accuracy and effectiveness of the forward and inverse kinematic solutions were validated using finite element analysis. Finally, a prototype of the 3-PRR parallel platform was fabricated, and its kinematic performance was experimentally verified visually for improved endpoint displacement detection. The assessment results revealed a maximum displacement error of 9.5% and confirmed that, judging by its favorable workspace-to-footprint ratio, the final system is significantly more compact than those reported in the literature.

Trajectory Tracking Control of Fast Parallel SCARA Robots with Fuzzy Adaptive Iterative Learning Control for Repetitive Pick-and-Place Operations

Aiming at enhanced suppression of external disturbances and high-precision trajectory tracking of parallel SCARA robot dedicating to fast pick-and-place operations, this work presents the integrated control design of iterative learning algorithm, adaptive control and fuzzy rules, namely, fuzzy adaptive iterative learning control, for such type of robots. A step-design approach is adopted to ensure the adaptability of the designed control law, which is reflected in two aspects: ① the feedback gain of the controller is adjusted by the fuzzy rules; ② the adaptive unknown parameters are obtained by means of iterative learning estimation to suppress the uncertainties and external disturbances. The stability of the designed controller is analyzed and proved by the Lyapunov theory, and the effectiveness is verified by observing the tracking errors in joint space along with the testing pick path, in comparison with different iterative learning based algorithms. After the first-iteration learning, the motion errors of the four actuated joints can be reduced by 56.5%, 45.8%, 46.4% and 39.8%, respectively, and after 15 iterations of learning control, the final angular errors by the designed control law converge to 0.7×10−4 degree maximally. The varying maximum, root-mean-squared and mean angular displacement errors of the actuation joints can converge to zero values with the increasing iterations rapidly, which shows the robustness, effectiveness and advantages of the designed control law. The designed control law can be generalized to high-speed parallel pick-and-place robot to ensure high-precision trajectory tracking for high-quality material handling tasks.

Quantifying the Effects of Network Latency for a Teleoperated Robot.

The development of teleoperated devices is a growing area of study since it can improve cost effectiveness, safety, and healthcare accessibility. However, due to the large distances involved in using teleoperated devices, these systems suffer from communication degradation, such as latency or signal loss. Understanding degradation is important to develop and improve the effectiveness of future systems. The objective of this research is to identify how a teleoperated system's behavior is affected by latency and to investigate possible methods to mitigate its effects. In this research, the end-effector position error of a 4-degree-of-freedom (4-DOF) teleultrasound robot was measured and correlated with measured time delay. The tests were conducted on a Wireless Local Area Network (WLAN) and a Virtual Local Area Network (VLAN) to monitor noticeable changes in position error with different network configurations. In this study, it was verified that the communication channel between master and slave stations was a significant source of delay. In addition, position error had a strong positive correlation with delay time. The WLAN configuration achieved an average of 300 ms of delay and a maximum displacement error of 7.8 mm. The VLAN configuration showed a noticeable improvement with a 40% decrease in average delay time and a 70% decrease in maximum displacement error. The contribution of this work includes quantifying the effects of delay on end-effector position error and the relative performance between different network configurations.

Design of a Teat Cup Attachment Robot for Automatic Milking Systems

Automatic milking systems (AMSs) for medium and large dairy farms in China require manual assistance to attach the teat cup, which greatly affects the milking efficiency and labor costs. In this regard, it is necessary to realize the automatic completion of cow teat attachment work. To address this issue, the authors developed a teat cup attachment robot for an AMS based on the theory of the solution of inventive problems (TRIZ). Specifically, we developed an enhanced algorithm for teat detection and designed a six-degree-of-freedom manipulator with integrated drive control. The design parameters were simulated and analyzed to validate their efficacy, while the rationality of the manipulator’s movement during teat cup attachment was verified. The maximum displacement and angle error of the cup was 1.625 mm and 1.216 mm, respectively, as verified by the teat cup attachment error test. A dynamic response test showed that the manipulator could follow the teat of the cow in real time. The attachment time for teat cups was 21 s per cow, with a success rate of 98%. The performance of the teat cup attachment robot was capable of meeting the automatic attachment teat cup needs for medium and large dairy farms during milking.

A Study on the Applicability and Accuracy of the Discrete Element Method for Plates Based on Parameter Sensitivity Analysis

In order to verify the accuracy and applicability of the discrete element method (DEM) in dealing with geometrically large deformations of continuous plate structures, both a single-parameter analysis and an orthogonal design method were adopted to analyze the displacement responses of the plate structures and were compared with those calculated using the finite element method (FEM). The single-parameter change condition involved the thickness-to-width ratio, elastic modulus, or Poisson’s ratio, while the multi-parameter change included boundary conditions, dimensions, load forms, thickness-to-width ratio, elastic modulus, and Poisson’s ratio. The results showed that displacements of the target locations were basically identical to those obtained according to FEM, with a maximum error of less than 5% under the single-parameter change condition. The maximum displacement error of the plate structures calculated using the DEM and FEM, respectively, was 4.212%, and the mean error and extreme difference of error parameters were 2.633% and 2.184%, respectively. These results indicate that the displacements of the plate structures calculated using the DEM were highly consistent with those obtained according to the FEM. Additionally, single-parameter changes and multi-parameter changes barely influenced the accuracy and suitability of the DEM in solving displacement response problems of plate structures. Therefore, the DEM is applicable in terms of dealing with displacement response problems of plate structures.

A balanced jumping control algorithm for quadruped robots

The jumping movement of quadruped robots is crucial, so a complete set of balanced jumping algorithms is proposed in this paper due to the flaws of the current jumping algorithms. The proposed algorithm includes trajectory planning of the Center of Mass(CoM) and four jumping phases, illustrating the jumping process in detail. Tasks that a quadruped robot with the height of 0.6 m jumps up a step with the height of 0.3 m, 0.4 m, 0.5 m and 0.6 m are the research object. Optimal Parabola Trajectory of CoM(OPTC) is solved by about ten iterations based on the fastest approaching strategy before jumping. During the first phase of jumping, Ground Reaction Forces(GRFs) are precisely distributed to control six Degrees of Freedom(DoFs) based on symmetric six-dimensional spatial mechanics decoupling solution, controlling the robot to adjust itself to the best ejecting posture. The maximum displacement error is less than 0.005 m. During the second phase, full-leg ejection is implemented to eject, guaranteeing that the robot accurately tracks the OPTC after takeoff by updating proportional virtual forces. The tracking Mean Square Error(MSE) is less than 0.06. During the third phase, the flying attitude is adjusted by swinging leg theory summarized in the paper, with the maximum pitch angle less than 4.5°. Meanwhile, the theoretical landing points of feet are calculated to lead the movement of feet, ensuring a soft landing to reduce touchdown impact. The momentary landing velocities of feet are less than 0.09 m/s. During the fourth phase, the robot buffers and brakes to a static state based on the algorithm used in the first phase. Eventually, the proposed algorithms are verified through simulating experiments on Webots physical engine, and the effectiveness and feasibility are validated by the experimental results.

Feedforward Control of Piezoelectric Ceramic Actuators Based on PEA-RNN.

Multilayer perceptron (MLP) has been demonstrated to implement feedforward control of the piezoelectric actuator (PEA). To further improve the control accuracy of the neural network, reduce the training time, and explore the possibility of online model updating, a novel recurrent neural network named PEA-RNN is established in this paper. PEA-RNN is a three-input, one-output neural network, including one gated recurrent unit (GRU) layer, seven linear layers, and one residual connection in the linear layers. The experimental results show that the displacement linearity error of piezoelectric ceramics reaches 8.96 m in the open-loop condition. After using PEA-RNN compensation, the maximum displacement error of piezoelectric ceramics is reduced to 0.465 m at the operating frequency of 10 Hz, which proves that PEA-RNN can accurately compensate piezoelectric ceramics’ dynamic hysteresis nonlinearity. At the same time, the training epochs of PEA-RNN are only 5% of the MLP, and fewer training epochs provide the possibility to realize online updates of the model in the future.

An Adaptive Constrained Path Following Control Scheme for Autonomous Electric Vehicles

To ensure driving safety, autonomous electric vehicles need to follow the planned path accurately, which depends on the vehicle path following control strategy. It is widely acknowledged that the model-based control strategies have excellent potential on path following, but their effect is seriously affected by the parametric uncertainty. To solve this problem, an adaptive constrained path following control scheme considering the influence of parametric uncertainty is proposed for autonomous electric vehicles. Firstly, an adaptive feedback control law and its update law are proposed to deal with the variation of tire cornering stiffness during vehicle path following process. Secondly, a constraint function for lateral displacement error during path following process is designed to further improve driving safety. And then, the closed-loop stability of the proposed control scheme is proved. Finally, the validation is implemented by simulation and experiment, the results show that the proposed control scheme is effective under different working conditions. The maximum lateral displacement error is reduced to 0.0297m by using the proposed scheme in the experiment. The proposed scheme might provide a theoretical reference for control practice of autonomous vehicles.

Model predictive control of hydraulic drive unit considering input delay

Hydraulic drive unit (HDU) is a typical actuator, but the characteristic of input delay hinders the application of many advanced control methods in HDU. First, in this paper, a mathematical model of HDU with input delay is established and the parameters are identified. Then, aiming at the input delay problem in HDU, a Smith estimated compensation model predictive control (SECMPC) strategy is proposed. On the one hand, the input delay state equation is employed to be a mathematical pattern for the state observation and predictive model. However, the combination between model predictive control (MPC) and Smith estimated compensation (SEC) is realized, the system state at k + d (d is the time delay coefficient) time is estimated in advance at k time to compensate the delay of the state. And then the prediction model based on input delay state equation is used for model prediction and rolling optimization. Thus, the delay system which is unstable is promoted to a stable system without delay. The effectiveness of SECMPC is proved with the HDU experiment and simulation; the maximum experimental displacement error of traditional MPC control is 15 mm, while that of SECMPC control is 8 mm. The SECMPC have some guiding significance for the control of systems with input delay.

Evaluation of the Path-Tracking Accuracy of a Three-Wheeled Omnidirectional Mobile Robot Designed as a Personal Assistant.

This paper presents the empirical evaluation of the path-tracking accuracy of a three-wheeled omnidirectional mobile robot that is able to move in any direction while simultaneously changing its orientation. The mobile robot assessed in this paper includes a precise onboard LIDAR for obstacle avoidance, self-location and map creation, path-planning and path-tracking. This mobile robot has been used to develop several assistive services, but the accuracy of its path-tracking system has not been specifically evaluated until now. To this end, this paper describes the kinematics and path-planning procedure implemented in the mobile robot and empirically evaluates the accuracy of its path-tracking system that corrects the trajectory. In this paper, the information gathered by the LIDAR is registered to obtain the ground truth trajectory of the mobile robot in order to estimate the path-tracking accuracy of each experiment conducted. Circular and eight-shaped trajectories were assessed with different translational velocities. In general, the accuracy obtained in circular trajectories is within a short range, but the accuracy obtained in eight-shaped trajectories worsens as the velocity increases. In the case of the mobile robot moving at its nominal translational velocity, 0.3 m/s, the root mean square (RMS) displacement error was 0.032 m for the circular trajectory and 0.039 m for the eight-shaped trajectory; the absolute maximum displacement errors were 0.077 m and 0.088 m, with RMS errors in the angular orientation of 6.27° and 7.76°, respectively. Moreover, the external visual perception generated by these error levels is that the trajectory of the mobile robot is smooth, with a constant velocity and without perceiving trajectory corrections.

Development of a Reference-Free Indirect Bridge Displacement Sensing System

Bridge displacement measurements are important data for assessing the condition of a bridge. Measuring bridge displacement under moving vehicle loads is helpful for rating the load-carrying capacity and evaluating the structural health of a bridge. Displacements are conventionally measured using a linear variable differential transformer (LVDT), which needs stable reference points and thus prohibits the use of this method for measuring displacements for bridges crossing sea channels, large rivers, and highways. This paper proposes a reference-free indirect bridge displacement sensing system using a multichannel sensor board strain and accelerometer with a commercial wireless sensor platform (Xnode). The indirect displacement estimation method is then optimized for measuring the structural displacement. The performance of the developed system was experimentally evaluated on concrete- and steelbox girder bridges. In comparison with the reference LVDT data, the maximum displacement error for the proposed method was 2.17%. The proposed method was successfully applied to the displacement monitoring of a tall bridge (height = 20 m), which was very difficult to monitor using existing systems.

A membrane equivalent method to reproduce the macroscopic mechanical responses of steel wire-ring nets under rockfall impact

Steel wire-ring nets, which have complex nonlinear mechanical behaviour, are widely used in rockfall protection engineering. At present, the circular beam model with a discrete contact boundary is the most accurate method to simulate steel wire-ring nets’ mechanical responses, but its computational efficiency is low. This paper hereby proposes a membrane equivalence-based continuum simulation method: the membrane equivalent method (MEM)11MEM: abbreviation of the membrane equivalent method proposed in this paper to reproduce the macroscopic mechanical behaviour of steel wire-ring nets.. This study’s aim is to greatly improve the computational efficiency of numerical models through the MEM without compromising computational accuracy in macroscopic mechanical behaviour, compared to the circular beam model. According to the out-of-plane loading experimental results of the net panel and membrane analytical model of orthogonal tension belts, an exponential hardening constitutive model of the equivalent membrane was derived. The MEM’s material parameters were corrected in numerical models for a less than 10% error between the simulated and experimental results. Under the rigid boundary condition, the net panel impact simulation results established by the MEM agreed with extant literature’s experimental results, the peak acceleration error was 4.3%, and the rebound characteristic of the net was reproduced. Under the flexible boundary condition, the MEM’s obtained maximum impact displacement and impact force errors were 10.3% and 7.7%, respectively, compared to 3000 kJ full-scale impact experimental results. The MEM’s computational efficiency can be increased almost tenfold compared to that of the circular beam model.

Research on Dynamic Structure Displacement Monitoring Based on Feature Optical Flow Method

In view of the difficulty of sensor installation and complicated process in traditional structure health monitoring, a feature point monitoring based on optical flow is proposed in this paper. A high-speed camera is applied to capture the dynamic response of the structure under excitation, and feature point could be selected and marked at any position in the video. The movement of the selected point could be traced and calculated by feature optical flow method, and the displacement time series of the feature point could be obtained. Results show that the displacement time series obtained from proposed method in this paper is consistent with the data of the pull-wire displacement sensor, the maximum displacement error is 3.3%, the method proposed is more flexible, convenient and of low cost.

Planning the trajectory of an autonomous wheel loader and tracking its trajectory via adaptive model predictive control

In a typical operation mode, a wheel loader frequently accelerates and decelerates, and the curvature of the driving path is inconsistent. In the past, autonomous vehicle trajectory planning has not considered the related changes in the velocity of the vehicle. Therefore, the trajectory tracking control process has seldom considered the impact of curving paths on the trajectory tracking performance. To address these problems, this study evaluated an autonomous wheel loader based on the trajectory of its non-uniform driving motion and constructed an adaptive model predictive control (AMPC) trajectory tracking system that considers disturbances in the path curvature. The trajectory of the autonomous wheel loader was then tracked using the proposed AMPC system with a planned non-uniform motion trajectory as the target. Its performance was then compared with that of a conventional model predictive control (MPC) trajectory tracking system that does not consider any path curvature disturbances. The maximum displacement error and heading error obtained by the proposed AMPC system were found to be 65.7% and 60%, respectively, smaller than those obtained by the MPC system. The desired trajectory can also be tracked well under different curvature amplitudes using the AMPC trajectory tracking system, ensuring active safety performance of an autonomous wheel loader in the process of trajectory tracking.

Extraction of topographic deformation based on the 3D information of individual trees

ABSTRACT Terrestrial laser scanning (TLS) has been used widely in topographic deformation monitoring, and the issue of deformation information extraction from multi-temporal point cloud data has high importance. Here, a method is developed for the extraction of topographic deformation in a forested area based on the 3D spatial information of individual trees. Initially, ground points are removed by using a local topographic surface fitting method, then individual trees are segmented using the PTrees algorithm; finally, the motion of individual trees is computed with a combination of global and local rigid-body transformations. Experimental validation results show that the proposed method is reliable to within a 0.12° maximum tilt error and 8.7 mm maximum displacement error. In addition, some inferences were drawn based on the original topography and the topographic deformation monitoring results. For example, a mining work-face was located beyond the eastern part of the study area, and trees growing in the middle part of this region of interest may face a survival challenge.

Path Tracking of Mining Vehicles Based on Nonlinear Model Predictive Control

Path tracking of mining vehicles plays a significant role in reducing the working time of operators in the underground environment. Because the existing path tracking control of mining vehicles, based on model predictive control, is not very effective when the longitudinal velocity of the vehicle is above 2 m/s, we have devised a new controller based on nonlinear model predictive control. Then, we compare this new controller with the existing model predictive controller. In the results of our simulation, the tracking accuracy of our controller at the longitudinal velocity of 4 m/s is close to that of the existing model predictive controller, at the longitudinal velocity of 2 m/s. When longitudinal velocity is 4 m/s, the existing model predictive controller cannot drive the mining vehicle to track the given path, but our nonlinear model predictive controller can, and the maximum displacement error and heading error are 0.1382 m and 0.0589 rad, respectively. According to these results, we believe that this nonlinear model predictive controller can be used to improve the performance of the path tracking of mining vehicles.