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Base on the accurate inverse of a system, the feedforward compensation method can compensate the tracking error of a linear system dramatically. However, many control systems have complex dynamics and their accurate inverses are difficult to obtain. In the paper, a variable parameter model is proposed to describe a system and a multi-step adaptive seeking approach is used to obtain its parameters in real time. Based on the proposed model, a variable-parameter-model-based feedforward compensation method is proposed, and a disturbance observer is used to overcome the influence of the model uncertainty. Theoretical analysis and simulation results show that the variable-parameter-model-based feedforward compensation method can obtain better performance than the traditional feedforward compensation.

In a tunneling boring machine (TBM), to obtain the attitude in real time is very important for a driver. However, the current laser targeting system has a large delay before obtaining the attitude. So, an adaptive-neuro-fuzzy-based information fusion method is proposed to predict the attitude of a laser targeting system in real time. In the proposed method, a dual-rate information fusion is used to fuse the information of a laser targeting system and a two-axis inclinometer, and then obtain roll and pitch angles with a higher rate and provide a smoother attitude prediction. Considering that a measurement error exists, the adaptive neuro-fuzzy inference system (ANFIS) is proposed to model the measurement error, and then the ANFIS-based model is combined with the dual-rate information fusion to achieve high performance. Experimental results show the ANFIS-based information fusion can provide higher real-time performance and accuracy of the attitude prediction. Experimental results also verify that the ANFIS-based information fusion can solve the problem of the laser targeting system losing signals.

The force control of an industrial robot, as a significant control strategy, enables a robot to perform contact assignment or be guided by humans in free space. The existing six-dimensional force sensors installed at the end of manipulators own only one perceptual unit, which fail to detect the traction force given by one's hands accurately when the end effector contacts with the manipulated objects. In this study, a six-dimensional traction force sensor has been developed to measure the traction force, based on which a tandem type force sensor that can detect the traction force and contact force simultaneously is proposed. The tandem type force sensor consists of a general six-dimensional force sensor, which is used to measure the contact force between the end effector and the manipulated objects, and a six-dimensional traction force sensor, which is used to measure the traction force exerted by one's hand. The basic structure of the six-dimensional traction force sensor is designed, and the calibration experiment verifies the six-dimensional traction force sensor performs well.

Most existing methods rely on the torque information of a servo drive to predict the tracking error caused by the friction force (friction error), but the torque information is not available in certain systems. This paper proposes a position-based modeling method for the friction error. Two examples are given to verify the practicality of the proposed friction error model on the systems when torque information is not available. The experimental results show that the proposed method can predict the friction error accurately and the proposed online parameter identification method exhibits better performance. The proposed position-based friction error model can also be easily applied to commercial CNC systems because only the position information is required.

In this paper, the research on the kinematic mechanism of the shield machine is carried out by using the analytical method of parallel mechanism kinematics for the demand of the shield machine’s position solution, and the kinematic expressions of the position and attitude of the shield machine are derived, which can be used for the real-time solution of the shield machine’s position solution. Finally, the kinematic solution is also verified by using the data from the engineering site, and the results show the correctness of the derived kinematics algorithm.

It is an important reform for medical education in China to combine professional postgraduate training with standardized resident training. This study aims to evaluate the depression and perceived stress in postgraduate students of clinical medicine and residents from society and to determine the relation between depression and perceived stress in medical residents.Chinese Perceived Stress Scale (CPSS) and Self-Rating Depression Scale (SDS) were applied to 330 residents (including 235 postgraduate students of clinical medicine and 95 residents from society) from a Class-A Grade-3 genernal hospital in Hunan Province to evaluate and compare the depression and perceived stress in postgraduate students of clinical medicine and residents from society. Pearson correlation analysis was performed to assess the association between depression and perceived stress. Stress resources between 2 groups of residents were observed and compared.Of the 235 postgraduate students of clinical medicine, 148 (63.0%) showed depression and 162 (68.9%) showed elevated perceived stress. Main stress resources were academic pressure, scientific research pressure, and employment pressure. Of the 95 residents from society, 52 (54.7%) showed depression and 58 (61.1%) showed elevated perceived stress. Main stress resources were economic stress, employment pressure, and academic pressure. The scores of CPSS and SDS were significantly higher in postgraduate students of clinical medicine than those in residents from society (Residents (including postgraduate students of clinical medicine and residents from society) possess depression and elevated perceived stress with positive correlation. The postgraduate students of clinical medicine show higher level of depression and perceived stress than the residents from society under the "unified double-track" training system.

Laser triangulation sensors (LTS) are widely used to acquire depth information in industrial applications. However, the parameters of the components, e.g., the camera, of the off-the-shelf LTS are typically unknown. This makes it difficult to recalibrate the degenerated LTS devices during regular maintenance operations. In this paper, a novel one-dimensional target-based camera intrinsic matrix-free LTS calibration method is proposed. In contrast to conventional methods that calibrate the LTS based on the precise camera intrinsic matrix, we formulate the LTS calibration as an optimization problem taking all parameters of the LTS into account, simultaneously. In this way, many pairs of the camera intrinsic matrix and the equation of the laser plane can be solved and different pairs of parameters are equivalent for displacement measurement. A closed-form solution of the position of the one-dimensional target is proposed to make the parameters of the LTS optimizable. The results of simulations and experiments show that the proposed method can calibrate the LTS without knowing the camera intrinsic matrix. In addition, the proposed approach significantly improves the displacement measurement precision of the LTS after calibration. In conclusion, the proposed method proved that the precise camera intrinsic matrix is not the necessary condition for LTS displacement measurement.

In view of the complicacy and the diversity of inertinite macerals of coal, a classification method based on linear discriminate analysis (LDA) and support vector machine (SVM) is proposed. Firstly, according to differences of texture and intensity among macerals, inertinite macerals are represented with texture related features as energy, entropy, moment, local smooth and intensity related features as contrast, mean, standard deviation, 3-order moment deviation. Then, by using LDA, the initial features are further extracted by means of maximizing the inter-class dispersion as well as minimizing intra-class scatter. Finally, a classifier based on SVM with radial basis function (RBF-SVM) is built for the automatic classification of inertinite macerals. Experimental results show that, textures employed in this paper can present inertinite macerals effectively; with LDA and RBF-SVM, the dimension of feature space is reduced and the accuracy of classification is increased obviously.

The manual disc cutter changing of the shield machine has greater security hidden danger, which leads to the urgent need to develop a disc cutter changing robot to replace the over-worn disc cutters. The rotation positioning error of the large diameter cutter head, the motion control error of the disc cutter changing robot, and the complexity of the disc cutter changing bin environment lead to the inaccuracy of the actual pose of the disc cutter. Therefore, it is necessary to increase the machine vision measurement system to accurately measure the pose of the disc cutter or its holder. This paper proposes a cutter holder positioning method, which uses the parallel line features and actual contour area of the cutter holder to determine its initial pose, and then uses the initial pose to calculates its accurate pose based on the distance matching method. The innovation of the method is that the pose measurement is carried out through the unique characteristics of the cutter holder, and it combines the initial pose estimation method based on the geometric characteristics of the cutter holder with the distance matching method which depends on the initial pose to solve the cutter holder pose. Simulation analysis shows that the accuracy of the proposed method is close to that of the most advanced PnP algorithms, and its robustness is better than others. Experimental results also verify the high accuracy of the proposed method.

Iterative learning control (ILC) can synthesize the feedforward control signal for the trajectory tracking control of a repetitive task, even when the system has strong nonlinear dynamics. This makes ILC be one of the most popular methods for trajectory tracking control. Restriction on a repetitive task, however, limits its application to multiple trajectories. This article proposes a neural-network-based ILC (NN-ILC) to deal with nonrepetitive tasks very effectively. A position-based ILC is designed to compensate the tracking error, based on which the multiple outputs of the ILC (ILC outputs) for multiple tasks are expressed as a function of the reference position, velocity, and acceleration. The proposed NN-ILC divides the ILC outputs of multiple tasks into two parts: the linear and nonlinear portions. The first part is expressed by a linear function, which is the linear portion of the function of the ILC outputs. The second part is expressed by a nonlinear function, which is estimated by complementary neural networks including a general neural network and a switching neural network. Finally, the two parts are combined and the ILC outputs of multiple tasks are expressed as a neural-network-based function. Two advantages of the proposed NN-ILC are emphasized. First, the ILC outputs of multiple tasks are compressed into a function by the proposed method, and thus, the memories can be saved. Second, in terms of generalizability, the neural-network-based function of the ILC outputs can easily predict position compensation for multiple tasks without extra iterative learning processes. Experimental results on a robot arm show that the proposed NN-ILC method can easily realize the ILC of multiple tasks. It can save memory comparing with the method of storing the data of multiple tasks and can predict the ILC output of any task, which can accelerate the iterative learning process.

In robot teaching for contact tasks, it is necessary to not only accurately perceive the traction force exerted by hands, but also to perceive the contact force at the robot end. This paper develops a tandem force sensor to detect traction and contact forces. As a component of the tandem force sensor, a cylindrical traction force sensor is developed to detect the traction force applied by hands. Its structure is designed to be suitable for humans to operate, and the mechanical model of its cylinder-shaped elastic structural body has been analyzed. After calibration, the cylindrical traction force sensor is proven to be able to detect forces/moments with small errors. Then, a tandem force sensor is developed based on the developed cylindrical traction force sensor and a wrist force sensor. The robot teaching experiment of drawer switches were made and the results confirm that the developed traction force sensor is simple to operate and the tandem force sensor can achieve the perception of the traction and contact forces.

The iterative pre-compensation method can predict the optimal pre-compensation value and compensate the tracking error effectively, but the compensation effect decreases if parameters of drive systems change. This paper proposes a variable-parameter-model-based iterative pre-compensation method of the tracking error, which can predict the optimal pre-compensation value when parameters of drive systems change. The proposed iterative pre-compensation method of the tracking error can be used to compensate the tracking error of any trajectory by using the predicted pre-compensation value. There are three contributions in detail. Firstly, a variable-parameter-model-based iterative pre-compensation method of the tracking error is proposed based on the designed iterative pre-compensation (IPC) model. Secondly, the data-driven pre-compensation method is proposed to obtain the uncertain portion of the pre-compensation value and adapt to the change of the moment-of-inertia. Thirdly, the identification method of the moment-of-inertia is proposed and applied to the data-driven pre-compensation. In the end, experiments were conducted to verify the proposed iterative pre-compensation method and the experimental results show that the variable-parameter-model-based iterative pre-compensation method of the tracking error can reduce the tracking error and adapt to the change of the moment-of-inertia.

Objective This experimental study set out to examine the effects of performance feedback (success or failure) on depressed emotions and self-serving attribution bias in inpatients suffering from major depressive disorder (MDD). Methods The study was based on a 2 × 2 experimental design in which 71 MDD patients and 59 healthy controls participated. Both groups (MDD and controls) were randomly assigned to two conditions: success or failure in the performance feedback. A section of Raven's Standard Progressive Matrices (SPM) was used as a bogus test of the participants' reasoning abilities, and the Core Depressive Factor of the Zung Self-Rating Depression Scale was used to measure changes in depressed emotion in the subjects following the performance feedback. Participants then rated the accuracy of the SPM as a measure of their reasoning capacity. Results The levels of depressed emotions in patients with MDD did not differ significantly under the two feedback conditions. In contrast, depressed emotion levels increased significantly in healthy individuals in response to failure feedback but did not change in response to success feedback. With regard to the ratings of SPM accuracy, there was no significant difference across the two feedback conditions for depressed patients; however, the accuracy ratings were higher in the success condition than in the failure condition for the controls. Conclusion Individuals with MDD exhibit blunted emotional reactivity when experiencing new positive or negative social stimuli, supporting the theory of Emotion Context Insensitivity. In addition, self-serving attribution bias does not occur in MDD, which is consistent with the theory of learned helplessness in depression.

This paper discussed the calibration of the relative pose of the stereo-camera. The rotation matrix estimation involved in this problem is typical instances of the single rotation averaging and conjugate rotation averaging problem. In order to avoid the ambiguity caused by the angle-axis and quaternion representations and obtain the global solution, a convex relation method is proposed for chordal metric under L-2 norm. In addition, a weighted robust cost function for the rotation averaging problems is also proposed to deal with the additional information about the measurements of the rotation and all the data including the outliers. The experimental results show that this method works efficiently and reliably. Meanwhile, the optimality is certified most of the time within a few sequence of linear matrix inequalities.

Considering the heterogeneous nature and non-stationary property of inertinite components, we propose a texture description method with a set of multifractal descriptors to identify different macerals with few but effective features. This method is based on the multifractal spectrum calculated from the method of multifractal detrended fluctuation analysis (MF-DFA). Additionally, microscopic images of inertinite macerals were analyzed, which were verified to possess the property of multifractal. Simultaneously, we made an attempt to assess the influences of noise and blur on multifractal descriptors, the multifractal analysis was proven to be robust and immune to image quality. Finally, a classification model with a support vector machine (SVM) was built to distinguish different inertinite macerals from microscopic images of coal. The performance evaluation proves that the proposed descriptors based on multifractal spectrum can be successfully applied in the classification of inertinite macerals. The average classification precision can reach 95.33%, higher than that of description method with gray level co-occurrence matrix (GLCM, about 7.99%).

Linear motion commands of multi-axis computer numerical control (CNC) machine tools need to be smoothed at the transition corners, because the velocity discontinuities at corners can result in fluctuations on machine tool motions and lead to poor surface quality. However, no research has been reported on local corner smoothing algorithm for four-axis CNC machine tools with two rotary axes by considering their special kinematic characteristics. To this end, this paper proposes an analytical C3 continuous local corner smoothing algorithm for four-axis CNC machines with two rotary axes. After coordinates transformation, the tool tip positions and tool orientations are smoothed by locally inserting specially designed three-dimensional (3D) quintic B-splines and one-dimensional (1D) quintic B-splines into the corners between linear motion segments, respectively. The smoothing algorithm guarantees C3 continuity of the tool tip position and C3 continuous synchronization of the tool orientation related to the tool tip position, through analytically evaluating control points of the inserted microsplines. The maximum error tolerances of the tool tip position and tool orientation are mathematically constrained. Experiments on an in-house developed four-axis machine verify the efficacy of the proposed algorithm, where maximal errors caused by the local corner smoothing algorithm are constrained, the synchronization of the tool orientation and the tool tip position are achieved, and the proposed C3 continuous corner smoothing algorithm has lower jerk and jounce but higher tracking and contour accuracy than C2 continuous algorithm.

While the heights and numbers of tires in the assembly line are changing, the traditional methods are difficult to identify the types of the tires, so an indirect tire identification method is proposed to identify the types of the tires, which uses the widths of the tires, the diameters and the shapes of the hubs to classify the tires. First, the tires are identified according to the widths and diameters by using the fuzzy C-means clustering algorithm. Second, the shapes of the hubs are used to distinguish the tires with similar dimensions. Finally, a two-layered fuzzy scheme is designed to identify the tires. Experimental results show that the two-layered fuzzy scheme is more effective than the fuzzy C-means clustering algorithm. And the proposed indirect tire identification method can achieve an accuracy of above 99.9% in the assembly line of tires.

A two-layered modeling and compensation scheme is proposed to reduce the contouring error of a three-dimensional motion control system. In the proposed scheme, the contouring error model of the three-dimensional motion control system is divided into two layers: the top layer and the bottom layer. The proposed multi-layered structure of the contouring error model presents more flexibility in the control system design because the cross coupling controllers in different layers can be designed separately. In this paper, a nonlinear PI controller and a position error compensator are designed in the bottom layer in order to achieve high contouring accuracy in the XY plane, while a unilateral compensator is designed in the top layer to further reduce contouring error in the three dimensional space. Finally, experiments are performed to verify the performance of the proposed two-layered modeling and compensation scheme. Experiment results show that the designed two-layered cross coupling controller can obtain higher contouring accuracy than traditional cross coupling controller both in the XY plane and in the XYZ space.

Although four-axis machines are widely used in welding, carving, and cutting revolving parts, much fewer four-axis tool path generation and contour error estimation researches have been studied when compared with five-axis ones. This paper proposes an off-line tool path generation and an on-line contour error estimation method for four-axis serial machines that are used for welding spatial intersecting curves on revolving parts. First, the kinematics module is derived, followed by proposing the tool path generation algorithm. The tool tip positions are represented by using a third order B-spline, while the tool orientations are represented by a third order polynomial-spline. Both splines, which form the C 2 continuous tool path, are fitted to the curve length parameter of the tool tip positions. When compared with existing multi-axis trajectory generation methods, the proposed method is greatly simplified by mapping the tool pose commands from the Cartesian coordinate frame to the cylindrical coordinate frame. In the proposed contour error estimation method, the tool tip position contour error is estimated at first, followed by calculating the relative tool orientation contour error which is synchronized with the tool tip position contour error to one same pose on the desired trajectory. The proposed tool path generation and contour error estimation methods are experimentally verified on a four-axis welding machine controlled by an in-house developed CNC system. Experiment results show that the desired trajectory can be tracked continuously and steadily. The contour error can be estimated with high accuracy and reduced by 50% after performing on-line compensation.

A layered modeling method is proposed to resolve the problems resulting from the complexity of the error model of a multi-axis motion control system. In this model, a low level layer can be used as a virtual axis by the high level layer. The first advantage of this model is that the complex error model of a four-axis motion control system can be divided into several simple layers and each layer has different coupling strength to match the real control system. The second advantage lies in the fact that the controller in each layer can be designed specifically for a certain purpose. In this research, a three-layered cross coupling scheme in a four-axis motion control system is proposed to compensate the contouring error of the motion control system. Simulation results show that the maximum contouring error is reduced from 0.208 mm to 0.022 mm and the integration of absolute error is reduced from 0.108 mm to 0.015 mm, which are respectively better than 0.027 mm and 0.037 mm by the traditional method. And in the bottom layer the proposed method also has remarkable ability to achieve high contouring accuracy.

Calibration plays an important part in the structured light system. It used to be regarded as time-consuming, expensive and hard to implement. In this paper, we introduce a novel and fast method to calibrate the structured light system by using the camera to control the projector to “capture” images. Firstly, we projected just six trapezoidal grayscale pattern to establish the corresponding pixel between the camera and the projector, then we converted the camera image to its corresponding projector image. Thus the structured light system can be easy controlled by the camera calibration. Experiments showed that the present calibration method is fast, easy and accurate.

Polar coordinate system is more effective for rotational axes than Cartesian coordinate one. But most commercial motion control cards do not support the polar coordinate, so this paper presents a program module based on polar coordinate system, which can be integrated into computer numeric control (CNC) controller based on motion control cards. To access the module, a special G code is developed. The module is implemented on a custom-made CNC controller and used to machine a class of watch parts. The experimental results show that the module is effective and easy to use.

A nanofluidic biosensor based on nanoreplica molding photonic crystal (PC) was proposed. UV epoxy PC was fabricated by nanoreplica molding on a master PC wafer. The nanochannels were sealed between the gratings on the PC surface and a taped layer. The resonance wavelength of PC-based nanofluidic biosensor was used for testing the sealing effect. According to the peak wavelength value of the sensor, an initial label-free experiment was realized with R6g as the analyte. When the PC-based biosensor was illuminated by a monochromatic light source with a specific angle, the resonance wavelength of the sensor will match with the light source and amplified the electromagnetic field. The amplified electromagnetic field was used to enhance the fluorescence excitation result. The enhancement effect was used for enhancing fluorescence excitation and emission when matched with the resonance condition. Alexa Fluor 635 was used as the target dye excited by 637-nm laser source on a configured photonic crystal enhanced fluorescence (PCEF) setup, and an initial PCEF enhancement factor was obtained. Electronic supplementary material The online version of this article (doi:10.1186/s11671-016-1644-x) contains supplementary material, which is available to authorized users.