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This paper aims to assess the possibilities of using current and incoming fifth generation (5G) devices as millimeter wave (mmWave) imagers. For this purpose, previous works about freehand scanning with compact devices working at mmWave frequencies are herein extended. In particular, a new tracking unit is now attached to the scanning device so the main parts of the freehand imager, namely the radiofrequency (RF) and tracking subsystems, become portable and not depend on external systems. Specifically, this work illustrates the possibilities of 5G devices working at the mmWave band as imagers. Results supporting that the embedded tracking unit provides enough accuracy are described and compared with an accurate reference system. The impact of the final image is also considered revealing that the shape of imaged objects can be easily identified.

In this paper, an anti-disturbance output feedback dynamic surface control (DSC) method is proposed for the position tracking of interior permanent magnet synchronous motor subject to unknown nonlinearities and time-varying disturbances. Specifically, a nonlinear extended-state-observer (NLESO) based on exponential functions is designed to estimate the total disturbance composed of system uncertainties and external disturbances. Then, by compensating for the total disturbance via the NLESO, an anti-disturbance output feedback law is designed based on the DSC approach. The salient features of the proposed approach is twofold. First, the total uncertainty including internal and external disturbances can be accurately estimated by an NLESO in real time. Second, the desired anti-disturbance performance of the servo control system can be achieved regardless of the position measurement only. The stability of the closed-loop control system is proved by using the cascade theory and input-to-state stability theory. Both simulation and experiment results are conducted to illustrate the effectiveness of the proposed control method.

It is well known that the position tracking control problem of permanent magnet synchronous motor (PMSM) is a challenging task when parameter uncertainties and time-varying load torque disturbances are taken into account. In this paper, a two-step controller design strategy composed of triple-loop control and internal model control is proposed to achieve a wide range of position tracking control of PMSM, where the reference position can be a relatively large value. In contrast, only local position tracking control problem has been solved by an internal model approach from output regulation theory in the recent work. In addition to the simulation results, the first experimental study is conducted to demonstrate the effectiveness of the proposed two-step control method. It is worth mentioning that our design can guarantee precise position tracking with a wide position range despite parameter uncertainties and time-varying load torque disturbances. [ABSTRACT FROM AUTHOR]

High energy efficiency and tracking accuracy are both vital for hydraulic lifting servo systems. However, the appropriate hardware configuration and its corresponding nonlinear controller is always a problem to be solved. To address this multi-objective task, an integrated energy-saving and position tracking controller is developed. Specifically, to reduce the substantial energy dissipation, a system configuration referring to the structure of the three-position-six-way valve is proposed. To ensure accurate tracking performance, a hybrid observer-based output feedback controller is developed. By doing so, the function of flow regeneration and the property of flow matching are achieved, and the tracking accuracy is guaranteed by using only position signal. To validate the effectiveness of the proposed method, a common Lyapunov function is used to prove the stability of the multi-model system, and case studies are conducted to demonstrate the system performance. • The multi-objective task is achieved. • System efficiency is improved by using the proposed scheme. • Tracking accuracy is guaranteed by the proposed controller. • Stability of the system is proved by common Lyapunov theory. • Estimates of states and unmatched uncertainties are obtained. [ABSTRACT FROM AUTHOR]

Autonomous take-off and landing on a moving landing pad are extraordinarily complex and challenging functionalities of modern UAVs, especially if they must be performed in windy environments. The article presents research focused on achieving such functionalities for two kinds of UAVs, i.e., a tethered multicopter and VTOL. Both vehicles are supported by a landing pad navigation station, which communicates with their ROS-based onboard computer. The computer integrates navigational data from the UAV and the landing pad navigational station through the utilization of an extended Kalman filter, which is a typical approach in such applications. The novelty of the presented system is extending navigational data with data from the ultra wide band (UWB) system, and this makes it possible to achieve a landing accuracy of about 1 m. In the research, landing tests were carried out in real conditions on a lake for both UAVs. In the tests, a special mobile landing pad was built and based on a barge. The results show that the expected accuracy of 1 m is indeed achieved, and both UAVs are ready to be tested in real conditions on a ferry.

Steel structures that benefit from having lightweight, ductility, and seismic behaviors are capable of improving the overall performance of civil engineering in environmental protection, project quality, process management, and ease of construction, making the procedure more feasible for builders. The application of steel structure techniques has been widely used in bridges, tall buildings, and complex projects around the world. Increasing demand for planning and design has led to structural projects upgrading in structural complexity and geometrical irregularity. However, steel structure projects are still limited by the principal disadvantage of susceptibility to deformation. Therefore, the challenges of the assembly and manufacturing process for steel structures are important. In this paper, to achieve full-loop tracking and control of the assembly and manufacturing process, we propose an integrated approach to undertake the aforementioned challenges via digital twin technology, which combines three modules: (1) deformation detection, (2) pose estimation and optimization, and (3) deformation correction and pose control. This proposed methodology innovatively merges gravitational deformation analysis with geometrical error analysis. Furthermore, the validity of this method’s implementation is demonstrated by the New Shougang Bridge project. The results show that the assembly precision satisfies the standard of less than H/4000, nearing H/6000. Moreover, the elevation difference is less than 20 mm, which satisfies the control precision of the geometric pose. The new method that we propose in this paper provides new ideas for structural deformation control and high-precision assembly, as it realizes dynamic deformation sensing, real-time deviation analysis and manufacturing, and efficient optimization of the assembly process.

Torque tracking is an important control target of a dry clutch. At present, the torque tracking control method of a dry clutch generally uses the relationship between the clutch torque and release bearing position obtained via experiment to convert the torque tracking control of the clutch into the position tracking control of the release bearing. However, due to the nonlinearity and time-varying parameters of the dry clutch, it is difficult to obtain an accurate and fixed relationship between torque and position. At the same time, there are also the nonlinearity and interference problems in the position tracking control process. In order to solve the above problems, this paper takes the torque tracking control process of the dry clutch in a three-speed automatic mechanical transmission of an electric vehicle as an example and proposes a double-loop control controller including torque loop and position loop. Firstly, the drive system dynamic model of electric vehicles and clutch actuator dynamic models is established. Secondly, the torque loop controller is established with the adaptive feedforward-feedback control method. The time-varying parameters are adaptively adjusted with adaptive feedforward control to solve the problem of the time-varying relationship between torque and position. In addition, the feedback control loop is added to improve the robustness of the controller. Thirdly, the position loop controller is established with the backstepping-based active disturbance rejection control method to solve the nonlinear and disturbance problems of the position tracking control. In the end, the torque loop and position loop are cascaded to form a double-loop controller, and the torque tracking control simulations of the dry clutch are carried out. The simulation results show that the double-loop controller has good control performance, and the effectiveness of the controller has been preliminarily verified.

Bilateral controller design for the teleoperation system is studied in this paper based on a motion prediction approach. To compensate the known long time-varying delays, novel predictors are presented to reconstruct the positions and velocities of robots on both sides through using the delayed measurements. The proposed predictors consist of several sub-predictors in a cascade structure, each of which is to predict the states of the previous one. The estimations of the actual states can be obtained from the last sub-predictor. New prediction horizons of each sub-observers are designed to cope with the time-varying fractions of the time delay. Then through applying the predicted results, bilateral predictive controller is designed for the teleoperation. The errors of both position tracking and prediction can converge into the bounded regions under several sufficient conditions of the control gains, which are obtained by using the Lyapunov–Krasovskii approach. The effective capacity of the presented method can be verified through comparative simulations. • Bilateral motion prediction for teleoperation with large time-varying delays. • Cascade predictor with variable prediction horizons. • Predictive position tracking and torque feedback controller for teleoperation. [ABSTRACT FROM AUTHOR]

The performances of position synchronization and force interaction of the teleoperation system provide a safe and efficient way for operators to perform tasks in remote, hazardous environments. In practice, however, communication delays and dynamic uncertainties can impair the performance of position synchronization controls. Under the above factors, it is necessary to study and design appropriate bilateral control methods to achieve stable and effective position synchronization control. In this paper, a new adaptive control architecture based on velocity feedback filter and radial basis function neural network is proposed. In the proposed control scheme, only the position signal is transmitted during the communication process, and the speed feedback filter and compensation method are designed and adopted to avoid the use of acceleration signals. In addition, a new auxiliary variable with a tracking error integral term is used to reduce the steady-state error of position tracking under nonzero external environmental forces. Using the Lyapunov–Krasovskii method, the stability of closed-loop remote operating systems is demonstrated. In the simulation and experiment sections, the algorithm was verified separately and compared with other algorithms. The results of a master–slave robot system verify the tracking performance of our proposed control scheme.

This article proposes a robust nonlinear position control for permanent magnet stepper motors. We develop a new single-input single-output model that consists of position, velocity, and acceleration using a commutation scheme to lump a system function and an external disturbance into a disturbance. An augmented observer is designed to estimate the position, velocity, acceleration, and disturbance. Because the disturbance refers to external disturbance, acceleration dynamics, and parameter uncertainties, it is difficult to accurately estimate disturbance without the high observer gain. It may result in the degradation of the position tracking performance. The nonlinear controller is then developed using backstepping to suppress the position tracking error using the input-to-state stability property. The key innovation of the proposed method is the design of the nonlinear gain to suppress the position tracking error according to the disturbance estimation error. Thus, the use of the high observer gain to accurately estimate the disturbance can be avoided. The proposed control algorithm was experimentally verified using the PM stepper motor control system and can be easily implemented in real-time using position measurements only. [ABSTRACT FROM AUTHOR]

This paper addresses the periodic position tracking and load force disturbance rejection in linear permanent magnet synchronous motors (LPMSM). Periodic position tracking is a challenge for LPMSMs, as there are electromagnetic forces that are not uniform along the actuator stroke due to end effects, which can lead to position variations. The proposed control structure combines a proportional–integral (PI) controller in the direct-axis control loop and a modified PI plus a multiple resonant controller (PI-RES) in the quadrature-axis control loop to ensure periodic reference tracking and disturbance rejection. The controller design is carried out by solving a convex optimization problem under linear matrix inequality (LMI) constraints, which guarantee closed-loop stability and transient performance. Simulations and experimental results are performed using a dual quasi-Halbach permanent magnet array linear tubular actuator with a coreless moving armature. The effectiveness of the proposed method is evaluated by applying position reference signals with different frequencies and harmonic compositions in conjunction with two types of load force disturbances. Experiments show the proposed controller results in precise reference tracking with negligible steady-state error. [ABSTRACT FROM AUTHOR]

This study examines the user position tracking system using marker-based AR on smartphones camera. The tracking system uses a homographic algorithm integrated into the Galeri Museum VR application. In the test, the user performed exploration interactions by 6 degrees of freedom in ten different positions in the museum gallery. The physical space used in this study was 4 x 4 m2 and a marker attached to the wall in front of the user. This system results in errors in XYZ field (0.102 m, 0.047 m, 0.044 m). If the camera's orientation is not directing to the marker and the user is moving, jitter appears because of the untracked marker. The use of marker-based AR successfully applied to track the position of users who perform natural locomotion interactions in the VR environment.

A completely new area of HoloLens usage is proposed. The Hololens is an augmented reality device, which provides the high precision location information. Such an information is normally used to accurately position holograms within the real space with respect to the viewer (user of HoloLens). The information is precise enough to use it for reporting the position for the purpose of autonomous driving. Several experiments have been executed in vast areas (20 m x 40 m) in order to find out the potential error coming from vibrations or other effects when moving the HoloLens. The results show that the technology can be used for spaces, which are previously known by the system - pre-scan of the space is needed. The big advantage of the system is its readiness for indoor positioning applications with no additional infrastructure needed, simultaneous localization and mapping, complex space mapping and reached precision. The disadvantage is mainly the costs.

Pneumatic muscle actuators (PMAs) have been attracting attention in recent years due to characteristics of natural compliance, high power output, lightweight, and low cost. Various apparatus and robots are developed by adopting PMAs and kinds of advanced controlling strategies are proposed to improve achieving accuracy. However, many of the proposed models and strategies are very complex and not suitable for the actual application. In this paper, we devise a single PMA driven setup and build up empirical quartic polynomial models of the apparatus by fitting sampled pressure-displacement data. The novel models are compact and easily computable. An improved PID algorithm by employing the phenomenological models as feed-forward is devised to improve the dynamical response of the setup. The experiments are performed to assess the proposed controller in improving the position accuracy of the apparatus.

In order to realize precise position tracking of a novel circular hydraulic actuator with parameter uncertainties and bounded disturbances, an adaptive sliding mode controller (ASMC) that incorporates a fuzzy tuning technique is proposed in this paper. The mechanical structure and basic principle of the actuator are first introduced, and the mathematical model of its corresponding valve-controlled hydraulic servo system is constructed. Based on Lyapunov stability theory, online parameter estimation and sliding mode controller design are effectively integrated to approximate the equivalent control of sliding mode. To mitigate the undesired chattering phenomenon and further improve system performance, a fuzzy tuning scheme is employed to regulate the proportional gain of the approaching control term. In addition, a real-time control platform is established, and the controllers parameter identification and position tracking are verified by preliminary experiments. Finally, the traditional PID controller and the exponent approaching sliding controller are also conduced to further evaluate the control performances of the designed controller, and the comparative results demonstrate that the proposed control scheme has better control performance in reducing errors for trajectory tracking.

In this paper, a new vision-based adaptive control algorithm is proposed for the positioning of a quadrotor aerial robot (QAR) with an onboard pin-hole camera. First, the transformation between the position tracking error and image projection error is constructed through the spherical projection method, and then the regulation of the position error is achieved indirectly by stabilizing the image projection error. To overcome the challenge that the dynamics of QAR is physically underactuated, a backstepping-based approach that synthesizes the Lipschitz condition and natural saturation of the inverse tangent function is proposed. In the proposed adaptive controller, an optimized adaptive neural network (NN) means is designed, where only the square of the NN weight matrix's maximum singular value, not the weight matrix itself, is estimated. Moreover, to facilitate practical application, a novel inertial matrix estimator is introduced in the tuning laws, so that the accurate QAR rotation inertial information is not required. By Lyapunov theory, it is proved that the image projection error converges to an adjustable region of zero asymptotically. The effectiveness of the proposed algorithm has been confirmed by the experimental results.

Performance of teleoperation can be greatly influenced by time delay in the process of tele-manipulation with respect to accuracy and transparency. Wave variable is an effective algorithm to achieve a good stable capability. However, some traditional wave variable methods may decrease the performance of transparency and suffer the impacts of wave reflection. To deal with the problem of stability and transparency in teleoperation, in this paper, a novel wave variable method with four channel is presented to achieve stable tracking in position and force. In addition, the proposed method can achieve the distortion compensation and reduce the impacts of wave reflection. The simulation experimental results verified the tracking performance of the proposed method.

In this paper, a novel finite-time command filtered backstepping control algorithm is proposed to address the problems of high order nonlinearity, noise and friction interference when tracking the pitch angles of wind turbine hydraulic pitch systems. Since taking derivative is not required, the system noise cannot be amplified in the algorithm design process. The finite-time command filter is first employed to filter the state variables of the hydraulic pitch systems to eliminate the interference caused by the noise and friction. Moreover, the filter is combined with backstepping design to approximate the derivatives of virtual control variables to avoid “Differential expansion” phenomenon. In addition, in order to ensure the accuracy of the filtered signals to approximate the virtual control variables, a finite-time error compensation mechanism is designed. Simulation results show the effectiveness and high-precision tracking performance of the proposed algorithm in this paper.

Wireless Local Area Network (WLAN) positioning is a challenging task indoors due to environmental constraints and the unpredictable behavior of signal propagation, even at a fixed location. The aim of this work is to develop deep learning-based approaches for indoor localization and tracking by utilizing Received Signal Strength (RSS). The study proposes Multi-Layer Perceptron (MLP), One and Two Dimensional Convolutional Neural Networks (1D CNN and 2D CNN), and Long Short Term Memory (LSTM) deep networks architectures for WLAN indoor positioning based on the data obtained by actual RSS measurements from an existing WLAN infrastructure in a mobile user scenario. The results, using different types of deep architectures including MLP, CNNs, and LSTMs with existing WLAN algorithms, are presented. The Root Mean Square Error (RMSE) is used as the assessment criterion. The proposed LSTM Model 2 achieved a dynamic positioning RMSE error of 1.73m, which outperforms probabilistic WLAN algorithms such as Memoryless Positioning (RMSE: 10.35m) and Nonparametric Information (NI) filter with variable acceleration (RMSE: 5.2m) under the same experiment environment.

In this work, a two-dimensional (2D) position-detection device using a single axis magnetic sensor combined with orthogonal gradient coils was designed and fabricated. The sensors used were an induction coil and a GMR spin-valve sensor GF807 from Sensitec Inc. The field profiles generated by the two orthogonal gradient coils were analyzed numerically to achieve the maximum linear range, which corresponded to the detection area of the tracking system. The two coils were driven by 1-kHz sine wave currents with a 90° phase difference to generate the fields with uniform gradients along the x- and y-axis in the plane of the tracking stage. The gradient fields were detected by a single-axis sensor incorporated with a digital dual-phase lock-in detector to retrieve the position information. A linearity correction algorithm was used to improve the location accuracy and to extend the linear range for position sensing. The mean positioning error was found to be 0.417 mm, corresponding to the relative error of 0.21% in the working range of 200 mm × 200 mm, indicating that the proposed tracking system is promising for applications requiring accurate control of the two-dimensional position.

Precise position tracking plays a key role in formation flights of UAVs (unmanned aerial vehicles) or other applications based on the idea of the leader–following scheme. It decides on the integrity of a formation or increasing the position error when a UAV follows the desired flight path. This is especially difficult in the case of nonholonomic vehicles having limited possibilities of making turns, causing a lack of stability. An asymmetrical artificial potential field (AAPF) is the way to achieve the stability of position tracking by nonholonomic UAVs, but it is only a nonlinear proportional relation to feedback given by a tracking error. Therefore, there can still be a steady-state error or error overshoots. Combining an AAPF with integral and derivative terms can improve the response of control by damping overshoots and minimizing the steady-state error. Such a combination results in a regulator whose properties allow defining it as nonlinear PID. Numerical simulation confirms that integral and derivative terms together with an AAPF create a control loop that can minimize overshoots of the tracking error and the steady-state error and satisfy conditions of asymptotical stability.

This article addresses the adaptive-based robust output feedback tracking control for robot manipulators with friction and alternating unknown loads. A switched nonlinear system is first established to model the friction and parameter variations, caused by the load change. Under arbitrary load changings, an adaptive H ∞ tracking control strategy is proposed to ensure link position tracking, in the presence of uncertainties and external disturbances. Then, for bounded external disturbances, a novel robust adaptive output tracking control strategy is developed, which guarantees all the closed-loop signals are bounded and tracking error is driven to zero. Unlike some previous studies, the proposed algorithms do not require velocity measurements, and the unknown switched parameters and disturbances are neither required to be periodic nor to have known bounds. A simulation study is also given to demonstrate the analytically proved properties of the proposed schemes. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Hebei University of Science & Technology is the property of Hebei University of Science & Technology, Journal of Hebei University of Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

To achieve a manipulator that is lighter and more anthropomorphic, a 7-DOF robotic manipulator driven by the tendon-sheath is designed. Its mechanical system and control system are both introduced in this paper. An encoder is installed on both the driver side and the joint side to realize double closed-loop control. Considering the transmission characteristics of the reducer and the tendon-sheath, a position transmission model of a single joint is constructed. Furthermore, the correctness of the transmission model is verified based on the prototype joint four. A proportional-integral-differential (PID) controller and fuzzy PID controller with time-delay estimation (TDE) are designed based on double encoders, and some experiments on the position tracking control are carried out for the robotic joints. The experimental results show that each joint can rotate normally and there is no interference between the different tendon-sheaths. When the drive motor moves to follow the position command of the sinusoidal signal, the TDE-based fuzzy PID controller can reduce the maximum tracking error compared with the traditional PID controller. According to the experimental results, it is feasible to apply the tendon-sheath transmission to the manipulator, which provides a reference for the development of other equipment based on the tendon-sheath. [ABSTRACT FROM AUTHOR]

High-speed electrical machines have been of great research interest because of their excellent efficiency and high storage capacity. In the case of switched reluctance machines (SRMs), position feedback is required for effective operation. The installation of this sensor in a high-speed flywheel is difficult and expensive. This paper proposes and analyses a methodology to estimate the position of a SRM and remove the position encoder to apply the machine as a flywheel at 50,000 rpm. The machine is modeled with non-linear characteristics, and is simulated under single-pulse operation due to the high-speed. Two configurations of the sensorless method are presented: Robust Method and Sequential Method. The robust configuration identifies the firing angles position only, while the sequential setup can track any position. Both configurations present advantages and disadvantages in relation to the error of estimation and to the number of estimations. The methods are tested in closed-loop speed control. In the two cases, the position estimation supports satisfactory results for simulating operation of the machine at high speed.

An adaptive dynamic surface controller (ADSC), which comprises an online parameter estimator and a robust control law, is developed for the pneumatic servo systems driven by the proportional directional control valves. Departing from the use of time-consuming offline fitting of the orifice area to accommodate the effect of valve dead zone, this paper employs the least-square-type indirect parameter estimation algorithm with online condition monitoring to estimate the dead-zone parameters and some other important model parameters. These accurate estimates of model parameters are utilized in the development of a precise position tracking controller for the single-rod pneumatic actuator. By using the dynamic surface control technique to synthesize the robust control law, the problem of “explosion of complexity” in traditional backstepping design method is avoided. The stability of the closed-loop system is proved by the means of the Lyapunov theory. The obtained extensive comparative experimental results verify the effectiveness of the proposed valve dead-zone compensation strategy and the high-performance nature of the ADSC in practical implementation.

In this article, we consider a family of in-mouth passive radio-frequency (RF) sensors for nutrients whose data is acquired externally using a miniaturized vector network analyzer (VNA). However, the data readings suffer from noise as the VNA’s position shifts during reading and also in-between readings. We propose an ML method to track the movement of these sensors using RF signals. Although classical studies in RF sensors have shown that the s-parameter of the sensor is related to the position of the sensor, they have always tried to find the relation between the resonance frequency and its loss to the position of the sensor. In contrast, our analysis revealed that based on theoretical perspectives, using just resonance frequency and its loss makes it impossible to find the correct position of the sensor with reasonable accuracy. To improve accuracy, we propose to use the loss information of RF sensors not only at one resonance frequency but across a wide spectrum. We introduced a pretrained neural network model consisting of a combination of DNN and convolutional neural network layers for extracting the sensor position. In order to accurately track the movement of the sensor with respect to the VNA, we propose a neural network-based RF sensor tracking (NEWERTRACK) model, which has utilized two unidirectional long short term memory layers. The results show that our proposed model achieves an average tracking error of 1.84 mm. Also, NEWERTRACK is capable of improving the position tracking accuracy by about $10\times $ compared to traditional s-parameter analysis methods and outperforms the best model in other RF methods by two times. [ABSTRACT FROM AUTHOR]

In this paper, the issue of position tracking control of servo system with external disturbance is studied. A novel fractional-order sliding mode control (FOSMC) strategy is proposed. To be specific, firstly, the motor parameter drift, additional unknown disturbance and the uncertainty of load torque are considered as lumped disturbance, and a nonlinear disturbance observer (NDO) is designed to estimate the disturbance. Secondly, fractional-order terminal sliding mode surfaces (FOTSMS) are designed for the current loop and the position–velocity loop, respectively, as well as the FOSMC is presented based on NDO, in which FOSMC of position–velocity loop introduces second-order super-twisting term to reduce the chattering of the system. Furthermore, the stability of the FOSMC is analyzed. Finally, the effectiveness of the proposed algorithm is verified by simulations and experiments. • A novel fractional-order sliding mode control (FOSMC) strategy is proposed. • A nonlinear disturbance observer (NDO) is designed to estimate the disturbance. • A fractional-order terminal sliding mode surfaces (FOTSMS) are designed for the current loop and the position–velocity​ loop. [ABSTRACT FROM AUTHOR]

Purpose: C-arms are portable X-ray devices used to generate radiographic images in orthopedic surgical procedures. Evidence suggests that scouting images, which are used to aid in C-arm positioning, result in increased operation time and excess radiation exposure. C-arms are also primarily used qualitatively to view images, with limited quantitative functionality. Various techniques have been proposed to improve positioning, reduce radiation exposure, and provide quantitative measuring tools, all of which require accurate C-arm position tracking. While external stereo camera systems can be used for this purpose, they are typically considered too obtrusive. This paper therefore presents the development and verification of a low-profile, real-time C-arm base-tracking system using computer vision techniques. Methods: The proposed tracking system, called OPTIX (On-board Position Tracking for Intraoperative X-rays), uses a single downward-facing camera mounted to the base of a C-arm. Relative motion tracking and absolute position recovery algorithms were implemented to track motion using the visual texture in operating room floors. The accuracy of the system was evaluated in a simulated operating room mounted on a real C-arm. Results: The relative tracking algorithm measured relative translation position changes with errors of less than 0.75% of the total distance travelled, and orientation with errors below 5% of the cumulative rotation. With an error-correction step incorporated, OPTIX achieved C-arm repositioning with translation errors of less than 1.10 ± 0.07 mm and rotation errors of less than 0.17 ± 0. 02 ∘ . A display based on the OPTIX measurements enabled consistent C-arm repositioning within 5 mm of a previously stored reference position. Conclusion: The system achieved clinically relevant accuracies and could result in a reduced need for scout images when re-acquiring a previous position. We believe that, if implemented in an operating room, OPTIX has the potential to reduce both operating time and harmful radiation exposure to patients and surgical staff. [ABSTRACT FROM AUTHOR]

The main objective of this article is to address the position tracking control problem for permanent magnet linear motor by using a novel model-based robust control method. Specifically, based on the assumed upper bound of the lumped model uncertainties and external disturbances, we design a novel nonlinear control algorithm, which is characterized by error-based and model-based inheriting from traditional proportional-integral-derivative (PID) control and robust control. The proposed control can be considered as an improved PID control or a redesigned robust control, with simple implementation and practical effectiveness. Theoretical analysis is provided to demonstrate that the controller can guarantee the uniform boundedness and uniform ultimate boundedness of the system. Moreover, on the experimental platform, rapid controller prototyping cSPACE is designed to avoid long time programming and debugging, and provides great convenience for practical operation. Numerical simulations and real-time experimental results are finally presented to illustrate the effectiveness and the achievable control performance of the control design. [ABSTRACT FROM AUTHOR]

The drive system of a switched reluctance motor (SRM) is a nonlinear one with coupling between the rotor position, inductance, and ux linkage. Moreover, the system parameters change with the external environment such as temperature, humidity, and pressure. At the same time, uncertain factors including friction, torque uctuation, and external interference in the system, reduce system stability and reliability. To effectively improve the inuence of uncertain factors on the performance of an SRM system, this study proposes an auxiliary sliding position tracking method, under the condition of limited control input. First, the mathematical model of the system was established according to the structure and characteristics of an SRM. Second, an auxiliary sliding mode position tracking controller was designed by constructing the auxiliary system and utilizing the sliding mode control theory. Finally, the effectiveness and superiority of the proposed method were verified through comparison with proportional integral differential (PID) control and the traditional sliding mode control using simulation. Results demonstrate that under limited control input, the auxiliary sliding position tracking control method still delivers rapid and error-free tracking of the position and speed for the change of model parameters. The recommended scheme has a response time 2.9 times shorter than that of PID control. Furthermore, the steady-state errors of the PID control position and speed are 0.66 rad and 1.62 rad/s, respectively. The control input of the traditional sliding mode control has greater chattering than the proposed method. When the system has interference, the designed method under the condition of limited control input can achieve the desired tracking command within 1.7 s. The steady-state error is 0.0044 rad, and the steady-state accuracy of the developed scheme is 10.3 times higher than that of PID control. Therefore, the proposed method enjoys both high position tracking accuracy and strong robustness to external disturbances. [ABSTRACT FROM AUTHOR]

Position tracking has been widely used in medical applications, especially in 3D ultrasound imaging, where it has transformed the 2D slice limitation into 3D volume with bigger clinical impacts. As a game controller can also produce position tracking information, it has the potential to act as a low-cost and portable position tracker for ultrasound probes. This paper aims to investigate the feasibility of a game controller to perform as a position tracker and to design its implementation in 3D ultrasound imaging. The study consists of data acquisition and 3D ultrasound reconstruction for visualization. The data acquisition is accomplished by capturing the 2D ultrasound frame and its relative positional and orientation data by using an ultrasound probe and game controller respectively. These data are further reconstructed to produce 3D ultrasound volume for visualization. Our experiments include game controller position tracker testing and 3D ultrasound reconstruction on baby phantom. The results have confirmed that the game controller performance was closely aligned with that of in a robot arm. Also, the 3D ultrasound reconstruction implementation has revealed promising outcomes. With these features, the function of the currently available ultrasound probes can be prospectively improved using a game controller position tracker effectively. Graphical Abstract. [ABSTRACT FROM AUTHOR]

This paper presents three strategies that adjust the coordination damping and stiffness of four-channel teleoperators to maintain the teleoperation stable regardless of time-varying delays in the transmission of operator and environment forces between the master and slave robots. A first strategy employs hybrid control terms that depend on position errors and local velocities. Thus, the hybrid terms simultaneously and dynamically regulate the master–slave coupling and the local damping injections. They increase the robustness of the system to perturbations caused by delayed transmission of operator and environment forces, but are singular at zero velocities. A second strategy injects additional damping around zero velocities, according to the master–slave position error. The additional damping makes the hybrid term nonsingular and eliminates chattering at zero velocities. However, it cannot synchronize the master and slave robots in the presence of large position error. This problem is addressed by a third strategy, which reduces the order of the position error in the hybrid term to guarantee the dominance of the Proportional term in coordination. Then, the two robots can be synchronized from arbitrarily large position errors. Lyapunov stability analysis and hardware-in-the-loop experimental results verify and compare these three proposed hybrid approaches. [ABSTRACT FROM AUTHOR]

Copyright of Electric Machines & Control / Dianji Yu Kongzhi Xuebao is the property of Electric Machines & Control and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Much recently, an internal model approach from output regulation theory has been adopted to solve the speed tracking control problem of the permanent magnet synchronous motor (PMSM) system on simulation level. A striking advantage of this approach is that it can achieve multiple goals including trajectory tracking, disturbance rejection, and robustness simultaneously. This article further studies a position tracking control problem of the PMSM system under nonlinear load torque disturbance. A nonlinear internal model based output feedback controller is proposed, which can achieve exact position tracking and allow certain parameter uncertainties. Besides simulation results, a real-time experimental setup is built and experimental results are provided to illustrate the effectiveness of the proposed controller. It is worth mentioning that the proposed controller can lead to a high precision position tracking performance under nonlinear load torque disturbance. [ABSTRACT FROM AUTHOR]

Much recently, a discrete-time neural network (NN) approach from the output regulation theory was adopted to solve the position tracking problem of the spherical inverted pendulum (SIP) system. The key of this approach is to find the approximate solution of the corresponding discrete regulator equations (DREs) of the SIP system, which are composed of 10 nonlinear algebraic functional equations. However, the procedure for calculating the approximate solution of the DREs is quite tedious and is dependent on the system parameters. In this paper, an improved discrete-time NN control algorithm is proposed, which relies on the NN approximation of the feedforward function. Since the feedforward function is two-dimensional, the improved NN approach is much simpler compared with the existing NN approach. Moreover, a distinct advantage of our approach is that it allows certain robustness to the system parameters when every state is available. Simulation results demonstrate that our approach leads to much smaller tracking errors than the existing NN approach. [ABSTRACT FROM AUTHOR]

To further improve the transient and steady-state performance of automotive electronic throttle position tracking, in this paper an adaptive prescribed performance servo control strategy is designed and applied to a real electronic throttle control system. In view of the possible high gain of the prescribed performance controller in practice, the actuator constraint is also considered in the controller design. The designed servo controller can ensure the transient and steady-state responses of tracking error are limited in the range prescribed by the performance function, and converge with the prescribed convergence rate and have no overshoot. The incorporated adaptive updating law can enhance the robustness of the transient and steady-state performance against uncertainty from the product tolerance, the operating conditions, and the aging of components. Both Matlab/Simulink simulation and dSPACE-based hardware-in-the-loop experimental verification show the effectiveness and applicability of the proposed control strategy. [ABSTRACT FROM AUTHOR]

The six-degree-of-freedom coupling control of the relative orbit and relative attitude of a chaser approaching an uncontrolled tumbling target is studied in this paper. The chaser must reach an aimed position in the body coordinate system of the uncontrolled tumbling target spacecraft, and at the same time the attitude of the chaser should be synchronized with the attitude of the target. First, the integrated model of relative position and attitude is established based on the T–H equations and the error quaternion. Then, considering the safety of the approaching process, the nominal trajectory of the chaser is designed. Finally, a robust adaptive relative position and relative attitude controller is designed. An adaptive tuning method is used to deal with external disturbances and system uncertainties, and the upper bounds need not be known in advance. Simulation results show that the proposed method can track the aimed position of the uncontrolled tumbling target and complete the attitude synchronization, and the controller is still effective even for the target tumbling at a high angular velocity. Compared with the existing researches, the duration to complete position tracking and attitude synchronization is greatly reduced, the required maximum force and torque are smaller, and the dynamic response performance of the system is improved. [ABSTRACT FROM AUTHOR]

Location positioning systems are available in applications such as mobile, robotic tracking systems and Wireless location-based service (LBS) applications. The GPS system is the most well-known location tracking system, but it is not easy to use indoors. The method of radio frequency identification (RFID) location tracking was studied in terms of cost-effectiveness for indoor location tracking systems. Most RFID systems use active RFID tags using expendable batteries, but in this paper, an inexpensive indoor location tracking system using passive RFID tags has been developed. A pattern matching method and a system for tracing location by generating regression curves were studied to use precision tracking algorithms. The system was tested by verifying the level of error caused by noise. The three-dimensional curves are produced by the regression equation estimated the statistically meaningful coordinates by the differential equation. The proposed system could also be applied to mobile robot systems, AGVs and mobile phone LBSs. [ABSTRACT FROM AUTHOR]

This paper proposes a robust tracking control method for swing-up and stabilization of a rotational inverted pendulum system by applying equivalent input disturbance (EID) rejection. The mathematical model of the system was developed by using a Lagrangian equation. Then, the EID, including external disturbances and parameter uncertainties, was defined; and the EID observer was designed to estimate EID using the state observer dynamics and a low-pass filter. For robustness, the linear-quadratic regulator method is used with EID rejection. The closed-loop stability is proven herein using the Lyapunov theory and input-to-state stability. The performance of the proposed method is validated and verified via experimental results.