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Bridge cranes used for vertical lifting and horizontal transportation of heavy objects are widely used in engineering. Based on the Hamilton principle, a dynamic model of a bridge crane system in planar space is established for the first time in this paper, and the movement of the main beam and trolley in planar space is considered at the same time. This paper introduces an adaptive fault-tolerant boundary control scheme, grounded in the Nussbaum function, to address the challenges posed by time-varying actuator faults and uncertain control directions. Ultimately, the control scheme can effectively suppress cable vibrations and achieve position tracking for both the main beam and the trolley, so as to provide a strong safety guarantee for the workers operating the bridge crane. The Lyapunov method is utilized to demonstrate the uniform ultimate boundedness of the closed-loop system. Furthermore, the effectiveness of the proposed control method is corroborated by simulation results. [ABSTRACT FROM AUTHOR]

Addressing input saturation, external disturbances, and uncertain system parameters, this paper investigates the position tracking control problem for bilateral teleoperation systems with a time delay communication channel. Based on a composite energy function, we propose an adaptive iterative learning control (AILC) method to achieve the objective of position tracking under the alignment condition. This extends the existing research on the control of nonlinear teleoperation systems with time delay. The saturation constraint property of the Softsign function ensures that no state of the system exceeds its constraints. The controller learns to simultaneously deal with the uncertainty of system parameters online, reject external disturbances, and eliminate positional errors along the time and iteration axes. All signals in the system for any constant time delay are proved to be bounded. Ultimately, the performance of the proposed controller is further verified through numerical simulations. [ABSTRACT FROM AUTHOR]

While marine animal behavior is often studied in constrained lab setups, a more reliable exploration should be done in their natural environment and without human interference. This task becomes excessively more challenging when quantitative data are needed in large and unconstrained aquatic environments. Toward that end, researchers widely use acoustic positioning telemetry to remotely track their subjects, though this often requires an extensive network of receivers placed in the environment ahead of time. This study proposes a new tracking method that continuously tracks and reports the trajectory of a target in unconstrained marine environments using a single‐moving acoustic receiver. Instead of deploying an extensive array of static receivers, we use a single receiver mounted on an autonomous surface vehicle to obtain highly accurate results with much cheaper and simpler means. The receiver position and earlier target location estimations are used to calculate an optimal trajectory for the receiver, which in turn provides subsequent readings and target localizations based on a new variant of the Time Difference of Arrival approach. We demonstrate the performance of the proposed methods using both simulations and field experiments. [ABSTRACT FROM AUTHOR]

Abstract Realizing precise and fast position control of the gear is a challenging issue because of its nonlinearity, parameter uncertainty and external disturbance. Therefore, this paper researches the clutch position control considering the influence because of the factor on the system performance. By virtue of the traditional adaptive control method, an improved strategy based on finite time theory is proposed to further improve the convergence rate as well as the position tracking precision. First, a model of electromechanical clutch actuator system is established by theoretical analysis. Then, an enhanced adaptive controller is designed using finite time idea by introducing power function in the virtual control. And parameter update rate is adopted in the control action. Next, the stability of the control system is proved theoretically. Finally, Matlab simulations and experimental bench test are carried out to exhibit the effectiveness of the presented method. The results show that the satisfactory performance has been achieved with accurate position tracking and fast convergence speed.

Copyright of China Mechanical Engineering is the property of Editorial Board of China Mechanical Engineering 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.)

Realizing precise and fast position control of the gear is a challenging issue because of its nonlinearity, parameter uncertainty and external disturbance. Therefore, this paper researches the clutch position control considering the influence because of the factor on the system performance. By virtue of the traditional adaptive control method, an improved strategy based on finite time theory is proposed to further improve the convergence rate as well as the position tracking precision. First, a model of electromechanical clutch actuator system is established by theoretical analysis. Then, an enhanced adaptive controller is designed using finite time idea by introducing power function in the virtual control. And parameter update rate is adopted in the control action. Next, the stability of the control system is proved theoretically. Finally, Matlab simulations and experimental bench test are carried out to exhibit the effectiveness of the presented method. The results show that the satisfactory performance has been achieved with accurate position tracking and fast convergence speed. [ABSTRACT FROM AUTHOR]

Radio tagging and tracking are fundamental to understanding the movements and habitats of wildlife in their natural environments. Today, the most widespread, widely applicable technology for gathering data relies on experienced scientists armed with handheld radio‐telemetry equipment to locate low‐power radio transmitters attached to wildlife from the ground. Although aerial robots can transform labor‐intensive conservation tasks, the realization of autonomous systems for tackling task complexities under real‐world conditions remains a challenge. We developed ConservationBots—small aerial robots for tracking multiple, dynamic, radio‐tagged wildlife. The aerial robot achieves robust localization performance and fast task completion times—significant for energy‐limited aerial systems while avoiding close encounters with potential, counterproductive disturbances to wildlife. Our approach overcomes the technical and practical problems posed by combining a lightweight sensor with new concepts: (i) planning to determine both trajectory and measurement actions guided by an information‐theoretic objective, which allows the robot to strategically select near‐instantaneous range‐only measurements to achieve faster localization, and time‐consuming sensor rotation actions to acquire bearing measurements and achieve robust tracking performance; (ii) a bearing detector more robust to noise; and (iii) a tracking algorithm formulation robust to missed and false detections experienced in real‐world conditions. We conducted extensive studies: simulations built upon complex signal propagation over high‐resolution elevation data on diverse geographical terrains; field testing; studies with wombats (Lasiorhinus latifrons; nocturnal, vulnerable species dwelling in underground warrens) and tracking comparisons with a highly experienced biologist to validate the effectiveness of our aerial robot and demonstrate the significant advantages over the manual method. [ABSTRACT FROM AUTHOR]

The classical ‘Geometric Control (GC)’ of the quadrotors is susceptible to the 180° turnover singularity, which could result in a crash. To overcome the problem, an ‘Improved Geometric Control (IGC)’ is developed based on a proposed attitude extraction method. The controller is cascaded with a position loop and an attitude loop. The two loops are bridged by the method. It geometrically determines the desired attitude from the desired thrust direction. Attitude tilt-prioritizing can also be achieved by scarifying the yaw control. Unlike the GC with almost global stability, the IGC is proved to be globally asymptotically stable. Simulation comparisons demonstrate excellent performance even when the quadrotor confronts large initial attitude and position errors. The singular problem is thoroughly avoided.

A position and force tracking control based on force estimation is proposed for bilateral teleoperation systems with time-varying delays. A time-delay state observer is employed to estimate the system state variables affected by the delays. To estimate the interaction forces effectively, a force estimation algorithm with adaptive law is designed. Based on the estimated states and forces, a P+D controller is designed to simultaneously guarantee the position and force tracking of the system. The stability and tracking performance of the closed-loop system are proved via Lyapunov functions, and the feasibility of the proposed control is verified by both simulations and experiments. The proposed control can improve the position and force tracking performance of bilateral teleoperation systems under time-varying delays. Meanwhile, it neither requires force measurement nor the bound of the derivative of the time-varying delays to be within one. [ABSTRACT FROM AUTHOR]

Addressing input saturation, external disturbances, and uncertain system parameters, this paper investigates the position tracking control problem for bilateral teleoperation systems with a time delay communication channel. Based on a composite energy function, we propose an adaptive iterative learning control (AILC) method to achieve the objective of position tracking under the alignment condition. This extends the existing research on the control of nonlinear teleoperation systems with time delay. The saturation constraint property of the Softsign function ensures that no state of the system exceeds its constraints. The controller learns to simultaneously deal with the uncertainty of system parameters online, reject external disturbances, and eliminate positional errors along the time and iteration axes. All signals in the system for any constant time delay are proved to be bounded. Ultimately, the performance of the proposed controller is further verified through numerical simulations.

DC motors are widely used in industries to provide mechanical power in speed and torque. The position and speed control of DC motors is receiving interest from the scientific community in robotics, especially in robotic arms, a flexible joint manipulator. The current research work is based on the position control of DC motors using experimental investigations in LabVIEW. The linear control strategy is applied to track the position and speed of the DC motor with comparative analysis in the LabVIEW platform and simulation analysis in MATLAB. The tracking error in the hardware setup based on LabVIEW programming is slightly greater than the simulation analysis in MATLAB due to the inertial load of the motor during steady-state conditions. The controller output shows the input voltage applied to the DC motor varies between 0 and 8 V to ensure minimal steady error while tracking the position and speed of the DC motor. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Chongqing University of Technology (Natural Science) is the property of Chongqing University of 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.)

Copyright of Machine Tool & Hydraulics is the property of Guangzhou Mechanical Engineering Research Institute (GMERI) 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.)

This paper presents the design and development of a control scheme, for a robot master–slave teleoperation system man–machine interface. The developed system consists of JUPITER XL SCARA robot as a slave manipulator with only the first two links activated, a wireless User Datagram Protocol (UDP) network, and PC as a master controller. The system model parameters identified using the Least-Squares method. A workspace-control system was developed to deals with the problem of position-tracking of bilateral teleoperated two degrees of freedom manipulator, and aid the human operator in driving and controlling the slave robot that performs critical and difficult tasks such as underwater works. A Proportional-Integral-Derivative (PID) and Fuzzy Logic Control (FLC) controllers with different input signals were applied to the system. It was proved experimentally and by simulation on Matlab that the FLC gave a better performance than the PID controller. The two parallel loop subroutine technique proved a great enhancement to the system performance as it decreased the total delay time in the system to almost 25 ms.

The purpose of this study was to investigate the reliability of spatio-temporal measurements applied within collective behaviour research in football. In silico experiments were conducted introducing positional errors (0.5, 2 and 4 m) representative of commercial tracking systems to match data from the 2020 European Championship qualifiers. Ratios of the natural variance ('signal') of spatio-temporal metrics obtained throughout sections of each game relative to the variance created by positional errors ('noise') were taken to calculate reliability. The effects of error magnitude and time of analysis (1, 5 and 15 mins; length of attack: <10, 10–20, >20 s) were assessed and compared using Cohen's f2 effect size. Error magnitude was found to exert greater influence on reliability (f2 = 0.15 to 0.81) compared with both standard time of analysis (f2 = 0.03 to 0.08) and length of attacks (f2 = 0.15 to 0.32). The results demonstrate that technologies generating positional errors of 0.5 m or less should be expected to produce spatio-temporal metrics with high reliability. However, technologies that generate errors of 2 m or greater may produce unreliable values, particularly when analyses are conducted over discrete events such as attacks, which although critical, are often short in duration. [ABSTRACT FROM AUTHOR]

Robotic exoskeletons with different actuators have been extensively investigated for decades, but designing a robot joint with compact structure, sufficient output torque, and satisfactory kinematic performance still remains a challenge. The paper introduces the mechanical design and control scheme of a novel joint with a circular rotary electro-hydraulic actuator in order to provide walking assistance for the hip joint. First, measurement and analysis techniques are applied in the gait recognition to determine an accurate swing range of the target joint and provide essential information for the structure design of the hydraulic rotary drive joint. Secondly, the functional structure and working principle of the hydraulic rotary joint are described in detail and the corresponding mathematical model is established for the valve-controlled hydraulic servo system. In addition, an adaptive sliding mode control (ASMC) method is proposed for position-tracking and improving the anti-disturbance ability of the controlled system. The global asymptotic stability and finite-time convergence of the closed-loop system are proved by Lyapunov stability theory. Finally, the feasibility and position-tracking performance of the designed ASMC controller were experimentally verified. Compared to the PID controller and the conventional sliding mode control scheme, the proposed controller improved the position-tracking control accuracy by 20%. [ABSTRACT FROM AUTHOR]

Copyright of Machine Tool & Hydraulics is the property of Guangzhou Mechanical Engineering Research Institute (GMERI) 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.)

This paper aims to study the fast finite-time (FFT) tracking control strategy for permanent magnet synchronous motor (PMSM). The design of FFT tracking controller for PMSM faces many difficulties due to the coupling between current and rotational speed, as well as the nonlinear characteristics of motor torque. To overcome the difficulty, we utilize a novel coordinate transformation to establish the mathematical models of PMSM in $\alpha -\beta $ coordinate system and $d-q $ coordinate system. Based on the obtained PMSM model, novel FFT tracking control strategy including FFT direct axis current tracking controller and FFT position tracking controller is developed. Superior to the existing control schemes of PMSM, the new FFT tracking control strategy ensures that the states error of the system can be quickly stabilized in a limited time with faster convergence speed and stronger anti-interference. Finally, the effectiveness of the proposed control method is illustrated by simulation results.

Flexible link manipulators (FLM) are widely preferred in applications that require faster operation, high maneuverability, and less energy consumption. However, their flexibility is associated with undesired vibrations, making accurate positioning challenging. As most of the existing controllers are model-based, their performances are affected by uncertainties and often require the feedback of all the states. This makes such control challenging and expensive. Interestingly, despite its poor position tracking, the input shaping control (ISC) proved to be effective in oscillation suppression of flexible structures. In this paper, precise automation of the FLM is presented by hybridizing an improved input shaping control (iISC) with a model-free fuzzy logic control (FLC), and the model-based sliding mode control (SMC). The single feedback FLC, and SMC were designed for the position control while the iISC provided the tip deflection control. Three parameters of the FLM, namely, the length, mass, and spring stiffness of the link were used to assess the sensitivity of the controllers. With the maximum velocity of 94 deg/s and the maximum r.m.s of 0.33 deg, ISC+FLC has increased the velocity of the iISC by at least 77% and improved the poor oscillation suppression of the FLC by at least 64%. Thus, the analysis demonstrated that the iISC+FLC could provide precise automation of the FLM by measuring the output of only one state (position), making it cost-effective and reduces the complexity and computation time of the full-state feedback controllers.

To provide reliable position control for a permanent-magnet synchronous motor (PMSM) under conditions of lumped disturbances such as external load torque fluctuation and system parameter variation, an adaptive backstepping sliding-mode control (ABSMC) with a nonlinear disturbance observer (NDO) is proposed. An ABSMC is a non-cascade technique that employs a position-current single-loop control structure rather than a conventional cascade control structure for vector control of the PMSM. This method uses Lyapunov theory to design a control law that ensures the motor position reaches a desired value in a finite period of time and consequently achieves a rapid transient response. The proposed ABSMC incorporates adaptive convergence gain to avoid a large overshoot under point-to-point position command. The NDO with nonlinear observer gain is proposed to estimate unknown disturbances and provide feed-forward compensation for the ABSMC, improving robustness and reducing steady-state position error. The proposed methods are applied to an industrial motor drive to confirm their validity in real-world operating environments.

Electrohydrostatic actuators (EHAs) are used to replace traditional centralized hydraulic systems to reduce weight and improve efficiency and maintainability. This paper proposes a cascade active disturbance rejection control (C‐ADRC) method for single‐rod EHAs with parametric uncertainties and severe external disturbances. The studied EHA can be transformed into a cascade connection of a first‐order pressure system and a second‐order position system. Two linear active disturbance rejection controllers are designed for the inner pressure system and the outer position system to estimate and compensate for various uncertainties in the two loops, respectively. The uniqueness of the C‐ADRC is that the two linear active disturbance rejection controllers are designed by making full use of the measurable states and known model information of the EHA system. It is theoretically proved that the closed‐loop system is semi‐globally uniformly ultimately bounded. Moreover, the proposed controller can theoretically ensure position tracking with desired accuracy as the bandwidth of extended state observers (ESOs) becomes sufficiently high. Simulation and experimental results verify the effectiveness of the proposed method. [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. [ABSTRACT FROM AUTHOR]

Position tracking modeling and automatic control of an innovative anchor beam supporting robot are presented. Specifically, the forward and inverse kinematics model integrated with BP neural network and the mechanical-hydraulic co-simulation model based on ante-valve pressure compensation method are developed and applied. The experimental system is built to verify the models and method. The results show that position tracking precision can reach the sub-centimeter level. The influence of variable load on hydraulic flow control is weakened effectively and the stability and controllability of load sensitive system is improved. The developed model and control approach are valuable for virtual development and automated testing during the commissioning of hydraulic manipulator. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This article presents a redundant control strategy of fully-actuated underwater vehicles. The proposed strategy offers vehicles more control flexibility for addressing the position tracking problem under the attitudes and velocities constraints. In kinematics, position tracking is formulated as a convex optimization problem, where the velocity constraints are considered as a feasible region and the attitudes are bounded via a barrier function. Then, a conservative boundary is determined in the context of stability analysis of the dynamic controller with a disturbance observer and an auxiliary system so that kinematic variables lie in the constraints even with the velocity tracking error. Also, it is proven that the position tracking error can converge to a neighborhood about zero, which can be made arbitrarily small. The simulations and experimental results through multiple scenarios have illustrated the efficiency of the proposed strategy. [ABSTRACT FROM AUTHOR]

In this article, a min-max model predictive control (MPC) method of planar motors is proposed for the first time to achieve robust precision position tracking, which has a low computational burden and strong capability to deal with the problems of stability, robustness, optimization, and input constraints. A state-space model with a homogeneous state equation is built to describe the dynamics of the time-varying reference trajectory. Combining the state-space model of the reference trajectory and that of the planar motor, an augmented state-space model is established to obtain an error state formulation. Then, using the error state formulation, a min-max optimal control problem subject to the constraints on bounded uncertainty, stability, and control input is developed. Moreover, applying the theory of asymptotically stable invariant ellipsoids and employing the nested invariant ellipsoids, the explicitly linear state-feedback control laws are obtained using a linear-matrix-inequalities based offline control algorithm. Finally, the min-max MPC is applied to a planar motor system developed in the laboratory for an experimentally comparative study. The results demonstrate the effectiveness of the proposed min-max MPC of planar motor for robust precision position tracking applications. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

DC motors are widely used in industries to provide mechanical power in speed and torque. The position and speed control of DC motors is receiving interest from the scientific community in robotics, especially in robotic arms, a flexible joint manipulator. The current research work is based on the position control of DC motors using experimental investigations in LabVIEW. The linear control strategy is applied to track the position and speed of the DC motor with comparative analysis in the LabVIEW platform and simulation analysis in MATLAB. The tracking error in the hardware setup based on LabVIEW programming is slightly greater than the simulation analysis in MATLAB due to the inertial load of the motor during steady-state conditions. The controller output shows the input voltage applied to the DC motor varies between 0 and 8 V to ensure minimal steady error while tracking the position and speed of the DC motor.

Summary: In practical engineering, load torque disturbance and parameter uncertainties are two important factors, which may deteriorate the tracking accuracy of permanent magnet synchronous motor (PMSM) servo system. Therefore, its global position tracking control problem is a challenging task when the load torque disturbance is time‐varying and the motor parameters are unknown. In this article, an internal model controller based on global robust output regulation (GROR) theory is proposed to achieve this control objective. In particular, we first formulate the global position tracking control problem as a GROR problem. Then, the GROR problem is converted into a global robust stabilization problem of an augmented system by constructing an appropriate internal model. Finally, we can stabilize the augmented system by a global stabilization controller instead of local stabilization controller used in the recent work, which guarantees global position tracking and disturbance rejection of PMSM servo system. The excellent position tracking performance of our design is demonstrated by both simulation and experimental results. [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. [ABSTRACT FROM AUTHOR]

Copyright of Control Theory & Applications / Kongzhi Lilun Yu Yinyong is the property of Editorial Department of Control Theory & Applications 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.)

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 1.73 m , which outperforms probabilistic WLAN algorithms such as Memoryless Positioning (RMSE: 10.35 m ) and Nonparametric Information (NI) filter with variable acceleration (RMSE: 5.2 m ) under the same experiment environment. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This article presents point-to-point tracking error reduction algorithm for indoor surveillance vehicle, which is driven by two in-wheel brushless ac (BLac) motors. In general, in order to control the position, additional equipment such as a separate sensor, camera, or GPS to know the absolute or relative position of the vehicle is required. However, when a large number of sensors or expensive equipment is used, the overall price of the system will also increase, which creates a problem. Also, Global Positioning System cannot be used in indoor systems due to poor signal reception. In the proposed method, the position tracking of the autonomous vehicle only adopts the hall sensor of the traction BLac motors and a gyro sensor on the controller, without any absolute position detecting sensors. From the estimated heading angle by the inertia measurement unit sensor and the calculated moving distance by the hall sensor, the tracking path and actual moving distance errors can be estimated in the proposed method. The actual real-time moving path error is compensated by adjusting the speed and heading angle in the presented control method. Through various experiments, it is verified that the position tracking performance of the indoor autonomous vehicle is improved using the proposed method. [ABSTRACT FROM AUTHOR]

Early direction-selective neurons in the primary visual cortex are widely considered to be the main neural basis underlying motion perception even though motion perception can also rely on attentively tracking the position of objects. Because of their small receptive fields, early direction-selective neurons suffer from the aperture problem, which is assumed to be overcome by integrating inputs from many early directionselective neurons. Because the perceived motion of objects sometimes depends on static form information and does not always match the mean direction of local motion signals, the general consensus is that motion integration is form dependent and complex. Based on the fact that early direction-selective neurons respond to motion only within a short temporal window, the present study used stroboscopic motion to test their contribution to motion perception of objects. For conditions under which the perceived motion was impaired by stroboscopic motion, the perceived motion matched the mean direction of local motion signals and was form independent. For classic conditions under which the perceived motion could not be explained by a simple form independent averaging of local motion signals, neutralizing the contribution of early directionselective neurons using stroboscopic motion had little impact on the perceived motion, which demonstrates that the perceived motion relied on position tracking, not on early direction-selective neurons. When the perceived motion relies on position tracking, assuming that motion perception relies on early directionselective neurons can lead to erroneously postulate the existence of complex or form-dependent integration of inputs from early direction-selective neurons. [ABSTRACT FROM AUTHOR]

Flexible link manipulators have recently high attention in research due to the numerous advantages over traditional manipulators. However, flexible link manipulators still have critical problem of less position accuracy due to the tip vibration. Thus, this research contributes by developing a robust P-H∞ integrated controller for a flexible link manipulator (FLM). The P-H∞ integrated controller is a combination of Proportional (p ) controller and H∞ controller which helps of possession several advantages such as optimal position tracking, effective vibration repression, and robust to reject disturbances. The proposed P-H∞ integrated controller has been simulated to control the FLM system using MATLAB/Simulink toolbox. The results have demonstrated satisfactory performance of the proposed P-H∞ integrated controller in terms of position tracking, vibration repression, and disturbance rejection.

Aiming at the characteristics of non-linearity,uncertainty and susceptibility to disturbance of single-degree-of-freedom magnetic levitation ball system,a back-stepping control method based on extended state observer (ESO-BS) was proposed to improve the control performance of the system.The extended state observer was used to estimate the position,velocity and disturbance information of the levitation ball in real time when the system was disturbed by uncertainty.The estimation was combined with the controller design,then the back-stepping method was used to design the levitation position tracking control law of the magnetic levitation ball,and the Lyapunov method was used to prove the ultimate bounded convergence of the tracking error of the system.The simulation results show that,compared with PID control,the adjusting time of ESO-BS control system is 0.01 s,while that of PID control is 0.08 s,which is obviously longer,so the dynamic characteristic of ESO-BS control is better than that of PID control.When there is uncertainty in the system,the designed control law can realize the stable suspension of the ball,and can realize the position tracking according to the required suspension height position.

This article presents research on a hybrid vertical take‐off and landing (VTOL) unmanned aerial vehicle (UAV) supported by a relative positioning system, enabling the deployment of autonomous missions from ship‐based helipads in maritime conditions. A crucial issue to be solved is ensuring precise positioning of the UAV relative to the landing pad in the take‐off and landing phases. To achieve this, an extended Kalman filter (EKF) is implemented on the UAV's onboard computer, which integrates the positioning data from the UAV's global navigation satellite system receiver and the positioning data of the landing pad broadcast by the landing pad navigation station (LNS). The EKF estimates both the absolute and relative position of the UAV, which are required for autonomous take‐off and landing on the moving landing pad. In unfavorable weather conditions, EKF also uses data from an optional local positioning system to keep the accuracy within the range 1–3 m. The research was concluded by experimental verification during a ferry cruise over the Baltic Sea. During the research, the VTOL UAV performed two fully autonomous flight missions at the range about 1 km from the moving ferry in international waters. Each of them ended with a successful landing back on the helipad with an accuracy matching its required level, which was already achieved in the previous research carried out in inland conditions. Data recorded during real flights confirm that the developed system, consisting of a hybrid VTOL UAV and a LNS, is ready to be utilized in autonomous missions at sea. Factors having a critical impact on the safety of use of the VTOL UAV in marine conditions were also identified, which were not observed during the research in inland conditions, and are related directly to turbulence around the landing pad. [ABSTRACT FROM AUTHOR]

In this article, an adaptive dynamic surface control method with nonlinear disturbance observers is proposed for accurate position tracking of an electro-hydraulic servo system with unknown time-varying inner or external disturbances. The dynamic surface control approach adopted in the proposed controller is used to ameliorate the inherent complexity differentiation explosion of traditional backstepping method, which significantly simplifies the controller design process. The designed nonlinear disturbance observers are exploited to online estimate the inner or external disturbances of electro-hydraulic servo systems, and the performance degradation resulted from unknown time-varying disturbances is effectively suppressed. To further compensate for the system's time-varying uncertain parameters, parameter adaptive updating laws are designed and combined in the proposed controller for accurate position tracking of electro-hydraulic servo systems. The closed-loop stability of the proposed controller is theoretically guaranteed by rigorous Lyapunov analysis. Comparative experimental results are carried out on a typical single-degree-of-freedom electro-hydraulic servo system, and the feasibility together with the superiority of the proposed controller is experimentally validated. [ABSTRACT FROM AUTHOR]