Trajectory Tracking of a Tri-Rotor Aerial Vehicle Using an MRAC-Based Robust Hybrid Control Algorithm

Directory of Open Access Journals (Sweden)

Zain Anwar Ali

2017-01-01

Full Text Available In this paper, a novel Model Reference Adaptive Control (MRAC-based hybrid control algorithm is presented for the trajectory tracking of a tri-rotor Unmanned Aerial Vehicle (UAV. The mathematical model of the tri-rotor is based on the Newton–Euler formula, whereas the MRAC-based hybrid controller consists of Fuzzy Proportional Integral Derivative (F-PID and Fuzzy Proportional Derivative (F-PD controllers. MRAC is used as the main controller for the dynamics, while the parameters of the adaptive controller are fine-tuned by the F-PD controller for the altitude control subsystem and the F-PID controller for the attitude control subsystem of the UAV. The stability of the system is ensured and proven by Lyapunov stability analysis. The proposed control algorithm is tested and verified using computer simulations for the trajectory tracking of the desired path as an input. The effectiveness of our proposed algorithm is compared with F-PID and the Fuzzy Logic Controller (FLC. Our proposed controller exhibits much less steady state error, quick error convergence in the presence of disturbance or noise, and model uncertainties.

Lane changing trajectory planning and tracking control for intelligent vehicle on curved road.

Science.gov (United States)

Wang, Lukun; Zhao, Xiaoying; Su, Hao; Tang, Gongyou

2016-01-01

This paper explores lane changing trajectory planning and tracking control for intelligent vehicle on curved road. A novel arcs trajectory is planned for the desired lane changing trajectory. A kinematic controller and a dynamics controller are designed to implement the trajectory tracking control. Firstly, the kinematic model and dynamics model of intelligent vehicle with non-holonomic constraint are established. Secondly, two constraints of lane changing on curved road in practice (LCCP) are proposed. Thirdly, two arcs with same curvature are constructed for the desired lane changing trajectory. According to the geometrical characteristics of arcs trajectory, equations of desired state can be calculated. Finally, the backstepping method is employed to design a kinematic trajectory tracking controller. Then the sliding-mode dynamics controller is designed to ensure that the motion of the intelligent vehicle can follow the desired velocity generated by kinematic controller. The stability of control system is proved by Lyapunov theory. Computer simulation demonstrates that the desired arcs trajectory and state curves with B-spline optimization can meet the requirements of LCCP constraints and the proposed control schemes can make tracking errors to converge uniformly.

Sliding Mode Control for Trajectory Tracking of an Intelligent Wheelchair

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Razvan SOLEA

2009-12-01

Full Text Available This paper deal with a robust sliding-mode trajectory tracking controller, fornonholonomic wheeled mobile robots and its experimental evaluation by theimplementation in an intelligent wheelchair (RobChair. The proposed control structureis based on two nonlinear sliding surfaces ensuring the tracking of the three outputvariables, with respect to the nonholonomic constraint. The performances of theproposed controller for the trajectory planning problem with comfort constraint areverified through the real time acceleration provided by an inertial measurement unit.

Minimum Time Trajectory Optimization of CNC Machining with Tracking Error Constraints

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Qiang Zhang

2014-01-01

Full Text Available An off-line optimization approach of high precision minimum time feedrate for CNC machining is proposed. Besides the ordinary considered velocity, acceleration, and jerk constraints, dynamic performance constraint of each servo drive is also considered in this optimization problem to improve the tracking precision along the optimized feedrate trajectory. Tracking error is applied to indicate the servo dynamic performance of each axis. By using variable substitution, the tracking error constrained minimum time trajectory planning problem is formulated as a nonlinear path constrained optimal control problem. Bang-bang constraints structure of the optimal trajectory is proved in this paper; then a novel constraint handling method is proposed to realize a convex optimization based solution of the nonlinear constrained optimal control problem. A simple ellipse feedrate planning test is presented to demonstrate the effectiveness of the approach. Then the practicability and robustness of the trajectory generated by the proposed approach are demonstrated by a butterfly contour machining example.

Trajectory generation for manipulators using linear quadratic optimal tracking

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Olav Egeland

1989-04-01

Full Text Available The reference trajectory is normally known in advance in manipulator control which makes it possible to apply linear quadratic optimal tracking. This gives a control system which rounds corners and generates optimal feedforward. The method may be used for references consisting of straight-line segments as an alternative to the two-step method of using splines to smooth the reference and then applying feedforward. In addition, the method can be used for more complex trajectories. The actual dynamics of the manipulator are taken into account, and this results in smooth and accurate tracking. The method has been applied in combination with the computed torque technique and excellent performance was demonstrated in a simulation study. The method has also been applied experimentally to an industrial spray-painting robot where a saw-tooth reference was tracked. The corner was rounded extremely well, and the steady-state tracking error was eliminated by the optimal feedforward.

Distributed adaptive asymptotically consensus tracking control of uncertain Euler-Lagrange systems under directed graph condition.

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Wang, Wei; Wen, Changyun; Huang, Jiangshuai; Fan, Huijin

2017-11-01

In this paper, a backstepping based distributed adaptive control scheme is proposed for multiple uncertain Euler-Lagrange systems under directed graph condition. The common desired trajectory is allowed totally unknown by part of the subsystems and the linearly parameterized trajectory model assumed in currently available results is no longer needed. To compensate the effects due to unknown trajectory information, a smooth function of consensus errors and certain positive integrable functions are introduced in designing virtual control inputs. Besides, to overcome the difficulty of completely counteracting the coupling terms of distributed consensus errors and parameter estimation errors in the presence of asymmetric Laplacian matrix, extra information transmission of local parameter estimates are introduced among linked subsystem and adaptive gain technique is adopted to generate distributed torque inputs. It is shown that with the proposed distributed adaptive control scheme, global uniform boundedness of all the closed-loop signals and asymptotically output consensus tracking can be achieved. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Accurately tracking single-cell movement trajectories in microfluidic cell sorting devices.

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Jeong, Jenny; Frohberg, Nicholas J; Zhou, Enlu; Sulchek, Todd; Qiu, Peng

2018-01-01

Microfluidics are routinely used to study cellular properties, including the efficient quantification of single-cell biomechanics and label-free cell sorting based on the biomechanical properties, such as elasticity, viscosity, stiffness, and adhesion. Both quantification and sorting applications require optimal design of the microfluidic devices and mathematical modeling of the interactions between cells, fluid, and the channel of the device. As a first step toward building such a mathematical model, we collected video recordings of cells moving through a ridged microfluidic channel designed to compress and redirect cells according to cell biomechanics. We developed an efficient algorithm that automatically and accurately tracked the cell trajectories in the recordings. We tested the algorithm on recordings of cells with different stiffness, and showed the correlation between cell stiffness and the tracked trajectories. Moreover, the tracking algorithm successfully picked up subtle differences of cell motion when passing through consecutive ridges. The algorithm for accurately tracking cell trajectories paves the way for future efforts of modeling the flow, forces, and dynamics of cell properties in microfluidics applications.

Accurately tracking single-cell movement trajectories in microfluidic cell sorting devices.

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Jenny Jeong

Full Text Available Microfluidics are routinely used to study cellular properties, including the efficient quantification of single-cell biomechanics and label-free cell sorting based on the biomechanical properties, such as elasticity, viscosity, stiffness, and adhesion. Both quantification and sorting applications require optimal design of the microfluidic devices and mathematical modeling of the interactions between cells, fluid, and the channel of the device. As a first step toward building such a mathematical model, we collected video recordings of cells moving through a ridged microfluidic channel designed to compress and redirect cells according to cell biomechanics. We developed an efficient algorithm that automatically and accurately tracked the cell trajectories in the recordings. We tested the algorithm on recordings of cells with different stiffness, and showed the correlation between cell stiffness and the tracked trajectories. Moreover, the tracking algorithm successfully picked up subtle differences of cell motion when passing through consecutive ridges. The algorithm for accurately tracking cell trajectories paves the way for future efforts of modeling the flow, forces, and dynamics of cell properties in microfluidics applications.

Tumor tracking and motion compensation with an adaptive tumor tracking system (ATTS): System description and prototype testing

International Nuclear Information System (INIS)

Wilbert, Juergen; Meyer, Juergen; Baier, Kurt; Guckenberger, Matthias; Herrmann, Christian; Hess, Robin; Janka, Christian; Ma Lei; Mersebach, Torben; Richter, Anne; Roth, Michael; Schilling, Klaus; Flentje, Michael

2008-01-01

A novel system for real-time tumor tracking and motion compensation with a robotic HexaPOD treatment couch is described. The approach is based on continuous tracking of the tumor motion in portal images without implanted fiducial markers, using the therapeutic megavoltage beam, and tracking of abdominal breathing motion with optical markers. Based on the two independently acquired data sets the table movements for motion compensation are calculated. The principle of operation of the entire prototype system is detailed first. In the second part the performance of the HexaPOD couch was investigated with a robotic four-dimensional-phantom capable of simulating real patient tumor trajectories in three-dimensional space. The performance and limitations of the HexaPOD table and the control system were characterized in terms of its dynamic behavior. The maximum speed and acceleration of the HexaPOD were 8 mm/s and 34.5 mm/s 2 in the lateral direction, and 9.5 mm/s and 29.5 mm/s 2 in longitudinal and anterior-posterior direction, respectively. Base line drifts of the mean tumor position of realistic lung tumor trajectories could be fully compensated. For continuous tumor tracking and motion compensation a reduction of tumor motion up to 68% of the original amplitude was achieved. In conclusion, this study demonstrated that it is technically feasible to compensate breathing induced tumor motion in the lung with the adaptive tumor tracking system

Indoor Trajectory Tracking Scheme Based on Delaunay Triangulation and Heuristic Information in Wireless Sensor Networks.

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Qin, Junping; Sun, Shiwen; Deng, Qingxu; Liu, Limin; Tian, Yonghong

2017-06-02

Object tracking and detection is one of the most significant research areas for wireless sensor networks. Existing indoor trajectory tracking schemes in wireless sensor networks are based on continuous localization and moving object data mining. Indoor trajectory tracking based on the received signal strength indicator ( RSSI ) has received increased attention because it has low cost and requires no special infrastructure. However, RSSI tracking introduces uncertainty because of the inaccuracies of measurement instruments and the irregularities (unstable, multipath, diffraction) of wireless signal transmissions in indoor environments. Heuristic information includes some key factors for trajectory tracking procedures. This paper proposes a novel trajectory tracking scheme based on Delaunay triangulation and heuristic information (TTDH). In this scheme, the entire field is divided into a series of triangular regions. The common side of adjacent triangular regions is regarded as a regional boundary. Our scheme detects heuristic information related to a moving object's trajectory, including boundaries and triangular regions. Then, the trajectory is formed by means of a dynamic time-warping position-fingerprint-matching algorithm with heuristic information constraints. Field experiments show that the average error distance of our scheme is less than 1.5 m, and that error does not accumulate among the regions.

Optimal Point-to-Point Trajectory Tracking of Redundant Manipulators using Generalized Pattern Search

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Thi Rein Myo

2008-11-01

Full Text Available Optimal point-to-point trajectory planning for planar redundant manipulator is considered in this study. The main objective is to minimize the sum of the position error of the end-effector at each intermediate point along the trajectory so that the end-effector can track the prescribed trajectory accurately. An algorithm combining Genetic Algorithm and Pattern Search as a Generalized Pattern Search GPS is introduced to design the optimal trajectory. To verify the proposed algorithm, simulations for a 3-D-O-F planar manipulator with different end-effector trajectories have been carried out. A comparison between the Genetic Algorithm and the Generalized Pattern Search shows that The GPS gives excellent tracking performance.

Vision-Based Leader Vehicle Trajectory Tracking for Multiple Agricultural Vehicles.

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Zhang, Linhuan; Ahamed, Tofael; Zhang, Yan; Gao, Pengbo; Takigawa, Tomohiro

2016-04-22

The aim of this study was to design a navigation system composed of a human-controlled leader vehicle and a follower vehicle. The follower vehicle automatically tracks the leader vehicle. With such a system, a human driver can control two vehicles efficiently in agricultural operations. The tracking system was developed for the leader and the follower vehicle, and control of the follower was performed using a camera vision system. A stable and accurate monocular vision-based sensing system was designed, consisting of a camera and rectangular markers. Noise in the data acquisition was reduced by using the least-squares method. A feedback control algorithm was used to allow the follower vehicle to track the trajectory of the leader vehicle. A proportional-integral-derivative (PID) controller was introduced to maintain the required distance between the leader and the follower vehicle. Field experiments were conducted to evaluate the sensing and tracking performances of the leader-follower system while the leader vehicle was driven at an average speed of 0.3 m/s. In the case of linear trajectory tracking, the RMS errors were 6.5 cm, 8.9 cm and 16.4 cm for straight, turning and zigzag paths, respectively. Again, for parallel trajectory tracking, the root mean square (RMS) errors were found to be 7.1 cm, 14.6 cm and 14.0 cm for straight, turning and zigzag paths, respectively. The navigation performances indicated that the autonomous follower vehicle was able to follow the leader vehicle, and the tracking accuracy was found to be satisfactory. Therefore, the developed leader-follower system can be implemented for the harvesting of grains, using a combine as the leader and an unloader as the autonomous follower vehicle.

An adaptive unscented Kalman filter-based adaptive tracking control for wheeled mobile robots with control constrains in the presence of wheel slipping

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Mingyue Cui

2016-09-01

Full Text Available A novel control approach is proposed for trajectory tracking of a wheeled mobile robot with unknown wheels’ slipping. The longitudinal and lateral slipping are considered and processed as three time-varying parameters. The adaptive unscented Kalman filter is then designed to estimate the slipping parameters online, an adaptive adjustment of the noise covariances in the estimation process is implemented using a technique of covariance matching in the adaptive unscented Kalman filter context. Considering the practical physical constrains, a stable tracking control law for this robot system is proposed by the backstepping method. Asymptotic stability is guaranteed by Lyapunov stability theory. Control gains are determined online by applying pole placement method. Simulation and real experiment results show the effectiveness and robustness of the proposed control method.

PaTAVTT: A Hardware-in-the-Loop Scaled Platform for Testing Autonomous Vehicle Trajectory Tracking

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Zhigang Xu

2017-01-01

Full Text Available With the advent of autonomous vehicles, in particular its adaptability to harsh conditions, the research and development of autonomous vehicles attract significant attention by not only academia but also practitioners. Due to the high risk, high cost, and difficulty to test autonomous vehicles under harsh conditions, the hardware-in-the-loop (HIL scaled platform has been proposed as it is a safe, inexpensive, and effective test method. This platform system consists of scaled autonomous vehicle, scaled roadway, monitoring center, transmission device, positioning device, and computers. This paper uses a case of the development process of tracking control for high-speed U-turn to build the tracking control function. Further, a simplified vehicle dynamics model and a trajectory tracking algorithm have been considered to build the simulation test. The experiment results demonstrate the effectiveness of the HIL scaled platform.

Reference trajectory tracking for a multi-DOF robot arm

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Krasňanský Róbert

2015-12-01

Full Text Available This paper presents the problem of tracking the generated reference trajectory by the simulation model of a multi-DOF robot arm. The kinematic transformation between task space and joint configuration coordinates is nonlinear and configuration dependent. To obtain the solution of the forward kinematics problem, the homogeneous transformation matrix is used. A solution to the inverse kinematics is a vector of joint configuration coordinates calculated using of pseudoinverse Jacobian technique. These coordinates correspond to a set of task space coordinates. The algorithm is presented which uses iterative solution and is simplified by considering stepper motors in robot arm joints. The reference trajectory in Cartesian coordinate system is generated on-line by the signal generator previously developed in MS Excel. Dynamic Data Exchange communication protocol allows sharing data with Matlab-Simulink. These data represent the reference tracking trajectory of the end effector. Matlab-Simulink software is used to calculate the representative joint rotations. The proposed algorithm is demonstrated experimentally on the model of 7-DOF robot arm system.

Adaptive Tracking and Obstacle Avoidance Control for Mobile Robots with Unknown Sliding

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Mingyue Cui

2012-11-01

Full Text Available An adaptive control approach is proposed for trajectory tracking and obstacle avoidance for mobile robots with consideration given to unknown sliding. A kinematic model of mobile robots is established in this paper, in which both longitudinal and lateral sliding are considered and processed as three time-varying parameters. A sliding model observer is introduced to estimate the sliding parameters online. A stable tracking control law for this nonholonomic system is proposed to compensate the unknown sliding effect. From Lyapunov-stability analysis, it is proved, regardless of unknown sliding, that tracking errors of the controlled closed-loop system are asymptotically stable, the tracking errors converge to zero outside the obstacle detection region and obstacle avoidance is guaranteed inside the obstacle detection region. The efficiency and robustness of the proposed control system are verified by simulation results.

Visual Trajectory-Tracking Model-Based Control for Mobile Robots

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Andrej Zdešar

2013-09-01

Full Text Available In this paper we present a visual-control algorithm for driving a mobile robot along the reference trajectory. The configuration of the system consists of a two-wheeled differentially driven mobile robot that is observed by an overhead camera, which can be placed at arbitrary, but reasonable, inclination with respect to the ground plane. The controller must be capable of generating appropriate tangential and angular control velocities for the trajectory-tracking problem, based on the information received about the robot position obtained in the image. To be able to track the position of the robot through a sequence of images in real-time, the robot is marked with an artificial marker that can be distinguishably recognized by the image recognition subsystem. Using the property of differential flatness, a dynamic feedback compensator can be designed for the system, thereby extending the system into a linear form. The presented control algorithm for reference tracking combines a feedforward and a feedback loop, the structure also known as a two DOF control scheme. The feedforward part should drive the system to the vicinity of the reference trajectory and the feedback part should eliminate any errors that occur due to noise and other disturbances etc. The feedforward control can never achieve accurate reference following, but this deficiency can be eliminated with the introduction of the feedback loop. The design of the model predictive control is based on the linear error model. The model predictive control is given in analytical form, so the computational burden is kept at a reasonable level for real-time implementation. The control algorithm requires that a reference trajectory is at least twice differentiable function. A suitable approach to design such a trajectory is by exploiting some useful properties of the Bernstein-Bézier parametric curves. The simulation experiments as well as real system experiments on a robot normally used in the

Quadrotor trajectory tracking using PID cascade control

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Idres, M.; Mustapha, O.; Okasha, M.

2017-12-01

Quadrotors have been applied to collect information for traffic, weather monitoring, surveillance and aerial photography. In order to accomplish their mission, quadrotors have to follow specific trajectories. This paper presents proportional-integral-derivative (PID) cascade control of a quadrotor for path tracking problem when velocity and acceleration are small. It is based on near hover controller for small attitude angles. The integral of time-weighted absolute error (ITAE) criterion is used to determine the PID gains as a function of quadrotor modeling parameters. The controller is evaluated in three-dimensional environment in Simulink. Overall, the tracking performance is found to be excellent for small velocity condition.

Construction of a WMR for Trajectory Tracking Control: Experimental Results

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R. Silva-Ortigoza

2013-01-01

Full Text Available This paper reports a solution for trajectory tracking control of a differential drive wheeled mobile robot (WMR based on a hierarchical approach. The general design and construction of the WMR are described. The hierarchical controller proposed has two components: a high-level control and a low-level control. The high-level control law is based on an input-output linearization scheme for the robot kinematic model, which provides the desired angular velocity profiles that the WMR has to track in order to achieve the desired position (x*,y* and orientation (φ*. Then, a low-level control law, based on a proportional integral (PI approach, is designed to control the velocity of the WMR wheels to ensure those tracking features. Regarding the trajectories, this paper provides the solution or the following cases: (1 time-varying parametric trajectories such as straight lines and parabolas and (2 smooth curves fitted by cubic splines which are generated by the desired data points x1*,y1*,…,xn*,yn*. A straightforward algorithm is developed for constructing the cubic splines. Finally, this paper includes an experimental validation of the proposed technique by employing a DS1104 dSPACE electronic board along with MATLAB/Simulink software.

Lane Changing Trajectory Planning and Tracking Controller Design for Intelligent Vehicle Running on Curved Road

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Lie Guo

2014-01-01

Full Text Available To enhance the active safety and realize the autonomy of intelligent vehicle on highway curved road, a lane changing trajectory is planned and tracked for lane changing maneuver on curved road. The kinematics model of the intelligent vehicle with nonholonomic constraint feature and the tracking error model are established firstly. The longitudinal and lateral coupling and the difference of curvature radius between the outside and inside lane are taken into account, which is helpful to enhance the authenticity of desired lane changing trajectory on curved road. Then the trajectory tracking controller of closed-loop control structure is derived using integral backstepping method to construct a new virtual variable. The Lyapunov theory is applied to analyze the stability of the proposed tracking controller. Simulation results demonstrate that this controller can guarantee the convergences of both the relative position tracking errors and the position tracking synchronization.

Adaptive fuzzy tracking control for a constrained flexible air-breathing hypersonic vehicle based on actuator compensation

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Peng Fei Wang

2016-10-01

Full Text Available The design of an adaptive fuzzy tracking control for a flexible air-breathing hypersonic vehicle with actuator constraints is discussed. Based on functional decomposition methodology, velocity and altitude controllers are designed. Fuzzy logic systems are applied to approximate the lumped uncertainty of each subsystem of air-breathing hypersonic vehicle model. Every controllers contain only one adaptive parameter that needs to be updated online with a minimal-learning-parameter scheme. The back-stepping design is not demanded by converting the altitude subsystem into the normal output-feedback formulation, which predigests the design of a controller. The special contribution is that novel auxiliary systems are developed to compensate both the tracking errors and desired control laws, based on which the explored controller can still provide effective tracking of velocity and altitude commands when the inputs are saturated. Finally, reference trajectory tracking simulation shows the effectiveness of the proposed method in its application to air-breathing hypersonic vehicle control.

Robust back-stepping output feedback trajectory tracking for quadrotors via extended state observer and sigmoid tracking differentiator

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Shao, Xingling; Liu, Jun; Wang, Honglun

2018-05-01

In this paper, a robust back-stepping output feedback trajectory tracking controller is proposed for quadrotors subject to parametric uncertainties and external disturbances. Based on the hierarchical control principle, the quadrotor dynamics is decomposed into translational and rotational subsystems to facilitate the back-stepping control design. With given model information incorporated into observer design, a high-order extended state observer (ESO) that relies only on position measurements is developed to estimate the remaining unmeasurable states and the lumped disturbances in rotational subsystem simultaneously. To overcome the problem of "explosion of complexity" in the back-stepping design, the sigmoid tracking differentiator (STD) is introduced to compute the derivative of virtual control laws. The advantage is that the proposed controller via output-feedback scheme not only can ensure good tracking performance using very limited information of quadrotors, but also has the ability of handling the undesired uncertainties. The stability analysis is established using the Lyapunov theory. Simulation results demonstrate the effectiveness of the proposed control scheme in achieving a guaranteed tracking performance with respect to an 8-shaped reference trajectory.

Analysis of Load-Carrying Capacity for Redundant Free-Floating Space Manipulators in Trajectory Tracking Task

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Qingxuan Jia

2014-01-01

Full Text Available The aim of this paper is to analyze load-carrying capacity of redundant free-floating space manipulators (FFSM in trajectory tracking task. Combined with the analysis of influential factors in load-carrying process, evaluation of maximum load-carrying capacity (MLCC is described as multiconstrained nonlinear programming problem. An efficient algorithm based on repeated line search within discontinuous feasible region is presented to determine MLCC for a given trajectory of the end-effector and corresponding joint path. Then, considering the influence of MLCC caused by different initial configurations for the starting point of given trajectory, a kind of maximum payload initial configuration planning method is proposed by using PSO algorithm. Simulations are performed for a particular trajectory tracking task of the 7-DOF space manipulator, of which MLCC is evaluated quantitatively. By in-depth research of the simulation results, significant gap between the values of MLCC when using different initial configurations is analyzed, and the discontinuity of allowable load-carrying capacity is illustrated. The proposed analytical method can be taken as theoretical foundation of feasibility analysis, trajectory optimization, and optimal control of trajectory tracking task in on-orbit load-carrying operations.

Consensus seeking, formation keeping, and trajectory tracking in multiple vehicle cooperative control

Science.gov (United States)

Ren, Wei

Cooperative control problems for multiple vehicle systems can be categorized as either formation control problems with applications to mobile robots, unmanned air vehicles, autonomous underwater vehicles, satellites, aircraft, spacecraft, and automated highway systems, or non-formation control problems such as task assignment, cooperative transport, cooperative role assignment, air traffic control, cooperative timing, and cooperative search. The cooperative control of multiple vehicle systems poses significant theoretical and practical challenges. For cooperative control strategies to be successful, numerous issues must be addressed. We consider three important and correlated issues: consensus seeking, formation keeping, and trajectory tracking. For consensus seeking, we investigate algorithms and protocols so that a team of vehicles can reach consensus on the values of the coordination data in the presence of imperfect sensors, communication dropout, sparse communication topologies, and noisy and unreliable communication links. The main contribution of this dissertation in this area is that we show necessary and/or sufficient conditions for consensus seeking with limited, unidirectional, and unreliable information exchange under fixed and switching interaction topologies (through either communication or sensing). For formation keeping, we apply a so-called "virtual structure" approach to spacecraft formation flying and multi-vehicle formation maneuvers. As a result, single vehicle path planning and trajectory generation techniques can be employed for the virtual structure while trajectory tracking strategies can be employed for each vehicle. The main contribution of this dissertation in this area is that we propose a decentralized architecture for multiple spacecraft formation flying in deep space with formation feedback introduced. This architecture ensures the necessary precision in the presence of actuator saturation, internal and external disturbances, and

Adaptive tracking control of nonholonomic systems: an example

NARCIS (Netherlands)

Lefeber, A.A.J.; Nijmeijer, Henk

1999-01-01

We study an example of an adaptive (state) tracking control problem for a four-wheel mobile robot, as it is an illustrative example of the general adaptive state-feedback tracking control problem. It turns out that formulating the adaptive state-feedback tracking control problem is not

Tracking adaptation and measuring development

Energy Technology Data Exchange (ETDEWEB)

Brooks, Nick; Anderson, Simon; Ayers, Jessica; Burton, Ian; Tellam, Ian

2011-11-15

This is the first paper in the new IIED Climate Change Working Paper series. As adaptation to climate change becomes the focus of increasing attention and the target of significant spending, there is a growing need for frameworks and tools that enable organisations to track and assess the outcomes of adaptation interventions. This paper presents a coherent framework for climate change adaptation programming, including potential indicators, or indicator categories/types, for tracking and evaluating the success of adaptation support and adaptation interventions. The paper begins with a discussion of some of the key issues related to the evaluation of adaptation, and outlines some of the main difficulties and constraints with respect to the development of adaptation indicators. Next, an evaluation framework is proposed and indicator categories or 'domains' are identified. Lastly, key conclusions are provided and a theory of change is outlined that shows how development and use of the framework could lead to more effective adaptation investments for climate resilient development.

RGBD Video Based Human Hand Trajectory Tracking and Gesture Recognition System

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Weihua Liu

2015-01-01

Full Text Available The task of human hand trajectory tracking and gesture trajectory recognition based on synchronized color and depth video is considered. Toward this end, in the facet of hand tracking, a joint observation model with the hand cues of skin saliency, motion and depth is integrated into particle filter in order to move particles to local peak in the likelihood. The proposed hand tracking method, namely, salient skin, motion, and depth based particle filter (SSMD-PF, is capable of improving the tracking accuracy considerably, in the context of the signer performing the gesture toward the camera device and in front of moving, cluttered backgrounds. In the facet of gesture recognition, a shape-order context descriptor on the basis of shape context is introduced, which can describe the gesture in spatiotemporal domain. The efficient shape-order context descriptor can reveal the shape relationship and embed gesture sequence order information into descriptor. Moreover, the shape-order context leads to a robust score for gesture invariant. Our approach is complemented with experimental results on the settings of the challenging hand-signed digits datasets and American sign language dataset, which corroborate the performance of the novel techniques.

Adaptive density trajectory cluster based on time and space distance

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Liu, Fagui; Zhang, Zhijie

2017-10-01

There are some hotspot problems remaining in trajectory cluster for discovering mobile behavior regularity, such as the computation of distance between sub trajectories, the setting of parameter values in cluster algorithm and the uncertainty/boundary problem of data set. As a result, based on the time and space, this paper tries to define the calculation method of distance between sub trajectories. The significance of distance calculation for sub trajectories is to clearly reveal the differences in moving trajectories and to promote the accuracy of cluster algorithm. Besides, a novel adaptive density trajectory cluster algorithm is proposed, in which cluster radius is computed through using the density of data distribution. In addition, cluster centers and number are selected by a certain strategy automatically, and uncertainty/boundary problem of data set is solved by designed weighted rough c-means. Experimental results demonstrate that the proposed algorithm can perform the fuzzy trajectory cluster effectively on the basis of the time and space distance, and obtain the optimal cluster centers and rich cluster results information adaptably for excavating the features of mobile behavior in mobile and sociology network.

Adaptive Jacobian Fuzzy Attitude Control for Flexible Spacecraft Combined Attitude and Sun Tracking System

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Chak, Yew-Chung; Varatharajoo, Renuganth

2016-07-01

Many spacecraft attitude control systems today use reaction wheels to deliver precise torques to achieve three-axis attitude stabilization. However, irrecoverable mechanical failure of reaction wheels could potentially lead to mission interruption or total loss. The electrically-powered Solar Array Drive Assemblies (SADA) are usually installed in the pitch axis which rotate the solar arrays to track the Sun, can produce torques to compensate for the pitch-axis wheel failure. In addition, the attitude control of a flexible spacecraft poses a difficult problem. These difficulties include the strong nonlinear coupled dynamics between the rigid hub and flexible solar arrays, and the imprecisely known system parameters, such as inertia matrix, damping ratios, and flexible mode frequencies. In order to overcome these drawbacks, the adaptive Jacobian tracking fuzzy control is proposed for the combined attitude and sun-tracking control problem of a flexible spacecraft during attitude maneuvers in this work. For the adaptation of kinematic and dynamic uncertainties, the proposed scheme uses an adaptive sliding vector based on estimated attitude velocity via approximate Jacobian matrix. The unknown nonlinearities are approximated by deriving the fuzzy models with a set of linguistic If-Then rules using the idea of sector nonlinearity and local approximation in fuzzy partition spaces. The uncertain parameters of the estimated nonlinearities and the Jacobian matrix are being adjusted online by an adaptive law to realize feedback control. The attitude of the spacecraft can be directly controlled with the Jacobian feedback control when the attitude pointing trajectory is designed with respect to the spacecraft coordinate frame itself. A significant feature of this work is that the proposed adaptive Jacobian tracking scheme will result in not only the convergence of angular position and angular velocity tracking errors, but also the convergence of estimated angular velocity to

Experimental Results for Minimum-Time Trajectory Tracking of a Direct-Drive Three-Link Planar Arm

Energy Technology Data Exchange (ETDEWEB)

DRIESSEN,BRIAN; PARKER,GORDON G.

1999-09-01

This work is an experimental investigation of the ability of a real three-link direct-drive arm to track model-based minimum-time trajectories that have been found off-line. Sufficiently large velocity gains in the computed torque control law were not achievable with the velocity sensors described herein. This indicates the critical importance of the velocity sensing when attempting to track trajectories that push the envelope of the system's torque capabilities.

Complex Dynamical Network Control for Trajectory Tracking Using Delayed Recurrent Neural Networks

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Jose P. Perez

2014-01-01

Full Text Available In this paper, the problem of trajectory tracking is studied. Based on the V-stability and Lyapunov theory, a control law that achieves the global asymptotic stability of the tracking error between a delayed recurrent neural network and a complex dynamical network is obtained. To illustrate the analytic results, we present a tracking simulation of a dynamical network with each node being just one Lorenz’s dynamical system and three identical Chen’s dynamical systems.

Quadrotor Trajectory Tracking Based on Quasi-LPV System and Internal Model Control

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ZeFang He

2015-01-01

Full Text Available Internal model control (IMC design method based on quasi-LPV (Linear Parameter Varying system is proposed. In this method, the nonlinear model is firstly transformed to the linear model based on quasi-LPV method; then, the quadrotor nonlinear motion function is transformed to transfer function matrix based on the transformation model from the state space to the transfer function; further, IMC is designed to control the controlled object represented by transfer function matrix and realize quadrotor trajectory tracking. The performance of the controller proposed in this paper is tested by tracking for three reference trajectories with drastic changes. The simulation results indicate that the control method proposed in this paper has stronger robustness to parameters uncertainty and disturbance rejection performance.

An Adaptive Speed Control Approach for DC Shunt Motors

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Ruben Tapia-Olvera

2016-11-01

Full Text Available A B-spline neural networks-based adaptive control technique for angular speed reference trajectory tracking tasks with highly efficient performance for direct current shunt motors is proposed. A methodology for adaptive control and its proper training procedure are introduced. This algorithm sets the control signal without using a detailed mathematical model nor exact values of the parameters of the nonlinear dynamic system. The proposed robust adaptive tracking control scheme only requires measurements of the velocity output signal. Thus, real-time measurements or estimations of acceleration, current and disturbance signals are avoided. Experimental results confirm the efficient and robust performance of the proposed control approach for highly demanding motor operation conditions exposed to variable-speed reference trajectories and completely unknown load torque. Hence, laboratory experimental tests on a direct current shunt motor prove the viability of the proposed adaptive output feedback trajectory tracking control approach.

Decontaminate feature for tracking: adaptive tracking via evolutionary feature subset

Science.gov (United States)

Liu, Qiaoyuan; Wang, Yuru; Yin, Minghao; Ren, Jinchang; Li, Ruizhi

2017-11-01

Although various visual tracking algorithms have been proposed in the last 2-3 decades, it remains a challenging problem for effective tracking with fast motion, deformation, occlusion, etc. Under complex tracking conditions, most tracking models are not discriminative and adaptive enough. When the combined feature vectors are inputted to the visual models, this may lead to redundancy causing low efficiency and ambiguity causing poor performance. An effective tracking algorithm is proposed to decontaminate features for each video sequence adaptively, where the visual modeling is treated as an optimization problem from the perspective of evolution. Every feature vector is compared to a biological individual and then decontaminated via classical evolutionary algorithms. With the optimized subsets of features, the "curse of dimensionality" has been avoided while the accuracy of the visual model has been improved. The proposed algorithm has been tested on several publicly available datasets with various tracking challenges and benchmarked with a number of state-of-the-art approaches. The comprehensive experiments have demonstrated the efficacy of the proposed methodology.

A miniature shoe-mounted orientation determination system for accurate indoor heading and trajectory tracking.

Science.gov (United States)

Zhang, Shengzhi; Yu, Shuai; Liu, Chaojun; Liu, Sheng

2016-06-01

Tracking the position of pedestrian is urgently demanded when the most commonly used GPS (Global Position System) is unavailable. Benefited from the small size, low-power consumption, and relatively high reliability, micro-electro-mechanical system sensors are well suited for GPS-denied indoor pedestrian heading estimation. In this paper, a real-time miniature orientation determination system (MODS) was developed for indoor heading and trajectory tracking based on a novel dual-linear Kalman filter. The proposed filter precludes the impact of geomagnetic distortions on pitch and roll that the heading is subjected to. A robust calibration approach was designed to improve the accuracy of sensors measurements based on a unified sensor model. Online tests were performed on the MODS with an improved turntable. The results demonstrate that the average RMSE (root-mean-square error) of heading estimation is less than 1°. Indoor heading experiments were carried out with the MODS mounted on the shoe of pedestrian. Besides, we integrated the existing MODS into an indoor pedestrian dead reckoning application as an example of its utility in realistic actions. A human attitude-based walking model was developed to calculate the walking distance. Test results indicate that mean percentage error of indoor trajectory tracking achieves 2% of the total walking distance. This paper provides a feasible alternative for accurate indoor heading and trajectory tracking.

Quantization-Based Adaptive Actor-Critic Tracking Control With Tracking Error Constraints.

Science.gov (United States)

Fan, Quan-Yong; Yang, Guang-Hong; Ye, Dan

2018-04-01

In this paper, the problem of adaptive actor-critic (AC) tracking control is investigated for a class of continuous-time nonlinear systems with unknown nonlinearities and quantized inputs. Different from the existing results based on reinforcement learning, the tracking error constraints are considered and new critic functions are constructed to improve the performance further. To ensure that the tracking errors keep within the predefined time-varying boundaries, a tracking error transformation technique is used to constitute an augmented error system. Specific critic functions, rather than the long-term cost function, are introduced to supervise the tracking performance and tune the weights of the AC neural networks (NNs). A novel adaptive controller with a special structure is designed to reduce the effect of the NN reconstruction errors, input quantization, and disturbances. Based on the Lyapunov stability theory, the boundedness of the closed-loop signals and the desired tracking performance can be guaranteed. Finally, simulations on two connected inverted pendulums are given to illustrate the effectiveness of the proposed method.

Multivariable Super Twisting Based Robust Trajectory Tracking Control for Small Unmanned Helicopter

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Xing Fang

2015-01-01

Full Text Available This paper presents a highly robust trajectory tracking controller for small unmanned helicopter with model uncertainties and external disturbances. First, a simplified dynamic model is developed, where the model uncertainties and external disturbances are treated as compounded disturbances. Then the system is divided into three interconnected subsystems: altitude subsystem, yaw subsystem, and horizontal subsystem. Second, a disturbance observer based controller (DOBC is designed based upon backstepping and multivariable super twisting control algorithm to obtain robust trajectory tracking property. A sliding mode observer works as an estimator of the compounded disturbances. In order to lessen calculative burden, a first-order exact differentiator is employed to estimate the time derivative of the virtual control. Moreover, proof of the stability of the closed-loop system based on Lyapunov method is given. Finally, simulation results are presented to illustrate the effectiveness and robustness of the proposed flight control scheme.

Determination Of Adaptive Control Parameter Using Fuzzy Logic Controller

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Omur Can Ozguney

2017-08-01

Full Text Available The robot industry has developed along with the increasing the use of robots in industry. This has led to increase the studies on robots. The most important part of these studies is that the robots must be work with minimum tracking trajectory error. But it is not easy for robots to track the desired trajectory because of the external disturbances and parametric uncertainty. Therefore adaptive and robust controllers are used to decrease tracking error. The aim of this study is to increase the tracking performance of the robot and minimize the trajectory tracking error. For this purpose adaptive control law for robot manipulator is identified and fuzzy logic controller is applied to find the accurate values for adaptive control parameter. Based on the Lyapunov theory stability of the uncertain system is guaranteed. In this study robot parameters are assumed to be unknown. This controller is applied to a robot model and the results of simulations are given. Controller with fuzzy logic and without fuzzy logic are compared with each other. Simulation results show that the fuzzy logic controller has improved the results.

Back-tracking of primary particle trajectories for muons detected at the Earth surface

Science.gov (United States)

Shutenko, V. V.

2017-01-01

Investigations of cosmic rays on the surface of the Earth allow to derive information of applied character on the conditions of the interplanetary magnetic field and of the geomagnetic field. For this purpose, it is necessary to collate trajectories of particles detected in the ground-based detector to trajectories of primary cosmic rays in the heliosphere. This problem is solved by means of various back-tracking methods. In this work, one of such methods is presented.

Back-tracking of primary particle trajectories for muons detected at the Earth surface

International Nuclear Information System (INIS)

Shutenko, V V

2017-01-01

Investigations of cosmic rays on the surface of the Earth allow to derive information of applied character on the conditions of the interplanetary magnetic field and of the geomagnetic field. For this purpose, it is necessary to collate trajectories of particles detected in the ground-based detector to trajectories of primary cosmic rays in the heliosphere. This problem is solved by means of various back-tracking methods. In this work, one of such methods is presented. (paper)

SU-G-BRA-09: Estimation of Motion Tracking Uncertainty for Real-Time Adaptive Imaging

Energy Technology Data Exchange (ETDEWEB)

Yan, H [Capital Medical University, Beijing, Beijing (China); Chen, Z [Yale New Haven Hospital, New Haven, CT (United States); Nath, R; Liu, W [Yale University School of Medicine, New Haven, CT (United States)

2016-06-15

Purpose: kV fluoroscopic imaging combined with MV treatment beam imaging has been investigated for intrafractional motion monitoring and correction. It is, however, subject to additional kV imaging dose to normal tissue. To balance tracking accuracy and imaging dose, we previously proposed an adaptive imaging strategy to dynamically decide future imaging type and moments based on motion tracking uncertainty. kV imaging may be used continuously for maximal accuracy or only when the position uncertainty (probability of out of threshold) is high if a preset imaging dose limit is considered. In this work, we propose more accurate methods to estimate tracking uncertainty through analyzing acquired data in real-time. Methods: We simulated motion tracking process based on a previously developed imaging framework (MV + initial seconds of kV imaging) using real-time breathing data from 42 patients. Motion tracking errors for each time point were collected together with the time point’s corresponding features, such as tumor motion speed and 2D tracking error of previous time points, etc. We tested three methods for error uncertainty estimation based on the features: conditional probability distribution, logistic regression modeling, and support vector machine (SVM) classification to detect errors exceeding a threshold. Results: For conditional probability distribution, polynomial regressions on three features (previous tracking error, prediction quality, and cosine of the angle between the trajectory and the treatment beam) showed strong correlation with the variation (uncertainty) of the mean 3D tracking error and its standard deviation: R-square = 0.94 and 0.90, respectively. The logistic regression and SVM classification successfully identified about 95% of tracking errors exceeding 2.5mm threshold. Conclusion: The proposed methods can reliably estimate the motion tracking uncertainty in real-time, which can be used to guide adaptive additional imaging to confirm the

SU-G-BRA-09: Estimation of Motion Tracking Uncertainty for Real-Time Adaptive Imaging

International Nuclear Information System (INIS)

Yan, H; Chen, Z; Nath, R; Liu, W

2016-01-01

Purpose: kV fluoroscopic imaging combined with MV treatment beam imaging has been investigated for intrafractional motion monitoring and correction. It is, however, subject to additional kV imaging dose to normal tissue. To balance tracking accuracy and imaging dose, we previously proposed an adaptive imaging strategy to dynamically decide future imaging type and moments based on motion tracking uncertainty. kV imaging may be used continuously for maximal accuracy or only when the position uncertainty (probability of out of threshold) is high if a preset imaging dose limit is considered. In this work, we propose more accurate methods to estimate tracking uncertainty through analyzing acquired data in real-time. Methods: We simulated motion tracking process based on a previously developed imaging framework (MV + initial seconds of kV imaging) using real-time breathing data from 42 patients. Motion tracking errors for each time point were collected together with the time point’s corresponding features, such as tumor motion speed and 2D tracking error of previous time points, etc. We tested three methods for error uncertainty estimation based on the features: conditional probability distribution, logistic regression modeling, and support vector machine (SVM) classification to detect errors exceeding a threshold. Results: For conditional probability distribution, polynomial regressions on three features (previous tracking error, prediction quality, and cosine of the angle between the trajectory and the treatment beam) showed strong correlation with the variation (uncertainty) of the mean 3D tracking error and its standard deviation: R-square = 0.94 and 0.90, respectively. The logistic regression and SVM classification successfully identified about 95% of tracking errors exceeding 2.5mm threshold. Conclusion: The proposed methods can reliably estimate the motion tracking uncertainty in real-time, which can be used to guide adaptive additional imaging to confirm the

Master-slave control with trajectory planning and Bouc-Wen model for tracking control of piezo-driven stage

Science.gov (United States)

Lu, Xiaojun; Liu, Changli; Chen, Lei

2018-04-01

In this paper, a redundant Piezo-driven stage having 3RRR compliant mechanism is introduced, we propose the master-slave control with trajectory planning (MSCTP) strategy and Bouc-Wen model to improve its micro-motion tracking performance. The advantage of the proposed controller lies in that its implementation only requires a simple control strategy without the complexity of modeling to avoid the master PEA's tracking error. The dynamic model of slave PEA system with Bouc-Wen hysteresis is established and identified via particle swarm optimization (PSO) approach. The Piezo-driven stage with operating period T=1s and 2s is implemented to track a prescribed circle. The simulation results show that MSCTP with Bouc-Wen model reduces the trajectory tracking errors to the range of the accuracy of our available measurement.

Adaptive Square-Shaped Trajectory-Based Service Location Protocol in Wireless Sensor Networks

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Hwa-Jung Lim

2010-04-01

Full Text Available In this paper we propose an adaptive square-shaped trajectory (ASST-based service location method to ensure load scalability in wireless sensor networks. This first establishes a square-shaped trajectory over the nodes that surround a target point computed by the hash function and any user can access it, using the hash. Both the width and the size of the trajectory are dynamically adjustable, depending on the number of queries made to the service information on the trajectory. The number of sensor nodes on the trajectory varies in proportion to the changing trajectory shape, allowing high loads to be distributed around the hot spot area.

A model predictive control approach combined unscented Kalman filter vehicle state estimation in intelligent vehicle trajectory tracking

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Hongxiao Yu

2015-05-01

Full Text Available Trajectory tracking and state estimation are significant in the motion planning and intelligent vehicle control. This article focuses on the model predictive control approach for the trajectory tracking of the intelligent vehicles and state estimation of the nonlinear vehicle system. The constraints of the system states are considered when applying the model predictive control method to the practical problem, while 4-degree-of-freedom vehicle model and unscented Kalman filter are proposed to estimate the vehicle states. The estimated states of the vehicle are used to provide model predictive control with real-time control and judge vehicle stability. Furthermore, in order to decrease the cost of solving the nonlinear optimization, the linear time-varying model predictive control is used at each time step. The effectiveness of the proposed vehicle state estimation and model predictive control method is tested by driving simulator. The results of simulations and experiments show that great and robust performance is achieved for trajectory tracking and state estimation in different scenarios.

Mobile Robot Based on the Selection of Fuzzy Behaviours for following Trajectories in Crops

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Claudio Urrea

2016-06-01

Full Text Available This article addresses the problem of trajectory tracking in crops by a weed sprayer mobile robot (WSMR. This problem arises because to fumigate, the robot must follow a predefined path and avoid any obstacles it may encounter. To achieve both trajectory tracking and obstacle avoidance, a control scheme based on different behaviours is proposed, which consists essentially of an adaptive controller with a reference model for trajectory tracking and a fuzzy reactive for obstacle avoidance. Each of these controllers is executed according to the selection of the fuzzy behaviour controller, which uses information delivered by anti-collision sensors located on the robot. As a result of the implementation of this behaviour-based architecture and by means of computer simulations and experimental laboratory tests, the WSMR demonstrates the capability of autonomously following a desired trajectory between the rows of a crop in the presence of obstacles. The results are evaluated by taking into account trajectory tracking curves and the operating requirements of each controller, as well as the application of different errors indices for quantitatively evaluating the proposed control scheme.

Adaptive Colour Feature Identification in Image for Object Tracking

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Feng Su

2012-01-01

Full Text Available Identification and tracking of a moving object using computer vision techniques is important in robotic surveillance. In this paper, an adaptive colour filtering method is introduced for identifying and tracking a moving object appearing in image sequences. This filter is capable of automatically identifying the most salient colour feature of the moving object in the image and using this for a robot to track the object. The method enables the selected colour feature to adapt to surrounding condition when it is changed. A method of determining the region of interest of the moving target is also developed for the adaptive colour filter to extract colour information. Experimental results show that by using a camera mounted on a robot, the proposed methods can perform robustly in tracking a randomly moving object using adaptively selected colour features in a crowded environment.

Decentralized adaptive control of manipulators - Theory, simulation, and experimentation

Science.gov (United States)

Seraji, Homayoun

1989-01-01

The author presents a simple decentralized adaptive-control scheme for multijoint robot manipulators based on the independent joint control concept. The control objective is to achieve accurate tracking of desired joint trajectories. The proposed control scheme does not use the complex manipulator dynamic model, and each joint is controlled simply by a PID (proportional-integral-derivative) feedback controller and a position-velocity-acceleration feedforward controller, both with adjustable gains. Simulation results are given for a two-link direct-drive manipulator under adaptive independent joint control. The results illustrate trajectory tracking under coupled dynamics and varying payload. The proposed scheme is implemented on a MicroVAX II computer for motion control of the three major joints of a PUMA 560 arm. Experimental results are presented to demonstrate that trajectory tracking is achieved despite coupled nonlinear joint dynamics.

An Improved Backstepping-Based Controller for Three-Dimensional Trajectory Tracking of a Midwater Trawl System

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Zhao Yan

2016-01-01

Full Text Available An improved backstepping control method for three-dimensional trajectory tracking of a midwater trawl system is investigated. A new mathematical model of the trawl system while considering the horizontal expansion effect of two otter boards is presented based on the Newton Euler method. Subsequently, an active path tracking strategy of the trawl system based on the backstepping method is proposed. The nonstrict feedback characteristic of the proposed model employs a control allocation method and several parallel nonlinear PID (Proportion Integration Differentiation controllers to eliminate the high-order state variables. Then, the stability analysis by the Lyapunov Stability Theory shows that the proposed controller can maintain the stability of the trawl system even with the presence of external disturbances. To validate the proposed controller, a simulation comparison with a linear PID controller was conducted. The simulation results illustrate that the improved backstepping controller is effective for three-dimensional trajectory tracking of the midwater trawl system.

Dynamic modelling and adaptive robust tracking control of a space robot with two-link flexible manipulators under unknown disturbances

Science.gov (United States)

Yang, Xinxin; Ge, Shuzhi Sam; He, Wei

2018-04-01

In this paper, both the closed-form dynamics and adaptive robust tracking control of a space robot with two-link flexible manipulators under unknown disturbances are developed. The dynamic model of the system is described with assumed modes approach and Lagrangian method. The flexible manipulators are represented as Euler-Bernoulli beams. Based on singular perturbation technique, the displacements/joint angles and flexible modes are modelled as slow and fast variables, respectively. A sliding mode control is designed for trajectories tracking of the slow subsystem under unknown but bounded disturbances, and an adaptive sliding mode control is derived for slow subsystem under unknown slowly time-varying disturbances. An optimal linear quadratic regulator method is proposed for the fast subsystem to damp out the vibrations of the flexible manipulators. Theoretical analysis validates the stability of the proposed composite controller. Numerical simulation results demonstrate the performance of the closed-loop flexible space robot system.

Differences in context and feedback result in different trajectories and adaptation strategies in reaching.

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Fritzie Arce

Full Text Available Computational models of motor control have often explained the straightness of horizontal planar reaching movements as a consequence of optimal control. Departure from rectilinearity is thus regarded as sub-optimal. Here we examine if subjects may instead select to make curved trajectories following adaptation to force fields and visuomotor rotations. Separate subjects adapted to force fields with or without visual feedback of their hand trajectory and were retested after 24 hours. Following adaptation, comparable accuracies were achieved in two ways: with visual feedback, adapted trajectories in force fields were straight whereas without it, they remained curved. The results suggest that trajectory shape is not always straight, but is also influenced by the calibration of available feedback signals for the state estimation required by the task. In a follow-up experiment, where additional subjects learned a visuomotor rotation immediately after force field, the trajectories learned in force fields (straight or curved were transferred when directions of the perturbations were similar but not when directions were opposing. This demonstrates a strong bias by prior experience to keep using a recently acquired control policy that continues to produce successful performance inspite of differences in tasks and feedback conditions. On relearning of force fields on the second day, facilitation by intervening visuomotor rotations occurred only when required motor adjustments and calibration of feedback signals were similar in both tasks. These results suggest that both the available feedback signals and prior history of learning influence the choice and maintenance of control policy during adaptations.

A discrete-time adaptive control scheme for robot manipulators

Science.gov (United States)

Tarokh, M.

1990-01-01

A discrete-time model reference adaptive control scheme is developed for trajectory tracking of robot manipulators. The scheme utilizes feedback, feedforward, and auxiliary signals, obtained from joint angle measurement through simple expressions. Hyperstability theory is utilized to derive the adaptation laws for the controller gain matrices. It is shown that trajectory tracking is achieved despite gross robot parameter variation and uncertainties. The method offers considerable design flexibility and enables the designer to improve the performance of the control system by adjusting free design parameters. The discrete-time adaptation algorithm is extremely simple and is therefore suitable for real-time implementation. Simulations and experimental results are given to demonstrate the performance of the scheme.

Modeling and Robust Trajectory Tracking Control for a Novel Six-Rotor Unmanned Aerial Vehicle

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Chengshun Yang

2013-01-01

Full Text Available Modeling and trajectory tracking control of a novel six-rotor unmanned aerial vehicle (UAV is concerned to solve problems such as smaller payload capacity and lack of both hardware redundancy and anticrosswind capability for quad-rotor. The mathematical modeling for the six-rotor UAV is developed on the basis of the Newton-Euler formalism, and a second-order sliding-mode disturbance observer (SOSMDO is proposed to reconstruct the disturbances of the rotational dynamics. In consideration of the under-actuated and strong coupling properties of the six-rotor UAV, a nested double loops trajectory tracking control strategy is adopted. In the outer loop, a position error PID controller is designed, of which the task is to compare the desired trajectory with real position of the six-rotor UAV and export the desired attitude angles to the inner loop. In the inner loop, a rapid-convergent nonlinear differentiator (RCND is proposed to calculate the derivatives of the virtual control signal, instead of using the analytical differentiation, to avoid “differential expansion” in the procedure of the attitude controller design. Finally, the validity and effectiveness of the proposed technique are demonstrated by the simulation results.

M-Track: A New Software for Automated Detection of Grooming Trajectories in Mice.

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Sheldon L Reeves

2016-09-01

Full Text Available Grooming is a complex and robust innate behavior, commonly performed by most vertebrate species. In mice, grooming consists of a series of stereotyped patterned strokes, performed along the rostro-caudal axis of the body. The frequency and duration of each grooming episode is sensitive to changes in stress levels, social interactions and pharmacological manipulations, and is therefore used in behavioral studies to gain insights into the function of brain regions that control movement execution and anxiety. Traditional approaches to analyze grooming rely on manually scoring the time of onset and duration of each grooming episode, and are often performed on grooming episodes triggered by stress exposure, which may not be entirely representative of spontaneous grooming in freely-behaving mice. This type of analysis is time-consuming and provides limited information about finer aspects of grooming behaviors, which are important to understand movement stereotypy and bilateral coordination in mice. Currently available commercial and freeware video-tracking software allow automated tracking of the whole body of a mouse or of its head and tail, not of individual forepaws. Here we describe a simple experimental set-up and a novel open-source code, named M-Track, for simultaneously tracking the movement of individual forepaws during spontaneous grooming in multiple freely-behaving mice. This toolbox provides a simple platform to perform trajectory analysis of forepaw movement during distinct grooming episodes. By using M-track we show that, in C57BL/6 wild type mice, the speed and bilateral coordination of the left and right forepaws remain unaltered during the execution of distinct grooming episodes. Stress exposure induces a profound increase in the length of the forepaw grooming trajectories. M-Track provides a valuable and user-friendly interface to streamline the analysis of spontaneous grooming in biomedical research studies.

M-Track: A New Software for Automated Detection of Grooming Trajectories in Mice.

Science.gov (United States)

Reeves, Sheldon L; Fleming, Kelsey E; Zhang, Lin; Scimemi, Annalisa

2016-09-01

Grooming is a complex and robust innate behavior, commonly performed by most vertebrate species. In mice, grooming consists of a series of stereotyped patterned strokes, performed along the rostro-caudal axis of the body. The frequency and duration of each grooming episode is sensitive to changes in stress levels, social interactions and pharmacological manipulations, and is therefore used in behavioral studies to gain insights into the function of brain regions that control movement execution and anxiety. Traditional approaches to analyze grooming rely on manually scoring the time of onset and duration of each grooming episode, and are often performed on grooming episodes triggered by stress exposure, which may not be entirely representative of spontaneous grooming in freely-behaving mice. This type of analysis is time-consuming and provides limited information about finer aspects of grooming behaviors, which are important to understand movement stereotypy and bilateral coordination in mice. Currently available commercial and freeware video-tracking software allow automated tracking of the whole body of a mouse or of its head and tail, not of individual forepaws. Here we describe a simple experimental set-up and a novel open-source code, named M-Track, for simultaneously tracking the movement of individual forepaws during spontaneous grooming in multiple freely-behaving mice. This toolbox provides a simple platform to perform trajectory analysis of forepaw movement during distinct grooming episodes. By using M-track we show that, in C57BL/6 wild type mice, the speed and bilateral coordination of the left and right forepaws remain unaltered during the execution of distinct grooming episodes. Stress exposure induces a profound increase in the length of the forepaw grooming trajectories. M-Track provides a valuable and user-friendly interface to streamline the analysis of spontaneous grooming in biomedical research studies.

Adaptive and accelerated tracking-learning-detection

Science.gov (United States)

Guo, Pengyu; Li, Xin; Ding, Shaowen; Tian, Zunhua; Zhang, Xiaohu

2013-08-01

An improved online long-term visual tracking algorithm, named adaptive and accelerated TLD (AA-TLD) based on Tracking-Learning-Detection (TLD) which is a novel tracking framework has been introduced in this paper. The improvement focuses on two aspects, one is adaption, which makes the algorithm not dependent on the pre-defined scanning grids by online generating scale space, and the other is efficiency, which uses not only algorithm-level acceleration like scale prediction that employs auto-regression and moving average (ARMA) model to learn the object motion to lessen the detector's searching range and the fixed number of positive and negative samples that ensures a constant retrieving time, but also CPU and GPU parallel technology to achieve hardware acceleration. In addition, in order to obtain a better effect, some TLD's details are redesigned, which uses a weight including both normalized correlation coefficient and scale size to integrate results, and adjusts distance metric thresholds online. A contrastive experiment on success rate, center location error and execution time, is carried out to show a performance and efficiency upgrade over state-of-the-art TLD with partial TLD datasets and Shenzhou IX return capsule image sequences. The algorithm can be used in the field of video surveillance to meet the need of real-time video tracking.

Distributed finite-time trajectory tracking control for multiple nonholonomic mobile robots with uncertainties and external disturbances

Science.gov (United States)

Ou, Meiying; Sun, Haibin; Gu, Shengwei; Zhang, Yangyi

2017-11-01

This paper investigates the distributed finite-time trajectory tracking control for a group of nonholonomic mobile robots with time-varying unknown parameters and external disturbances. At first, the tracking error system is derived for each mobile robot with the aid of a global invertible transformation, which consists of two subsystems, one is a first-order subsystem and another is a second-order subsystem. Then, the two subsystems are studied respectively, and finite-time disturbance observers are proposed for each robot to estimate the external disturbances. Meanwhile, distributed finite-time tracking controllers are developed for each mobile robot such that all states of each robot can reach the desired value in finite time, where the desired reference value is assumed to be the trajectory of a virtual leader whose information is available to only a subset of the followers, and the followers are assumed to have only local interaction. The effectiveness of the theoretical results is finally illustrated by numerical simulations.

Strong tracking adaptive Kalman filters for underwater vehicle dead reckoning

Institute of Scientific and Technical Information of China (English)

XIAO Kun; FANG Shao-ji; PANG Yong-jie

2007-01-01

To improve underwater vehicle dead reckoning, a developed strong tracking adaptive kalman filter is proposed. The filter is improved with an additional adaptive factor and an estimator of measurement noise covariance. Since the magnitude of fading factor is changed adaptively, the tracking ability of the filter is still enhanced in low velocity condition of underwater vehicles. The results of simulation tests prove the presented filter effective.

Study on Oil Pressure Characteristics and Trajectory Tracking Control in Shift Process of Wet-Clutch for Electric Vehicles

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Junqiu Li

2016-01-01

Full Text Available Accurate control of oil pressure of wet-clutch is of great importance for improving shift quality. Based on dynamic models of two-gear planetary transmission and hydraulic control system, a trajectory tracking model of oil pressure was built by sliding mode control method. An experiment was designed to verify the validity of hydraulic control system, through which the relationship between duty cycle of on-off valve and oil pressure of clutch was determined. The tracking effect was analyzed by simulation. Results showed that oil pressure could follow well the optimal trajectory and the shift quality was effectively improved.

Adaptive-Repetitive Visual-Servo Control of Low-Flying Aerial Robots via Uncalibrated High-Flying Cameras

Science.gov (United States)

Guo, Dejun; Bourne, Joseph R.; Wang, Hesheng; Yim, Woosoon; Leang, Kam K.

2017-08-01

This paper presents the design and implementation of an adaptive-repetitive visual-servo control system for a moving high-flying vehicle (HFV) with an uncalibrated camera to monitor, track, and precisely control the movements of a low-flying vehicle (LFV) or mobile ground robot. Applications of this control strategy include the use of high-flying unmanned aerial vehicles (UAVs) with computer vision for monitoring, controlling, and coordinating the movements of lower altitude agents in areas, for example, where GPS signals may be unreliable or nonexistent. When deployed, a remote operator of the HFV defines the desired trajectory for the LFV in the HFV's camera frame. Due to the circular motion of the HFV, the resulting motion trajectory of the LFV in the image frame can be periodic in time, thus an adaptive-repetitive control system is exploited for regulation and/or trajectory tracking. The adaptive control law is able to handle uncertainties in the camera's intrinsic and extrinsic parameters. The design and stability analysis of the closed-loop control system is presented, where Lyapunov stability is shown. Simulation and experimental results are presented to demonstrate the effectiveness of the method for controlling the movement of a low-flying quadcopter, demonstrating the capabilities of the visual-servo control system for localization (i.e.,, motion capturing) and trajectory tracking control. In fact, results show that the LFV can be commanded to hover in place as well as track a user-defined flower-shaped closed trajectory, while the HFV and camera system circulates above with constant angular velocity. On average, the proposed adaptive-repetitive visual-servo control system reduces the average RMS tracking error by over 77% in the image plane and over 71% in the world frame compared to using just the adaptive visual-servo control law.

Track and vertex reconstruction: From classical to adaptive methods

International Nuclear Information System (INIS)

Strandlie, Are; Fruehwirth, Rudolf

2010-01-01

This paper reviews classical and adaptive methods of track and vertex reconstruction in particle physics experiments. Adaptive methods have been developed to meet the experimental challenges at high-energy colliders, in particular, the CERN Large Hadron Collider. They can be characterized by the obliteration of the traditional boundaries between pattern recognition and statistical estimation, by the competition between different hypotheses about what constitutes a track or a vertex, and by a high level of flexibility and robustness achieved with a minimum of assumptions about the data. The theoretical background of some of the adaptive methods is described, and it is shown that there is a close connection between the two main branches of adaptive methods: neural networks and deformable templates, on the one hand, and robust stochastic filters with annealing, on the other hand. As both classical and adaptive methods of track and vertex reconstruction presuppose precise knowledge of the positions of the sensitive detector elements, the paper includes an overview of detector alignment methods and a survey of the alignment strategies employed by past and current experiments.

Parking Space Detection and Trajectory Tracking Control for Vehicle Auto-Parking

OpenAIRE

Shiuh-Jer Huang; Yu-Sheng Hsu

2017-01-01

On-board available parking space detecting system, parking trajectory planning and tracking control mechanism are the key components of vehicle backward auto-parking system. Firstly, pair of ultrasonic sensors is installed on each side of vehicle body surface to detect the relative distance between ego-car and surrounding obstacle. The dimension of a found empty space can be calculated based on vehicle speed and the time history of ultrasonic sensor detecting information. This result can be u...

A new approach to adaptive control of manipulators

Science.gov (United States)

Seraji, H.

1987-01-01

An approach in which the manipulator inverse is used as a feedforward controller is employed in the adaptive control of manipulators in order to achieve trajectory tracking by the joint angles. The desired trajectory is applied as an input to the feedforward controller, and the controller output is used as the driving torque for the manipulator. An adaptive algorithm obtained from MRAC theory is used to update the controller gains to cope with variations in the manipulator inverse due to changes of the operating point. An adaptive feedback controller and an auxiliary signal enhance closed-loop stability and achieve faster adaptation. Simulation results demonstrate the effectiveness of the proposed control scheme for different reference trajectories, and despite large variations in the payload.

Adaptive Mesh Iteration Method for Trajectory Optimization Based on Hermite-Pseudospectral Direct Transcription

Directory of Open Access Journals (Sweden)

Humin Lei

2017-01-01

Full Text Available An adaptive mesh iteration method based on Hermite-Pseudospectral is described for trajectory optimization. The method uses the Legendre-Gauss-Lobatto points as interpolation points; then the state equations are approximated by Hermite interpolating polynomials. The method allows for changes in both number of mesh points and the number of mesh intervals and produces significantly smaller mesh sizes with a higher accuracy tolerance solution. The derived relative error estimate is then used to trade the number of mesh points with the number of mesh intervals. The adaptive mesh iteration method is applied successfully to the examples of trajectory optimization of Maneuverable Reentry Research Vehicle, and the simulation experiment results show that the adaptive mesh iteration method has many advantages.

Probabilistic Tracking and Trajectory Planning for Autonomous Ground Vehicles in Urban Environments

Science.gov (United States)

2016-03-05

Vehicles in Urban Environments The views, opinions and/or findings contained in this report are those of the author(s) and should not contrued as an...Pine Tree Road Ithaca, NY 14850 -2820 ABSTRACT Probabilistic Tracking and Trajectory Planning for Autonomous Ground Vehicles in Urban Environments...Probabilistic Anticipation for Autonomous Robots in Urban Environments, IEEE Transactions on Robotics, (04 2014): 0. doi: 10.1109/TRO.2013.2291620 Isaac

Optimizing Likelihood Models for Particle Trajectory Segmentation in Multi-State Systems.

Science.gov (United States)

Young, Dylan Christopher; Scrimgeour, Jan

2018-06-19

Particle tracking offers significant insight into the molecular mechanics that govern the behav- ior of living cells. The analysis of molecular trajectories that transition between different motive states, such as diffusive, driven and tethered modes, is of considerable importance, with even single trajectories containing significant amounts of information about a molecule's environment and its interactions with cellular structures. Hidden Markov models (HMM) have been widely adopted to perform the segmentation of such complex tracks. In this paper, we show that extensive analysis of hidden Markov model outputs using data derived from multi-state Brownian dynamics simulations can be used both for the optimization of the likelihood models used to describe the states of the system and for characterization of the technique's failure mechanisms. This analysis was made pos- sible by the implementation of parallelized adaptive direct search algorithm on a Nvidia graphics processing unit. This approach provides critical information for the visualization of HMM failure and successful design of particle tracking experiments where trajectories contain multiple mobile states. © 2018 IOP Publishing Ltd.

Adaptive Tracking Control of an Electro-Pneumatic Clutch Actuator

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Glenn-Ole Kaasa

2003-10-01

Full Text Available This paper deals with the application of a simple adaptive algorithm for robust tracking control of an electro-pneumatic clutch actuator with output feedback. We present a mathematical model of the strongly nonlinear system, and implement an adaptive algorithm, based on a parallel feedforward compensator (PFC to remove the relative-degree-1 restriction. We propose a practical method of constructing the PFC, and introduce a simple modification that removes an inherent restriction on bandwidth of the nonlinear system. We show that the adaptive algorithm deals well with nonlinearities, and we achieve tracking corresponding to a settling-time of 150 ms.

Long-lasting amelioration of walking trajectory in neglect after prismatic adaptation

Directory of Open Access Journals (Sweden)

Marco eRabuffetti

2013-07-01

Full Text Available In the present investigation we explored the effect of prismatic adaptation (PA applied to the upper right limb on the walking trajectory of a neglect patient with more severe neglect in far than in near space. The patient was asked to bisect a line fixed to the floor by walking across it before and after four sessions of PA distributed over a time frame of 67 days. Gait path was analysed by means of an optoelectronic motion analysis system.The walking trajectory improved following PA and the result was maintained at follow-up, fifteen months after treatment. The improvement was greater for the predicted bisection error (estimated on the basis of the trajectory extrapolated from the first walking step then for the observed bisection error (measured at line crossing.These results show that PA may act on high level spatial representation of gait trajectory rather than on lower level sensory-motor gait components and suggest that PA may have a long lasting rehabilitative effect on neglect patients showing a deviated walking trajectory.

Fuzzy adaptive robust control for space robot considering the effect of the gravity

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Qin Li

2014-12-01

Full Text Available Space robot is assembled and tested in gravity environment, and completes on-orbit service (OOS in microgravity environment. The kinematic and dynamic characteristic of the robot will change with the variations of gravity in different working condition. Fully considering the change of kinematic and dynamic models caused by the change of gravity environment, a fuzzy adaptive robust control (FARC strategy which is adaptive to these model variations is put forward for trajectory tracking control of space robot. A fuzzy algorithm is employed to approximate the nonlinear uncertainties in the model, adaptive laws of the parameters are constructed, and the approximation error is compensated by using a robust control algorithm. The stability of the control system is guaranteed based on the Lyapunov theory and the trajectory tracking control simulation is performed. The simulation results are compared with the proportional plus derivative (PD controller, and the effectiveness to achieve better trajectory tracking performance under different gravity environment without changing the control parameters and the advantage of the proposed controller are verified.

ADAPTIVE BACKGROUND DENGAN METODE GAUSSIAN MIXTURE MODELS UNTUK REAL-TIME TRACKING

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Silvia Rostianingsih

2008-01-01

Full Text Available Nowadays, motion tracking application is widely used for many purposes, such as detecting traffic jam and counting how many people enter a supermarket or a mall. A method to separate background and the tracked object is required for motion tracking. It will not be hard to develop the application if the tracking is performed on a static background, but it will be difficult if the tracked object is at a place with a non-static background, because the changing part of the background can be recognized as a tracking area. In order to handle the problem an application can be made to separate background where that separation can adapt to change that occur. This application is made to produce adaptive background using Gaussian Mixture Models (GMM as its method. GMM method clustered the input pixel data with pixel color value as it’s basic. After the cluster formed, dominant distributions are choosen as background distributions. This application is made by using Microsoft Visual C 6.0. The result of this research shows that GMM algorithm could made adaptive background satisfactory. This proofed by the result of the tests that succeed at all condition given. This application can be developed so the tracking process integrated in adaptive background maker process. Abstract in Bahasa Indonesia : Saat ini, aplikasi motion tracking digunakan secara luas untuk banyak tujuan, seperti mendeteksi kemacetan dan menghitung berapa banyak orang yang masuk ke sebuah supermarket atau sebuah mall. Sebuah metode untuk memisahkan antara background dan obyek yang di-track dibutuhkan untuk melakukan motion tracking. Membuat aplikasi tracking pada background yang statis bukanlah hal yang sulit, namun apabila tracking dilakukan pada background yang tidak statis akan lebih sulit, dikarenakan perubahan background dapat dikenali sebagai area tracking. Untuk mengatasi masalah tersebut, dapat dibuat suatu aplikasi untuk memisahkan background dimana aplikasi tersebut dapat

Trajectory Control of Rendezvous with Maneuver Target Spacecraft

Science.gov (United States)

Zhou, Zhinqiang

2012-01-01

In this paper, a nonlinear trajectory control algorithm of rendezvous with maneuvering target spacecraft is presented. The disturbance forces on the chaser and target spacecraft and the thrust forces on the chaser spacecraft are considered in the analysis. The control algorithm developed in this paper uses the relative distance and relative velocity between the target and chaser spacecraft as the inputs. A general formula of reference relative trajectory of the chaser spacecraft to the target spacecraft is developed and applied to four different proximity maneuvers, which are in-track circling, cross-track circling, in-track spiral rendezvous and cross-track spiral rendezvous. The closed-loop differential equations of the proximity relative motion with the control algorithm are derived. It is proven in the paper that the tracking errors between the commanded relative trajectory and the actual relative trajectory are bounded within a constant region determined by the control gains. The prediction of the tracking errors is obtained. Design examples are provided to show the implementation of the control algorithm. The simulation results show that the actual relative trajectory tracks the commanded relative trajectory tightly. The predicted tracking errors match those calculated in the simulation results. The control algorithm developed in this paper can also be applied to interception of maneuver target spacecraft and relative trajectory control of spacecraft formation flying.

Adaptive tracking for pneumatic muscle actuators in bicep and tricep configurations.

Science.gov (United States)

Lilly, John H

2003-09-01

Adaptive tracking techniques are applied to pneumatic muscle actuators arranged in bicep and tricep configurations. The control objective is to force the joint angle to track a specified reference path. Mathematical models are derived for the bicep and tricep configurations. The models are nonlinear and in general time-varying, making adaptive control desirable. Stability results are derived, and the results of simulation studies are presented, contrasting the nonlinear adaptive control to a nonadaptive PID control approach.

Adaptive Robot Control – An Experimental Comparison

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Francesco Alonge

2012-11-01

Full Text Available This paper deals with experimental comparison between stable adaptive controllers of robotic manipulators based on Model Based Adaptive, Neural Network and Wavelet -Based control. The above control methods were compared with each other in terms of computational efficiency, need for accurate mathematical model of the manipulator and tracking performances. An original management algorithm of the Wavelet Network control scheme has been designed, with the aim of constructing the net automatically during the trajectory tracking, without the need to tune it to the trajectory itself. Experimental tests, carried out on a planar two link manipulator, show that the Wavelet-Based control scheme, with the new management algorithm, outperforms the conventional Model-Based schemes in the presence of structural uncertainties in the mathematical model of the robot, without pre-training and more efficiently than the Neural Network approach.

Singularity-Free Neural Control for the Exponential Trajectory Tracking in Multiple-Input Uncertain Systems with Unknown Deadzone Nonlinearities

Directory of Open Access Journals (Sweden)

J. Humberto Pérez-Cruz

2014-01-01

Full Text Available The trajectory tracking for a class of uncertain nonlinear systems in which the number of possible states is equal to the number of inputs and each input is preceded by an unknown symmetric deadzone is considered. The unknown dynamics is identified by means of a continuous time recurrent neural network in which the control singularity is conveniently avoided by guaranteeing the invertibility of the coupling matrix. Given this neural network-based mathematical model of the uncertain system, a singularity-free feedback linearization control law is developed in order to compel the system state to follow a reference trajectory. By means of Lyapunov-like analysis, the exponential convergence of the tracking error to a bounded zone can be proven. Likewise, the boundedness of all closed-loop signals can be guaranteed.

A Dynamic and Adaptive Selection Radar Tracking Method Based on Information Entropy

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Ge Jianjun

2017-12-01

Full Text Available Nowadays, the battlefield environment has become much more complex and variable. This paper presents a quantitative method and lower bound for the amount of target information acquired from multiple radar observations to adaptively and dynamically organize the detection of battlefield resources based on the principle of information entropy. Furthermore, for minimizing the given information entropy’s lower bound for target measurement at every moment, a method to dynamically and adaptively select radars with a high amount of information for target tracking is proposed. The simulation results indicate that the proposed method has higher tracking accuracy than that of tracking without adaptive radar selection based on entropy.

Adaptive control of robotic manipulators

Science.gov (United States)

Seraji, H.

1987-01-01

The author presents a novel approach to adaptive control of manipulators to achieve trajectory tracking by the joint angles. The central concept in this approach is the utilization of the manipulator inverse as a feedforward controller. The desired trajectory is applied as an input to the feedforward controller which behaves as the inverse of the manipulator at any operating point; the controller output is used as the driving torque for the manipulator. The controller gains are then updated by an adaptation algorithm derived from MRAC (model reference adaptive control) theory to cope with variations in the manipulator inverse due to changes of the operating point. An adaptive feedback controller and an auxiliary signal are also used to enhance closed-loop stability and to achieve faster adaptation. The proposed control scheme is computationally fast and does not require a priori knowledge of the complex dynamic model or the parameter values of the manipulator or the payload.

Adaptive hybrid control of manipulators

Science.gov (United States)

Seraji, H.

1987-01-01

Simple methods for the design of adaptive force and position controllers for robot manipulators within the hybrid control architecuture is presented. The force controller is composed of an adaptive PID feedback controller, an auxiliary signal and a force feedforward term, and it achieves tracking of desired force setpoints in the constraint directions. The position controller consists of adaptive feedback and feedforward controllers and an auxiliary signal, and it accomplishes tracking of desired position trajectories in the free directions. The controllers are capable of compensating for dynamic cross-couplings that exist between the position and force control loops in the hybrid control architecture. The adaptive controllers do not require knowledge of the complex dynamic model or parameter values of the manipulator or the environment. The proposed control schemes are computationally fast and suitable for implementation in on-line control with high sampling rates.

Efficient Dynamic Adaptation Strategies for Object Tracking Tree in Wireless Sensor Network

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CHEN, M.

2012-12-01

Full Text Available Most object tracking trees are established using the predefined mobility profile. However, when the real object's movement behaviors and query rates are different from the predefined mobility profile and query rates, the update cost and query cost of object tracking tree may increase. To upgrade the object tracking tree, the sink needs to send very large messages to collect the real movement information from the network, introducing a very large message overhead, which is referred to as adaptation cost. The Sub Root Message-Tree Adaptive procedure was proposed to dynamically collect the real movement information under the sub-tree and reconstruct the sub-tree to provide good performance based on the collected information. The simulation results indicates that the Sub Root Message-Tree Adaptive procedure is sufficient to achieve good total cost and lower adaptation cost.

Experimental evaluation of feedforward control for the trajectory tracking of power in nuclear reactors

International Nuclear Information System (INIS)

Lau, S.H.; Bernard, J.A.; Lanning, D.D.

1991-01-01

This paper reports on an experimental comparison of feedforward control techniques for the trajectory-tracking of neutronic power was performed on the 5-MWt MIT Research Reactor. Included in the comparison were pure feedforward control in which the actuator signal is found solely by processing a demanded output through a system model, hybrid feedforward/feedback control in which the actuator signal is obtained by summing feedforward and feedback components, and period-generated control in which feedback is used to update the demand trajectory prior to its being processed through the system model for calculation of the actuator signal. This latter approach was found to be the most effective. In addition to the experimental results, discussions are given of both the rationale for model-based, feedforward control and the designs of the various controllers

Adaptive Moving Object Tracking Integrating Neural Networks And Intelligent Processing

Science.gov (United States)

Lee, James S. J.; Nguyen, Dziem D.; Lin, C.

1989-03-01

A real-time adaptive scheme is introduced to detect and track moving objects under noisy, dynamic conditions including moving sensors. This approach integrates the adaptiveness and incremental learning characteristics of neural networks with intelligent reasoning and process control. Spatiotemporal filtering is used to detect and analyze motion, exploiting the speed and accuracy of multiresolution processing. A neural network algorithm constitutes the basic computational structure for classification. A recognition and learning controller guides the on-line training of the network, and invokes pattern recognition to determine processing parameters dynamically and to verify detection results. A tracking controller acts as the central control unit, so that tracking goals direct the over-all system. Performance is benchmarked against the Widrow-Hoff algorithm, for target detection scenarios presented in diverse FLIR image sequences. Efficient algorithm design ensures that this recognition and control scheme, implemented in software and commercially available image processing hardware, meets the real-time requirements of tracking applications.

Scale-adaptive Local Patches for Robust Visual Object Tracking

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Kang Sun

2014-04-01

Full Text Available This paper discusses the problem of robustly tracking objects which undergo rapid and dramatic scale changes. To remove the weakness of global appearance models, we present a novel scheme that combines object’s global and local appearance features. The local feature is a set of local patches that geometrically constrain the changes in the target’s appearance. In order to adapt to the object’s geometric deformation, the local patches could be removed and added online. The addition of these patches is constrained by the global features such as color, texture and motion. The global visual features are updated via the stable local patches during tracking. To deal with scale changes, we adapt the scale of patches in addition to adapting the object bound box. We evaluate our method by comparing it to several state-of-the-art trackers on publicly available datasets. The experimental results on challenging sequences confirm that, by using this scale-adaptive local patches and global properties, our tracker outperforms the related trackers in many cases by having smaller failure rate as well as better accuracy.

Quantum Dynamics with Short-Time Trajectories and Minimal Adaptive Basis Sets.

Science.gov (United States)

Saller, Maximilian A C; Habershon, Scott

2017-07-11

Methods for solving the time-dependent Schrödinger equation via basis set expansion of the wave function can generally be categorized as having either static (time-independent) or dynamic (time-dependent) basis functions. We have recently introduced an alternative simulation approach which represents a middle road between these two extremes, employing dynamic (classical-like) trajectories to create a static basis set of Gaussian wavepackets in regions of phase-space relevant to future propagation of the wave function [J. Chem. Theory Comput., 11, 8 (2015)]. Here, we propose and test a modification of our methodology which aims to reduce the size of basis sets generated in our original scheme. In particular, we employ short-time classical trajectories to continuously generate new basis functions for short-time quantum propagation of the wave function; to avoid the continued growth of the basis set describing the time-dependent wave function, we employ Matching Pursuit to periodically minimize the number of basis functions required to accurately describe the wave function. Overall, this approach generates a basis set which is adapted to evolution of the wave function while also being as small as possible. In applications to challenging benchmark problems, namely a 4-dimensional model of photoexcited pyrazine and three different double-well tunnelling problems, we find that our new scheme enables accurate wave function propagation with basis sets which are around an order-of-magnitude smaller than our original trajectory-guided basis set methodology, highlighting the benefits of adaptive strategies for wave function propagation.

Unveiling adaptation using high-resolution lineage tracking

Science.gov (United States)

Blundell, Jamie; Levy, Sasha; Fisher, Daniel; Petrov, Dmitri; Sherlock, Gavin

2013-03-01

Human diseases such as cancer and microbial infections are adaptive processes inside the human body with enormous population sizes: between 106 -1012 cells. In spite of this our understanding of adaptation in large populations is limited. The key problem is the difficulty in identifying anything more than a handful of rare, large-effect beneficial mutations. The development and use of molecular barcodes allows us to uniquely tag hundreds of thousands of cells and enable us to track tens of thousands of adaptive mutations in large yeast populations. We use this system to test some of the key theories on which our understanding of adaptation in large populations is based. We (i) measure the fitness distribution in an evolving population at different times, (ii) identify when an appreciable fraction of clones in the population have at most a single adaptive mutation and isolate a large number of clones with independent single adaptive mutations, and (iii) use this clone collection to determine the distribution of fitness effects of single beneficial mutations.

Learning-Based Adaptive Optimal Tracking Control of Strict-Feedback Nonlinear Systems.

Science.gov (United States)

Gao, Weinan; Jiang, Zhong-Ping; Weinan Gao; Zhong-Ping Jiang; Gao, Weinan; Jiang, Zhong-Ping

2018-06-01

This paper proposes a novel data-driven control approach to address the problem of adaptive optimal tracking for a class of nonlinear systems taking the strict-feedback form. Adaptive dynamic programming (ADP) and nonlinear output regulation theories are integrated for the first time to compute an adaptive near-optimal tracker without any a priori knowledge of the system dynamics. Fundamentally different from adaptive optimal stabilization problems, the solution to a Hamilton-Jacobi-Bellman (HJB) equation, not necessarily a positive definite function, cannot be approximated through the existing iterative methods. This paper proposes a novel policy iteration technique for solving positive semidefinite HJB equations with rigorous convergence analysis. A two-phase data-driven learning method is developed and implemented online by ADP. The efficacy of the proposed adaptive optimal tracking control methodology is demonstrated via a Van der Pol oscillator with time-varying exogenous signals.

Evaluation of Small Unmanned Aircraft Flight Trajectory Accuracy

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Ramūnas Kikutis

2014-12-01

Full Text Available Today small unmanned aircraft are being more widely adapted for practical tasks. These tasks require high reliability and flight path accuracy. For such aircraft we have to deal with the chalenge how to compensate external factors and how to ensure the accuracy of the flight trajectory according to new regulations and standards. In this paper, new regulations for the flights of small unmanned aircraft in Lithuanian air space are discussed. Main factors, which affect errors of the autonomous flight path tracking, are discussed too. The emphasis is on the wind factor and the flight path of Dubbin’s trajectories. Research was performed with mathematical-dynamic model of UAV and it was compared with theoretical calculations. All calculations and experiments were accomplished for the circular part of Dubbin’s paths when the airplane was trimmed for circular trajectory flight in calm conditions. Further, for such flight the wind influence was analysed.

Trajectory planning and trajectory tracking for a small-scale helicopter in autorotation

NARCIS (Netherlands)

Taamallah, Skander; Bombois, Xavier; Van den Hof, Paul M.J.

2017-01-01

The design of a high-performance guidance and control system for a small-scale helicopterUnmanned Aerial Vehicle (UAV), with an engine OFF flight condition (i.e. autorotation), is known to be a challenging task. It is the purpose of this paper to present a Trajectory Planning (TP) and Trajectory

Distributed radar network for real-time tracking of bullet trajectory

Science.gov (United States)

Zhang, Yimin; Li, Xin; Jin, Yuanwei; Amin, Moeness G.; Eydgahi, Ali

2009-05-01

Gunshot detection, sniper localization, and bullet trajectory prediction are of significant importance in military and homeland security applications. While the majority of existing work is based on acoustic and electro-optical sensors, this paper develops a framework of networked radar systems that uses distributed radar sensor networks to achieve the aforementioned objectives. The use of radio frequency radar systems allows the achievement of subtime- of-flight tracking response, enabling to response before the bullet reaches its target and, as such, effectively leading to the reduction of injuries and casualties in military and homeland security operations. The focus of this paper is to examine the MIMO radar concept with concurrent transmission of low-correlation waveforms from multiple radar sets to ensure wide surveillance coverage and maintain a high waveform repetition frequency for long coherent time interval required to achieve return signal concentration.

Virtual decoupling flight control via real-time trajectory synthesis and tracking

Science.gov (United States)

Zhang, Xuefu

The production of the General Aviation industry has declined in the past 25 years. Ironically, however, the increasing demand for air travel as a fast, safe, and high-quality mode of transportation has been far from satisfied. Addressing this demand shortfall with personal air transportation necessitates advanced systems for navigation, guidance, control, flight management, and flight traffic control. Among them, an effective decoupling flight control system will not only improve flight quality, safety, and simplicity, and increase air space usage, but also reduce expenses on pilot initial and current training, and thus expand the current market and explore new markets. Because of the formidable difficulties encountered in the actual decoupling of non-linear, time-variant, and highly coupled flight control systems through traditional approaches, a new approach, which essentially converts the decoupling problem into a real-time trajectory synthesis and tracking problem, is employed. Then, the converted problem is solved and a virtual decoupling effect is achieved. In this approach, a trajectory in inertial space can be predefined and dynamically modified based on the flight mission and the pilot's commands. A feedforward-feedback control architecture is constructed to guide the airplane along the trajectory as precisely as possible. Through this approach, the pilot has much simpler, virtually decoupled control of the airplane in terms of speed, flight path angle and horizontal radius of curvature. To verify and evaluate this approach, extensive computer simulation is performed. A great deal of test cases are designed for the flight control under different flight conditions. The simulation results show that our decoupling strategy is satisfactory and promising, and therefore the research can serve as a consolidated foundation for future practical applications.

How to Track Adaptation to Climate Change: A Typology of Approaches for National-Level Application

Directory of Open Access Journals (Sweden)

James D. Ford

2013-09-01

Full Text Available The need to track climate change adaptation progress is being increasingly recognized but our ability to do the tracking is constrained by the complex nature of adaptation and the absence of measurable outcomes or indicators by which to judge if and how adaptation is occurring. We developed a typology of approaches by which climate change adaptation can be tracked globally at a national level. On the one hand, outcome-based approaches directly measure adaptation progress and effectiveness with reference to avoided climate change impacts. However, given that full exposure to climate change impacts will not happen for decades, alternative approaches focus on developing indicators or proxies by which adaptation can be monitored. These include systematic measures of adaptation readiness, processes undertaken to advance adaptation, policies and programs implemented to adapt, and measures of the impacts of these policies and programs on changing vulnerability. While these approaches employ various methods and data sources, and identify different components of adaptation progress to track at the national level, they all seek to characterize the current status of adaptation by which progress over time can be monitored. However, there are significant challenges to operationalizing these approaches, including an absence of systematically collected data on adaptation actions and outcomes, underlying difficulties of defining what constitutes "adaptation", and a disconnect between the timescale over which adaptation plays out and the practical need for evaluation to inform policy. Given the development of new adaptation funding streams, it is imperative that tools for monitoring progress are developed and validated for identifying trends and gaps in adaptation response.

Adaptive DFT-Based Interferometer Fringe Tracking

Science.gov (United States)

Wilson, Edward; Pedretti, Ettore; Bregman, Jesse; Mah, Robert W.; Traub, Wesley A.

2005-12-01

An automatic interferometer fringe tracking system has been developed, implemented, and tested at the Infrared Optical Telescope Array (IOTA) Observatory at Mount Hopkins, Arizona. The system can minimize the optical path differences (OPDs) for all three baselines of the Michelson stellar interferometer at IOTA. Based on sliding window discrete Fourier-transform (DFT) calculations that were optimized for computational efficiency and robustness to atmospheric disturbances, the algorithm has also been tested extensively on offline data. Implemented in ANSI C on the 266 MHz PowerPC processor running the VxWorks real-time operating system, the algorithm runs in approximately [InlineEquation not available: see fulltext.] milliseconds per scan (including all three interferograms), using the science camera and piezo scanners to measure and correct the OPDs. The adaptive DFT-based tracking algorithm should be applicable to other systems where there is a need to detect or track a signal with an approximately constant-frequency carrier pulse. One example of such an application might be to the field of thin-film measurement by ellipsometry, using a broadband light source and a Fourier-transform spectrometer to detect the resulting fringe patterns.

Adaptive DFT-Based Interferometer Fringe Tracking

Directory of Open Access Journals (Sweden)

Wesley A. Traub

2005-09-01

Full Text Available An automatic interferometer fringe tracking system has been developed, implemented, and tested at the Infrared Optical Telescope Array (IOTA Observatory at Mount Hopkins, Arizona. The system can minimize the optical path differences (OPDs for all three baselines of the Michelson stellar interferometer at IOTA. Based on sliding window discrete Fourier-transform (DFT calculations that were optimized for computational efficiency and robustness to atmospheric disturbances, the algorithm has also been tested extensively on offline data. Implemented in ANSI C on the 266 MHz PowerPC processor running the VxWorks real-time operating system, the algorithm runs in approximately 2.0 milliseconds per scan (including all three interferograms, using the science camera and piezo scanners to measure and correct the OPDs. The adaptive DFT-based tracking algorithm should be applicable to other systems where there is a need to detect or track a signal with an approximately constant-frequency carrier pulse. One example of such an application might be to the field of thin-film measurement by ellipsometry, using a broadband light source and a Fourier-transform spectrometer to detect the resulting fringe patterns.

Mobility Modelling through Trajectory Decomposition and Prediction

OpenAIRE

Faghihi, Farbod

2017-01-01

The ubiquity of mobile devices with positioning sensors make it possible to derive user's location at any time. However, constantly sensing the position in order to track the user's movement is not feasible, either due to the unavailability of sensors, or computational and storage burdens. In this thesis, we present and evaluate a novel approach for efficiently tracking user's movement trajectories using decomposition and prediction of trajectories. We facilitate tracking by taking advantage ...

PTM Along Track Algorithm to Maintain Spacing During Same Direction Pair-Wise Trajectory Management Operations

Science.gov (United States)

Carreno, Victor A.

2015-01-01

Pair-wise Trajectory Management (PTM) is a cockpit based delegated responsibility separation standard. When an air traffic service provider gives a PTM clearance to an aircraft and the flight crew accepts the clearance, the flight crew will maintain spacing and separation from a designated aircraft. A PTM along track algorithm will receive state information from the designated aircraft and from the own ship to produce speed guidance for the flight crew to maintain spacing and separation

Adaptive optics with pupil tracking for high resolution retinal imaging.

Science.gov (United States)

Sahin, Betul; Lamory, Barbara; Levecq, Xavier; Harms, Fabrice; Dainty, Chris

2012-02-01

Adaptive optics, when integrated into retinal imaging systems, compensates for rapidly changing ocular aberrations in real time and results in improved high resolution images that reveal the photoreceptor mosaic. Imaging the retina at high resolution has numerous potential medical applications, and yet for the development of commercial products that can be used in the clinic, the complexity and high cost of the present research systems have to be addressed. We present a new method to control the deformable mirror in real time based on pupil tracking measurements which uses the default camera for the alignment of the eye in the retinal imaging system and requires no extra cost or hardware. We also present the first experiments done with a compact adaptive optics flood illumination fundus camera where it was possible to compensate for the higher order aberrations of a moving model eye and in vivo in real time based on pupil tracking measurements, without the real time contribution of a wavefront sensor. As an outcome of this research, we showed that pupil tracking can be effectively used as a low cost and practical adaptive optics tool for high resolution retinal imaging because eye movements constitute an important part of the ocular wavefront dynamics.

Augmented $L1$ adaptive control of an actuated knee joint exoskeleton: From design to real-time experiments

OpenAIRE

Rifai , Hala; Ben Abdessalem , Mohamed ,; Chemori , Ahmed; Mohammed , Samer; Amirat , Yacine

2016-01-01

International audience; This paper deals with the control of a lower limb exoskeleton acting on the knee joint level. Classical L1 adaptive control law is proposed to ensure assistance-as-needed and resistive rehabilitation following a desired trajectory considered defined by a therapeutic doctor. This control law introduces a time lag within the desired trajectory tracking because of the presence of a filter in its structure. In order to mitigate this drawback, the classical L1 adaptive cont...

Object Tracking Using Adaptive Covariance Descriptor and Clustering-Based Model Updating for Visual Surveillance

Directory of Open Access Journals (Sweden)

Lei Qin

2014-05-01

Full Text Available We propose a novel approach for tracking an arbitrary object in video sequences for visual surveillance. The first contribution of this work is an automatic feature extraction method that is able to extract compact discriminative features from a feature pool before computing the region covariance descriptor. As the feature extraction method is adaptive to a specific object of interest, we refer to the region covariance descriptor computed using the extracted features as the adaptive covariance descriptor. The second contribution is to propose a weakly supervised method for updating the object appearance model during tracking. The method performs a mean-shift clustering procedure among the tracking result samples accumulated during a period of time and selects a group of reliable samples for updating the object appearance model. As such, the object appearance model is kept up-to-date and is prevented from contamination even in case of tracking mistakes. We conducted comparing experiments on real-world video sequences, which confirmed the effectiveness of the proposed approaches. The tracking system that integrates the adaptive covariance descriptor and the clustering-based model updating method accomplished stable object tracking on challenging video sequences.

Vehicle Reference Generator for Collision-Free Trajectories in Hazardous Maneuvers

Directory of Open Access Journals (Sweden)

Cuauhtémoc Acosta Lúa

2018-01-01

Full Text Available This paper presents a reference generator for ground vehicles, based on potential fields adapted to the case of vehicular dynamics. The reference generator generates signals to be tracked by the vehicle, corresponding to a trajectory avoiding collisions with obstacles. This generator integrates artificial forces of potential fields of the object surrounding the vehicle. The reference generator is used with a controller to ensure the tracking of the accident-free reference. This approach can be used for vehicle autonomous driving or for active control of manned vehicles. Simulation results, presented for the autonomous driving, consider a scenario inspired by the so-called moose (or elk test, with the presence of other collaborative vehicles.

Cognitive, Linguistic and Adaptive Functioning in Williams Syndrome: Trajectories from Early to Middle Adulthood

Science.gov (United States)

Howlin, Patricia; Elison, Sarah; Udwin, Orlee; Stinton, Christopher

2010-01-01

Background: Little is known about trajectories of cognitive functioning as individuals with Williams syndrome (WS) move though adulthood. Method: The present study investigated cognitive, linguistic and adaptive functioning in adults with WS aged 19-55 years, using both cross-sectional and longitudinal approaches. Results: Data from the…

High precision tracking of a piezoelectric nano-manipulator with parameterized hysteresis compensation

Science.gov (United States)

Yan, Peng; Zhang, Yangming

2018-06-01

High performance scanning of nano-manipulators is widely deployed in various precision engineering applications such as SPM (scanning probe microscope), where trajectory tracking of sophisticated reference signals is an challenging control problem. The situation is further complicated when rate dependent hysteresis of the piezoelectric actuators and the stress-stiffening induced nonlinear stiffness of the flexure mechanism are considered. In this paper, a novel control framework is proposed to achieve high precision tracking of a piezoelectric nano-manipulator subjected to hysteresis and stiffness nonlinearities. An adaptive parameterized rate-dependent Prandtl-Ishlinskii model is constructed and the corresponding adaptive inverse model based online compensation is derived. Meanwhile a robust adaptive control architecture is further introduced to improve the tracking accuracy and robustness of the compensated system, where the parametric uncertainties of the nonlinear dynamics can be well eliminated by on-line estimations. Comparative experimental studies of the proposed control algorithm are conducted on a PZT actuated nano-manipulating stage, where hysteresis modeling accuracy and excellent tracking performance are demonstrated in real-time implementations, with significant improvement over existing results.

On Using Exponential Parameter Estimators with an Adaptive Controller

Science.gov (United States)

Patre, Parag; Joshi, Suresh M.

2011-01-01

Typical adaptive controllers are restricted to using a specific update law to generate parameter estimates. This paper investigates the possibility of using any exponential parameter estimator with an adaptive controller such that the system tracks a desired trajectory. The goal is to provide flexibility in choosing any update law suitable for a given application. The development relies on a previously developed concept of controller/update law modularity in the adaptive control literature, and the use of a converse Lyapunov-like theorem. Stability analysis is presented to derive gain conditions under which this is possible, and inferences are made about the tracking error performance. The development is based on a class of Euler-Lagrange systems that are used to model various engineering systems including space robots and manipulators.

Adaptive learning compressive tracking based on Markov location prediction

Science.gov (United States)

Zhou, Xingyu; Fu, Dongmei; Yang, Tao; Shi, Yanan

2017-03-01

Object tracking is an interdisciplinary research topic in image processing, pattern recognition, and computer vision which has theoretical and practical application value in video surveillance, virtual reality, and automatic navigation. Compressive tracking (CT) has many advantages, such as efficiency and accuracy. However, when there are object occlusion, abrupt motion and blur, similar objects, and scale changing, the CT has the problem of tracking drift. We propose the Markov object location prediction to get the initial position of the object. Then CT is used to locate the object accurately, and the classifier parameter adaptive updating strategy is given based on the confidence map. At the same time according to the object location, extract the scale features, which is able to deal with object scale variations effectively. Experimental results show that the proposed algorithm has better tracking accuracy and robustness than current advanced algorithms and achieves real-time performance.

An adaptive approach to human motion tracking from video

Science.gov (United States)

Wu, Lifang; Chen, Chang Wen

2010-07-01

Vision based human motion tracking has drawn considerable interests recently because of its extensive applications. In this paper, we propose an approach to tracking the body motion of human balancing on each foot. The ability to balance properly is an important indication of neurological condition. Comparing with many other human motion tracking, there is much less occlusion in human balancing tracking. This less constrained problem allows us to combine a 2D model of human body with image analysis techniques to develop an efficient motion tracking algorithm. First we define a hierarchical 2D model consisting of six components including head, body and four limbs. Each of the four limbs involves primary component (upper arms and legs) and secondary component (lower arms and legs) respectively. In this model, we assume each of the components can be represented by quadrangles and every component is connected to one of others by a joint. By making use of inherent correlation between different components, we design a top-down updating framework and an adaptive algorithm with constraints of foreground regions for robust and efficient tracking. The approach has been tested using the balancing movement in HumanEva-I/II dataset. The average tracking time is under one second, which is much shorter than most of current schemes.

Chattering-Free Adaptive Sliding Mode Control for Attitude Tracking of Spacecraft with External Disturbance

Directory of Open Access Journals (Sweden)

Xuxi Zhang

2014-01-01

Full Text Available The attitude tracking problem of spacecraft in the presence of unknown disturbance is investigated. By using the adaptive control technique and the Lyapunov stability theory, a chattering-free adaptive sliding mode control law is proposed for the attitude tracking problem of spacecraft with unknown disturbance. Simulation results are employed to demonstrate the effectiveness of the proposed control design technique in this paper.

TH-AB-202-04: Auto-Adaptive Margin Generation for MLC-Tracked Radiotherapy

International Nuclear Information System (INIS)

Glitzner, M; Lagendijk, J; Raaymakers, B; Crijns, S; Fast, M; Nill, S; Oelfke, U; Denis de Senneville, B

2016-01-01

Purpose: To develop an auto-adaptive margin generator for MLC tracking. The generator is able to estimate errors arising in image guided radiotherapy, particularly on an MR-Linac, which depend on the latencies of machine and image processing, as well as on patient motion characteristics. From the estimated error distribution, a segment margin is generated, able to compensate errors up to a user-defined confidence. Method: In every tracking control cycle (TCC, 40ms), the desired aperture D(t) is compared to the actual aperture A(t), a delayed and imperfect representation of D(t). Thus an error e(t)=A(T)-D(T) is measured every TCC. Applying kernel-density-estimation (KDE), the cumulative distribution (CDF) of e(t) is estimated. With CDF-confidence limits, upper and lower error limits are extracted for motion axes along and perpendicular leaf-travel direction and applied as margins. To test the dosimetric impact, two representative motion traces were extracted from fast liver-MRI (10Hz). The traces were applied onto a 4D-motion platform and continuously tracked by an Elekta Agility 160 MLC using an artificially imposed tracking delay. Gafchromic film was used to detect dose exposition for static, tracked, and error-compensated tracking cases. The margin generator was parameterized to cover 90% of all tracking errors. Dosimetric impact was rated by calculating the ratio between underexposed points (>5% underdosage) to the total number of points inside FWHM of static exposure. Results: Without imposing adaptive margins, tracking experiments showed a ratio of underexposed points of 17.5% and 14.3% for two motion cases with imaging delays of 200ms and 300ms, respectively. Activating the margin generated yielded total suppression (<1%) of underdosed points. Conclusion: We showed that auto-adaptive error compensation using machine error statistics is possible for MLC tracking. The error compensation margins are calculated on-line, without the need of assuming motion or

TH-AB-202-04: Auto-Adaptive Margin Generation for MLC-Tracked Radiotherapy

Energy Technology Data Exchange (ETDEWEB)

Glitzner, M; Lagendijk, J; Raaymakers, B; Crijns, S [University Medical Center Utrecht, Utrecht (Netherlands); Fast, M; Nill, S; Oelfke, U [The Institute of Cancer Research, London (United Kingdom); Denis de Senneville, B [University Medical Center Utrecht, Utrecht (Netherlands); IMB, UMR 5251 CNRS/University of Bordeaux, Talence, FR (France)

2016-06-15

Purpose: To develop an auto-adaptive margin generator for MLC tracking. The generator is able to estimate errors arising in image guided radiotherapy, particularly on an MR-Linac, which depend on the latencies of machine and image processing, as well as on patient motion characteristics. From the estimated error distribution, a segment margin is generated, able to compensate errors up to a user-defined confidence. Method: In every tracking control cycle (TCC, 40ms), the desired aperture D(t) is compared to the actual aperture A(t), a delayed and imperfect representation of D(t). Thus an error e(t)=A(T)-D(T) is measured every TCC. Applying kernel-density-estimation (KDE), the cumulative distribution (CDF) of e(t) is estimated. With CDF-confidence limits, upper and lower error limits are extracted for motion axes along and perpendicular leaf-travel direction and applied as margins. To test the dosimetric impact, two representative motion traces were extracted from fast liver-MRI (10Hz). The traces were applied onto a 4D-motion platform and continuously tracked by an Elekta Agility 160 MLC using an artificially imposed tracking delay. Gafchromic film was used to detect dose exposition for static, tracked, and error-compensated tracking cases. The margin generator was parameterized to cover 90% of all tracking errors. Dosimetric impact was rated by calculating the ratio between underexposed points (>5% underdosage) to the total number of points inside FWHM of static exposure. Results: Without imposing adaptive margins, tracking experiments showed a ratio of underexposed points of 17.5% and 14.3% for two motion cases with imaging delays of 200ms and 300ms, respectively. Activating the margin generated yielded total suppression (<1%) of underdosed points. Conclusion: We showed that auto-adaptive error compensation using machine error statistics is possible for MLC tracking. The error compensation margins are calculated on-line, without the need of assuming motion or

A MEMS-based Adaptive AHRS for Marine Satellite Tracking Antenna

DEFF Research Database (Denmark)

Wang, Yunlong; Hussain, Dil Muhammed Akbar; Soltani, Mohsen

2015-01-01

Satellite tracking is a challenging task for marine applications. An attitude determination system should estimate the wave disturbances on the ship body accurately. To achieve this, an Attitude Heading Reference System (AHRS) based on Micro-Electro-Mechanical Systems (MEMS) sensors, composed...... of three-axis gyroscope, accelerometer and magnetometer, is developed for Marine Satellite Tracking Antenna (MSTA). In this paper, the attitude determination algorithm is improved using an adaptive mechanism that tunes the attitude estimator parameters based on an estimation of ship motion frequency...

Geometric Algorithms for Trajectory Analysis

NARCIS (Netherlands)

Staals, Frank

2015-01-01

Technology such as the Global Positing System (GPS) has made tracking moving entities easy and cheap. As a result there is a large amount of trajectory data available, and an increasing demand on tools and techniques to analyze such data. We consider several analysis tasks for trajectory data,

A Method for Extracting Road Boundary Information from Crowdsourcing Vehicle GPS Trajectories.

Science.gov (United States)

Yang, Wei; Ai, Tinghua; Lu, Wei

2018-04-19

Crowdsourcing trajectory data is an important approach for accessing and updating road information. In this paper, we present a novel approach for extracting road boundary information from crowdsourcing vehicle traces based on Delaunay triangulation (DT). First, an optimization and interpolation method is proposed to filter abnormal trace segments from raw global positioning system (GPS) traces and interpolate the optimization segments adaptively to ensure there are enough tracking points. Second, constructing the DT and the Voronoi diagram within interpolated tracking lines to calculate road boundary descriptors using the area of Voronoi cell and the length of triangle edge. Then, the road boundary detection model is established integrating the boundary descriptors and trajectory movement features (e.g., direction) by DT. Third, using the boundary detection model to detect road boundary from the DT constructed by trajectory lines, and a regional growing method based on seed polygons is proposed to extract the road boundary. Experiments were conducted using the GPS traces of taxis in Beijing, China, and the results show that the proposed method is suitable for extracting the road boundary from low-frequency GPS traces, multi-type road structures, and different time intervals. Compared with two existing methods, the automatically extracted boundary information was proved to be of higher quality.

A Method for Extracting Road Boundary Information from Crowdsourcing Vehicle GPS Trajectories

Directory of Open Access Journals (Sweden)

Wei Yang

2018-04-01

Full Text Available Crowdsourcing trajectory data is an important approach for accessing and updating road information. In this paper, we present a novel approach for extracting road boundary information from crowdsourcing vehicle traces based on Delaunay triangulation (DT. First, an optimization and interpolation method is proposed to filter abnormal trace segments from raw global positioning system (GPS traces and interpolate the optimization segments adaptively to ensure there are enough tracking points. Second, constructing the DT and the Voronoi diagram within interpolated tracking lines to calculate road boundary descriptors using the area of Voronoi cell and the length of triangle edge. Then, the road boundary detection model is established integrating the boundary descriptors and trajectory movement features (e.g., direction by DT. Third, using the boundary detection model to detect road boundary from the DT constructed by trajectory lines, and a regional growing method based on seed polygons is proposed to extract the road boundary. Experiments were conducted using the GPS traces of taxis in Beijing, China, and the results show that the proposed method is suitable for extracting the road boundary from low-frequency GPS traces, multi-type road structures, and different time intervals. Compared with two existing methods, the automatically extracted boundary information was proved to be of higher quality.

Fuzzy Vector Field Orientation Feedback Control-Based Slip Compensation for Trajectory Tracking Control of a Four Track Wheel Skid-steered Mobile Robot

Directory of Open Access Journals (Sweden)

Xuan Vinh Ha

2013-04-01

Full Text Available Skid-steered mobile robots have been widely used in exploring unknown environments and in military applications. In this paper, the tuning fuzzy Vector Field Orientation (FVFO feedback control method is proposed for a four track wheel skid-steered mobile robot (4-TW SSMR using flexible fuzzy logic control (FLC. The extended Kalman filter is utilized to estimate the positions, velocities and orientation angles, which are used for feedback control signals in the FVFO method, based on the AHRS kinematic motion model and velocity constraints. In addition, in light of the wheel slip and the braking ability of the robot, we propose a new method for estimating online wheel slip parameters based on a discrete Kalman filter to compensate for the velocity constraints. As demonstrated by our experimental results, the advantages of the combination of the proposed FVFO and wheel slip estimation methods overcome the limitations of the others in the trajectory tracking control problem for a 4-TW SSMR.

Adaptive Backstepping-Based Neural Tracking Control for MIMO Nonlinear Switched Systems Subject to Input Delays.

Science.gov (United States)

Niu, Ben; Li, Lu

2018-06-01

This brief proposes a new neural-network (NN)-based adaptive output tracking control scheme for a class of disturbed multiple-input multiple-output uncertain nonlinear switched systems with input delays. By combining the universal approximation ability of radial basis function NNs and adaptive backstepping recursive design with an improved multiple Lyapunov function (MLF) scheme, a novel adaptive neural output tracking controller design method is presented for the switched system. The feature of the developed design is that different coordinate transformations are adopted to overcome the conservativeness caused by adopting a common coordinate transformation for all subsystems. It is shown that all the variables of the resulting closed-loop system are semiglobally uniformly ultimately bounded under a class of switching signals in the presence of MLF and that the system output can follow the desired reference signal. To demonstrate the practicability of the obtained result, an adaptive neural output tracking controller is designed for a mass-spring-damper system.

Toward a method for tracking virus evolutionary trajectory applied to the pandemic H1N1 2009 influenza virus.

Science.gov (United States)

Squires, R Burke; Pickett, Brett E; Das, Sajal; Scheuermann, Richard H

2014-12-01

In 2009 a novel pandemic H1N1 influenza virus (H1N1pdm09) emerged as the first official influenza pandemic of the 21st century. Early genomic sequence analysis pointed to the swine origin of the virus. Here we report a novel computational approach to determine the evolutionary trajectory of viral sequences that uses data-driven estimations of nucleotide substitution rates to track the gradual accumulation of observed sequence alterations over time. Phylogenetic analysis and multiple sequence alignments show that sequences belonging to the resulting evolutionary trajectory of the H1N1pdm09 lineage exhibit a gradual accumulation of sequence variations and tight temporal correlations in the topological structure of the phylogenetic trees. These results suggest that our evolutionary trajectory analysis (ETA) can more effectively pinpoint the evolutionary history of viruses, including the host and geographical location traversed by each segment, when compared against either BLAST or traditional phylogenetic analysis alone. Copyright © 2014 Elsevier B.V. All rights reserved.

Online 4D ultrasound guidance for real-time motion compensation by MLC tracking.

Science.gov (United States)

Ipsen, Svenja; Bruder, Ralf; O'Brien, Rick; Keall, Paul J; Schweikard, Achim; Poulsen, Per R

2016-10-01

With the trend in radiotherapy moving toward dose escalation and hypofractionation, the need for highly accurate targeting increases. While MLC tracking is already being successfully used for motion compensation of moving targets in the prostate, current real-time target localization methods rely on repeated x-ray imaging and implanted fiducial markers or electromagnetic transponders rather than direct target visualization. In contrast, ultrasound imaging can yield volumetric data in real-time (3D + time = 4D) without ionizing radiation. The authors report the first results of combining these promising techniques-online 4D ultrasound guidance and MLC tracking-in a phantom. A software framework for real-time target localization was installed directly on a 4D ultrasound station and used to detect a 2 mm spherical lead marker inside a water tank. The lead marker was rigidly attached to a motion stage programmed to reproduce nine characteristic tumor trajectories chosen from large databases (five prostate, four lung). The 3D marker position detected by ultrasound was transferred to a computer program for MLC tracking at a rate of 21.3 Hz and used for real-time MLC aperture adaption on a conventional linear accelerator. The tracking system latency was measured using sinusoidal trajectories and compensated for by applying a kernel density prediction algorithm for the lung traces. To measure geometric accuracy, static anterior and lateral conformal fields as well as a 358° arc with a 10 cm circular aperture were delivered for each trajectory. The two-dimensional (2D) geometric tracking error was measured as the difference between marker position and MLC aperture center in continuously acquired portal images. For dosimetric evaluation, VMAT treatment plans with high and low modulation were delivered to a biplanar diode array dosimeter using the same trajectories. Dose measurements with and without MLC tracking were compared to a static reference dose using 3%/3 mm and 2

An adaptive multi-spline refinement algorithm in simulation based sailboat trajectory optimization using onboard multi-core computer systems

Directory of Open Access Journals (Sweden)

Dębski Roman

2016-06-01

Full Text Available A new dynamic programming based parallel algorithm adapted to on-board heterogeneous computers for simulation based trajectory optimization is studied in the context of “high-performance sailing”. The algorithm uses a new discrete space of continuously differentiable functions called the multi-splines as its search space representation. A basic version of the algorithm is presented in detail (pseudo-code, time and space complexity, search space auto-adaptation properties. Possible extensions of the basic algorithm are also described. The presented experimental results show that contemporary heterogeneous on-board computers can be effectively used for solving simulation based trajectory optimization problems. These computers can be considered micro high performance computing (HPC platforms-they offer high performance while remaining energy and cost efficient. The simulation based approach can potentially give highly accurate results since the mathematical model that the simulator is built upon may be as complex as required. The approach described is applicable to many trajectory optimization problems due to its black-box represented performance measure and use of OpenCL.

On designing geometric motion planners to solve regulating and trajectory tracking problems for robotic locomotion systems

Energy Technology Data Exchange (ETDEWEB)

Asnafi, Alireza [Hydro-Aeronautical Research Center, Shiraz University, Shiraz, 71348-13668 (Iran, Islamic Republic of); Mahzoon, Mojtaba [Department of Mechanical Engineering, School of Engineering, Shiraz University, Shiraz, 71348-13668 (Iran, Islamic Republic of)

2011-09-15

Based on a geometric fiber bundle structure, a generalized method to solve both regulation and trajectory tracking problems for locomotion systems is presented. The method is especially applied to two case studies of robotic locomotion systems; a three link articulated fish-like robot as a prototype of locomotion systems with symmetry, and the snakeboard as a prototype of mixed locomotion systems. Our results show that although these motion planners have an open loop structure, due to their generalities, they can steer case studies with negligible errors for almost any complicated path.

On designing geometric motion planners to solve regulating and trajectory tracking problems for robotic locomotion systems

International Nuclear Information System (INIS)

Asnafi, Alireza; Mahzoon, Mojtaba

2011-01-01

Based on a geometric fiber bundle structure, a generalized method to solve both regulation and trajectory tracking problems for locomotion systems is presented. The method is especially applied to two case studies of robotic locomotion systems; a three link articulated fish-like robot as a prototype of locomotion systems with symmetry, and the snakeboard as a prototype of mixed locomotion systems. Our results show that although these motion planners have an open loop structure, due to their generalities, they can steer case studies with negligible errors for almost any complicated path.

Tracking Control of Hysteretic Piezoelectric Actuator using Adaptive Rate-Dependent Controller.

Science.gov (United States)

Tan, U-Xuan; Latt, Win Tun; Widjaja, Ferdinan; Shee, Cheng Yap; Riviere, Cameron N; Ang, Wei Tech

2009-03-16

With the increasing popularity of actuators involving smart materials like piezoelectric, control of such materials becomes important. The existence of the inherent hysteretic behavior hinders the tracking accuracy of the actuators. To make matters worse, the hysteretic behavior changes with rate. One of the suggested ways is to have a feedforward controller to linearize the relationship between the input and output. Thus, the hysteretic behavior of the actuator must first be modeled by sensing the relationship between the input voltage and output displacement. Unfortunately, the hysteretic behavior is dependent on individual actuator and also environmental conditions like temperature. It is troublesome and costly to model the hysteresis regularly. In addition, the hysteretic behavior of the actuators also changes with age. Most literature model the actuator using a cascade of rate-independent hysteresis operators and a dynamical system. However, the inertial dynamics of the structure is not the only contributing factor. A complete model will be complex. Thus, based on the studies done on the phenomenological hysteretic behavior with rate, this paper proposes an adaptive rate-dependent feedforward controller with Prandtl-Ishlinskii (PI) hysteresis operators for piezoelectric actuators. This adaptive controller is achieved by adapting the coefficients to manipulate the weights of the play operators. Actual experiments are conducted to demonstrate the effectiveness of the adaptive controller. The main contribution of this paper is its ability to perform tracking control of non-periodic motion and is illustrated with the tracking control ability of a couple of different non-periodic waveforms which were created by passing random numbers through a low pass filter with a cutoff frequency of 20Hz.

Obstacle avoidance for kinematically redundant robots using an adaptive fuzzy logic algorithm

International Nuclear Information System (INIS)

Beheshti, M.T.H.; Tehrani, A.K.

1999-05-01

In this paper the Adaptive Fuzzy Logic approach for solving the inverse kinematics of redundant robots in an environment with obstacles is presented. The obstacles are modeled as convex bodies. A fuzzy rule base that is updated via an adaptive law is used to solve the inverse kinematic problem. Additional rules have been introduced to take care of the obstacles avoidance problem. The proposed method has advantages such as high accuracy, simplicity of computations and generality for all redundant robots. Simulation results illustrate much better tracking performance than the dynamic base solution for a given trajectory in cartesian space, while guaranteeing a collision-free trajectory and observation of a mechanical joint limit

Adaptive Backstepping Control of Lightweight Tower Wind Turbine

DEFF Research Database (Denmark)

Galeazzi, Roberto; Borup, Kasper Trolle; Niemann, Hans Henrik

2015-01-01

the angular deflection of the tower with respect to the vertical axis in response to variations in wind speed. The controller is shown to guarantee asymptotic tracking of the reference trajectory. The performance of the control system is evaluated through deterministic and stochastic simulations including......This paper investigates the feasibility of operating a wind turbine with lightweight tower in the full load region exploiting an adaptive nonlinear controller that allows the turbine to dynamically lean against the wind while maintaining nominal power output. The use of lightweight structures...... for towers and foundations would greatly reduce the construction cost of the wind turbine, however extra features ought be included in the control system architecture to avoid tower collapse. An adaptive backstepping collective pitch controller is proposed for tower point tracking control, i.e. to modify...

Robust online tracking via adaptive samples selection with saliency detection

Science.gov (United States)

Yan, Jia; Chen, Xi; Zhu, QiuPing

2013-12-01

Online tracking has shown to be successful in tracking of previously unknown objects. However, there are two important factors which lead to drift problem of online tracking, the one is how to select the exact labeled samples even when the target locations are inaccurate, and the other is how to handle the confusors which have similar features with the target. In this article, we propose a robust online tracking algorithm with adaptive samples selection based on saliency detection to overcome the drift problem. To deal with the problem of degrading the classifiers using mis-aligned samples, we introduce the saliency detection method to our tracking problem. Saliency maps and the strong classifiers are combined to extract the most correct positive samples. Our approach employs a simple yet saliency detection algorithm based on image spectral residual analysis. Furthermore, instead of using the random patches as the negative samples, we propose a reasonable selection criterion, in which both the saliency confidence and similarity are considered with the benefits that confusors in the surrounding background are incorporated into the classifiers update process before the drift occurs. The tracking task is formulated as a binary classification via online boosting framework. Experiment results in several challenging video sequences demonstrate the accuracy and stability of our tracker.

Intelligent Hybrid Control Strategy for Trajectory Tracking of Robot Manipulators

Directory of Open Access Journals (Sweden)

Yi Zuo

2008-01-01

Full Text Available We address the problem of robust tracking control using a PD-plus-feedforward controller and an intelligent adaptive robust compensator for a rigid robotic manipulator with uncertain dynamics and external disturbances. A key feature of this scheme is that soft computer methods are used to learn the upper bound of system uncertainties and adjust the width of the boundary layer base. In this way, the prior knowledge of the upper bound of the system uncertainties does need not to be required. Moreover, chattering can be effectively eliminated, and asymptotic error convergence can be guaranteed. Numerical simulations and experiments of two-DOF rigid robots are presented to show effectiveness of the proposed scheme.

An adaptive Cartesian control scheme for manipulators

Science.gov (United States)

Seraji, H.

1987-01-01

A adaptive control scheme for direct control of manipulator end-effectors to achieve trajectory tracking in Cartesian space is developed. The control structure is obtained from linear multivariable theory and is composed of simple feedforward and feedback controllers and an auxiliary input. The direct adaptation laws are derived from model reference adaptive control theory and are not based on parameter estimation of the robot model. The utilization of feedforward control and the inclusion of auxiliary input are novel features of the present scheme and result in improved dynamic performance over existing adaptive control schemes. The adaptive controller does not require the complex mathematical model of the robot dynamics or any knowledge of the robot parameters or the payload, and is computationally fast for online implementation with high sampling rates.

Neural and Fuzzy Adaptive Control of Induction Motor Drives

International Nuclear Information System (INIS)

Bensalem, Y.; Sbita, L.; Abdelkrim, M. N.

2008-01-01

This paper proposes an adaptive neural network speed control scheme for an induction motor (IM) drive. The proposed scheme consists of an adaptive neural network identifier (ANNI) and an adaptive neural network controller (ANNC). For learning the quoted neural networks, a back propagation algorithm was used to automatically adjust the weights of the ANNI and ANNC in order to minimize the performance functions. Here, the ANNI can quickly estimate the plant parameters and the ANNC is used to provide on-line identification of the command and to produce a control force, such that the motor speed can accurately track the reference command. By combining artificial neural network techniques with fuzzy logic concept, a neural and fuzzy adaptive control scheme is developed. Fuzzy logic was used for the adaptation of the neural controller to improve the robustness of the generated command. The developed method is robust to load torque disturbance and the speed target variations when it ensures precise trajectory tracking with the prescribed dynamics. The algorithm was verified by simulation and the results obtained demonstrate the effectiveness of the IM designed controller

Implementation of an adaptive training and tracking game in statistics teaching

NARCIS (Netherlands)

Groeneveld, C.M.; Kalz, M.; Ras, E.

2014-01-01

Statistics teaching in higher education has a number of challenges. An adaptive training, tracking and teaching tool in a gaming environment aims to address problems inherent in statistics teaching. This paper discusses the implementation of this tool in a large first year university programme and

Adaptive H∞ nonlinear velocity tracking using RBFNN for linear DC brushless motor

Science.gov (United States)

Tsai, Ching-Chih; Chan, Cheng-Kain; Li, Yi Yu

2012-01-01

This article presents an adaptive H ∞ nonlinear velocity control for a linear DC brushless motor. A simplified model of this motor with friction is briefly recalled. The friction dynamics is described by the Lu Gre model and the online tuning radial basis function neural network (RBFNN) is used to parameterise the nonlinear friction function and un-modelled errors. An adaptive nonlinear H ∞ control method is then proposed to achieve velocity tracking, by assuming that the upper bounds of the ripple force, the changeable load and the nonlinear friction can be learned by the RBFNN. The closed-loop system is proven to be uniformly bounded using the Lyapunov stability theory. The feasibility and the efficacy of the proposed control are exemplified by conducting two velocity tracking experiments.

A multi-frame particle tracking algorithm robust against input noise

International Nuclear Information System (INIS)

Li, Dongning; Zhang, Yuanhui; Sun, Yigang; Yan, Wei

2008-01-01

The performance of a particle tracking algorithm which detects particle trajectories from discretely recorded particle positions could be substantially hindered by the input noise. In this paper, a particle tracking algorithm is developed which is robust against input noise. This algorithm employs the regression method instead of the extrapolation method usually employed by existing algorithms to predict future particle positions. If a trajectory cannot be linked to a particle at a frame, the algorithm can still proceed by trying to find a candidate at the next frame. The connectivity of tracked trajectories is inspected to remove the false ones. The algorithm is validated with synthetic data. The result shows that the algorithm is superior to traditional algorithms in the aspect of tracking long trajectories

Air-Breathing Hypersonic Vehicle Tracking Control Based on Adaptive Dynamic Programming.

Science.gov (United States)

Mu, Chaoxu; Ni, Zhen; Sun, Changyin; He, Haibo

2017-03-01

In this paper, we propose a data-driven supplementary control approach with adaptive learning capability for air-breathing hypersonic vehicle tracking control based on action-dependent heuristic dynamic programming (ADHDP). The control action is generated by the combination of sliding mode control (SMC) and the ADHDP controller to track the desired velocity and the desired altitude. In particular, the ADHDP controller observes the differences between the actual velocity/altitude and the desired velocity/altitude, and then provides a supplementary control action accordingly. The ADHDP controller does not rely on the accurate mathematical model function and is data driven. Meanwhile, it is capable to adjust its parameters online over time under various working conditions, which is very suitable for hypersonic vehicle system with parameter uncertainties and disturbances. We verify the adaptive supplementary control approach versus the traditional SMC in the cruising flight, and provide three simulation studies to illustrate the improved performance with the proposed approach.

An adaptive vibration control method to suppress the vibration of the maglev train caused by track irregularities

Science.gov (United States)

Zhou, Danfeng; Yu, Peichang; Wang, Lianchun; Li, Jie

2017-11-01

The levitation gap of the urban maglev train is around 8 mm, which puts a rather high requirement on the smoothness of the track. In practice, it is found that the track irregularity may cause stability problems when the maglev train is traveling. In this paper, the dynamic response of the levitation module, which is the basic levitation structure of the urban maglev train, is investigated in the presence of track irregularities. Analyses show that due to the structural configuration of the levitation module, the vibration of the levitation gap may be amplified and "resonances" may be observed under some specified track wavelengths and train speeds; besides, it is found that the gap vibration of the rear levitation unit in a levitation module is more significant than that of the front levitation unit, which agrees well with practice. To suppress the vibration of the rear levitation gap, an adaptive vibration control method is proposed, which utilizes the information of the front levitation unit as a reference. A pair of mirror FIR (finite impulse response) filters are designed and tuned by an adaptive mechanism, and they produce a compensation signal for the rear levitation controller to cancel the disturbance brought by the track irregularity. Simulations under some typical track conditions, including the sinusoidal track profile, random track irregularity, as well as track steps, indicate that the adaptive vibration control scheme can significantly reduce the amplitude of the rear gap vibration, which provides a method to improve the stability and ride comfort of the maglev train.

Wavelet-based tracking of bacteria in unreconstructed off-axis holograms.

Science.gov (United States)

Marin, Zach; Wallace, J Kent; Nadeau, Jay; Khalil, Andre

2018-03-01

We propose an automated wavelet-based method of tracking particles in unreconstructed off-axis holograms to provide rough estimates of the presence of motion and particle trajectories in digital holographic microscopy (DHM) time series. The wavelet transform modulus maxima segmentation method is adapted and tailored to extract Airy-like diffraction disks, which represent bacteria, from DHM time series. In this exploratory analysis, the method shows potential for estimating bacterial tracks in low-particle-density time series, based on a preliminary analysis of both living and dead Serratia marcescens, and for rapidly providing a single-bit answer to whether a sample chamber contains living or dead microbes or is empty. Copyright © 2017 Elsevier Inc. All rights reserved.

Adaptive Output Tracking Control for Nonlinear Systems with Failed Actuators and Aircraft Flight System Applications

OpenAIRE

Hou, Chuanjing; Hu, Lisheng; Zhang, Yingwei

2015-01-01

An adaptive failure compensation scheme using output feedback is proposed for a class of nonlinear systems with nonlinearities depending on the unmeasured states of systems. Adaptive high-gain K-filters are presented to suppress the nonlinearities while the proposed backstepping adaptive high-gain controller guarantees the stability of the closed-loop system and small tracking errors. Simulation results verify that the adaptive failure compensation scheme is effective.

Adaptive Sliding-Mode Tracking Control for a Class of Nonholonomic Mechanical Systems

Directory of Open Access Journals (Sweden)

Wei Sun

2013-01-01

Full Text Available This paper investigates the problem of finite-time tracking control for nonholonomic mechanical systems with affine constraints. The control scheme is provided by flexibly incorporating terminal sliding-mode control with the method of relay switching control and related adaptive technique. The proposed relay switching controller ensures that the output tracking error converges to zero in a finite time. As an application, a boat on a running river is given to show the effectiveness of the control scheme.

Nonlinear model-based robust control of a nuclear reactor using adaptive PIF gains and variable structure controller

International Nuclear Information System (INIS)

Park, Moon Ghu; Cho, Nam Zin

1993-01-01

A Nonlinear model-based Hybrid Controller (NHC) is developed which consists of the adaptive proportional-integral-feedforward (PIF) gains and variable structure controller. The controller has the robustness against modeling uncertainty and is applied to the trajectory tracking control of single-input, single-output nonlinear systems. The essence of the scheme is to divide the control into four different terms. Namely, the adaptive P-I-F gains and variable structure controller are used to accomplish the specific control actions by each terms. The robustness of the controller is guaranteed by the feedback of estimated uncertainty and the performance specification given by the adaptation of PIF gains using the second method of Lyapunov. The variable structure controller is incorporated to regulate the initial peak of the tracking error during the parameter adaptation is not settled yet. The newly developed NHC method is applied to the power tracking control of a nuclear reactor and the simulation results show great improvement in tracking performance compared with the conventional model-based control methods. (Author)

Efficient and Adaptive Node Selection for Target Tracking in Wireless Sensor Network

Directory of Open Access Journals (Sweden)

Juan Feng

2016-01-01

Full Text Available In target tracking wireless sensor network, choosing the proper working nodes can not only minimize the number of active nodes, but also satisfy the tracking reliability requirement. However, most existing works focus on selecting sensor nodes which are the nearest to the target for tracking missions and they did not consider the correlation of the location of the sensor nodes so that these approaches can not meet all the goals of the network. This work proposes an efficient and adaptive node selection approach for tracking a target in a distributed wireless sensor network. The proposed approach combines the distance-based node selection strategy and particle filter prediction considering the spatial correlation of the different sensing nodes. Moreover, a joint distance weighted measurement is proposed to estimate the information utility of sensing nodes. Experimental results show that EANS outperformed the state-of-the-art approaches by reducing the energy cost and computational complexity as well as guaranteeing the tracking accuracy.

L1 Adaptive Speed Control of a Small Wind Energy Conversion System for Maximum Power Point Tracking

DEFF Research Database (Denmark)

Zhao, Haoran; Wu, Qiuwei; Rasmussen, Claus Nygaard

2014-01-01

This paper presents the design of an L1 adaptive controller for maximum power point tracking (MPPT) of a small variable speed Wind Energy Conversion System (WECS). The proposed controller generates the optimal torque command for the vector controlled generator side converter (GSC) based on the wi......) is used to carry out case studies using Matlab/Simulink. The case study results show that the designed L1 adaptive controller has good tracking performance even with unmodeled dynamics and in the presence of parameter uncertainties and unknown disturbances.......This paper presents the design of an L1 adaptive controller for maximum power point tracking (MPPT) of a small variable speed Wind Energy Conversion System (WECS). The proposed controller generates the optimal torque command for the vector controlled generator side converter (GSC) based on the wind...

Lagrangian 3D tracking of fluorescent microscopic objects in motion

Science.gov (United States)

Darnige, T.; Figueroa-Morales, N.; Bohec, P.; Lindner, A.; Clément, E.

2017-05-01

We describe the development of a tracking device, mounted on an epi-fluorescent inverted microscope, suited to obtain time resolved 3D Lagrangian tracks of fluorescent passive or active micro-objects in microfluidic devices. The system is based on real-time image processing, determining the displacement of a x, y mechanical stage to keep the chosen object at a fixed position in the observation frame. The z displacement is based on the refocusing of the fluorescent object determining the displacement of a piezo mover keeping the moving object in focus. Track coordinates of the object with respect to the microfluidic device as well as images of the object are obtained at a frequency of several tenths of Hertz. This device is particularly well adapted to obtain trajectories of motile micro-organisms in microfluidic devices with or without flow.

Oscillatory Adaptive Yaw-Plane Control of Biorobotic Autonomous Underwater Vehicles Using Pectoral-Like Fins

Directory of Open Access Journals (Sweden)

Mugdha S. Naik

2007-01-01

Full Text Available This article considers the control of a biorobotic autonomous underwater vehicle (BAUV in the yaw plane using biologically inspired oscillatory pectoral-like fins of marine animals. The fins are assumed to be oscillating harmonically with a combined linear (sway and angular (yaw motion producing unsteady forces, which are used for fish-like control of BAUVs. Manoeuvring of the BAUV in the yaw plane is accomplished by altering the bias (mean angle of the angular motion of the fin. For the derivation of the adaptive control system, it is assumed that the physical parameters, the hydrodynamic coefficients, and the fin force and moment are not known. A direct adaptive sampled-data control system for the trajectory control of the yaw-angle using only yaw-angle measurement is derived. The parameter adaptation law is based on the normalised gradient scheme. Simulation results for the set point control, sinusoidal trajectory tracking and turning manoeuvres are presented, which show that the control system accomplishes precise trajectory control in spite of the parameter uncertainties.

Globally Stable Adaptive Backstepping Neural Network Control for Uncertain Strict-Feedback Systems With Tracking Accuracy Known a Priori.

Science.gov (United States)

Chen, Weisheng; Ge, Shuzhi Sam; Wu, Jian; Gong, Maoguo

2015-09-01

This paper addresses the problem of globally stable direct adaptive backstepping neural network (NN) tracking control design for a class of uncertain strict-feedback systems under the assumption that the accuracy of the ultimate tracking error is given a priori. In contrast to the classical adaptive backstepping NN control schemes, this paper analyzes the convergence of the tracking error using Barbalat's Lemma via some nonnegative functions rather than the positive-definite Lyapunov functions. Thus, the accuracy of the ultimate tracking error can be determined and adjusted accurately a priori, and the closed-loop system is guaranteed to be globally uniformly ultimately bounded. The main technical novelty is to construct three new n th-order continuously differentiable functions, which are used to design the control law, the virtual control variables, and the adaptive laws. Finally, two simulation examples are given to illustrate the effectiveness and advantages of the proposed control method.

Adaptive Output Tracking Control for Nonlinear Systems with Failed Actuators and Aircraft Flight System Applications

Directory of Open Access Journals (Sweden)

Chuanjing Hou

2015-01-01

Full Text Available An adaptive failure compensation scheme using output feedback is proposed for a class of nonlinear systems with nonlinearities depending on the unmeasured states of systems. Adaptive high-gain K-filters are presented to suppress the nonlinearities while the proposed backstepping adaptive high-gain controller guarantees the stability of the closed-loop system and small tracking errors. Simulation results verify that the adaptive failure compensation scheme is effective.

Ultra-precise tracking control of piezoelectric actuators via a fuzzy hysteresis model.

Science.gov (United States)

Li, Pengzhi; Yan, Feng; Ge, Chuan; Zhang, Mingchao

2012-08-01

In this paper, a novel Takagi-Sugeno (T-S) fuzzy system based model is proposed for hysteresis in piezoelectric actuators. The antecedent and consequent structures of the fuzzy hysteresis model (FHM) can be, respectively, identified on-line through uniform partition approach and recursive least squares (RLS) algorithm. With respect to controller design, the inverse of FHM is used to develop a feedforward controller to cancel out the hysteresis effect. Then a hybrid controller is designed for high-performance tracking. It combines the feedforward controller with a proportional integral differential (PID) controller favourable for stabilization and disturbance compensation. To achieve nanometer-scale tracking precision, the enhanced adaptive hybrid controller is further developed. It uses real-time input and output data to update FHM, thus changing the feedforward controller to suit the on-site hysteresis character of the piezoelectric actuator. Finally, as to 3 cases of 50 Hz sinusoidal, multiple frequency sinusoidal and 50 Hz triangular trajectories tracking, experimental results demonstrate the efficiency of the proposed controllers. Especially, being only 0.35% of the maximum desired displacement, the maximum error of 50 Hz sinusoidal tracking is greatly reduced to 5.8 nm, which clearly shows the ultra-precise nanometer-scale tracking performance of the developed adaptive hybrid controller.

Segmenting Trajectories by Movement States

NARCIS (Netherlands)

Buchin, M.; Kruckenberg, H.; Kölzsch, A.; Timpf, S.; Laube, P.

2013-01-01

Dividing movement trajectories according to different movement states of animals has become a challenge in movement ecology, as well as in algorithm development. In this study, we revisit and extend a framework for trajectory segmentation based on spatio-temporal criteria for this purpose. We adapt

Target Response Adaptation for Correlation Filter Tracking

KAUST Repository

Bibi, Adel Aamer

2016-09-16

Most correlation filter (CF) based trackers utilize the circulant structure of the training data to learn a linear filter that best regresses this data to a hand-crafted target response. These circularly shifted patches are only approximations to actual translations in the image, which become unreliable in many realistic tracking scenarios including fast motion, occlusion, etc. In these cases, the traditional use of a single centered Gaussian as the target response impedes tracker performance and can lead to unrecoverable drift. To circumvent this major drawback, we propose a generic framework that can adaptively change the target response from frame to frame, so that the tracker is less sensitive to the cases where circular shifts do not reliably approximate translations. To do that, we reformulate the underlying optimization to solve for both the filter and target response jointly, where the latter is regularized by measurements made using actual translations. This joint problem has a closed form solution and thus allows for multiple templates, kernels, and multi-dimensional features. Extensive experiments on the popular OTB100 benchmark show that our target adaptive framework can be combined with many CF trackers to realize significant overall performance improvement (ranging from 3 %-13.5% in precision and 3.2 %-13% in accuracy), especially in categories where this adaptation is necessary (e.g. fast motion, motion blur, etc.). © Springer International Publishing AG 2016.

ADAPTIVE PARAMETER ESTIMATION OF PERSON RECOGNITION MODEL IN A STOCHASTIC HUMAN TRACKING PROCESS

OpenAIRE

W. Nakanishi; T. Fuse; T. Ishikawa

2015-01-01

This paper aims at an estimation of parameters of person recognition models using a sequential Bayesian filtering method. In many human tracking method, any parameters of models used for recognize the same person in successive frames are usually set in advance of human tracking process. In real situation these parameters may change according to situation of observation and difficulty level of human position prediction. Thus in this paper we formulate an adaptive parameter estimation ...

Data-based control trajectory planning for nonlinear systems

International Nuclear Information System (INIS)

Rhodes, C.; Morari, M.; Tsimring, L.S.; Rulkov, N.F.

1997-01-01

An open-loop trajectory planning algorithm is presented for computing an input sequence that drives an input-output system such that a reference trajectory is tracked. The algorithm utilizes only input-output data from the system to determine the proper control sequence, and does not require a mathematical or identified description of the system dynamics. From the input-output data, the controlled input trajectory is calculated in a open-quotes one-step-aheadclose quotes fashion using local modeling. Since the algorithm is calculated in this fashion, the output trajectories to be tracked can be nonperiodic. The algorithm is applied to a driven Lorenz system, and an experimental electrical circuit and the results are analyzed. Issues of stability associated with the implementation of this open-loop scheme are also examined using an analytic example of a driven Hacute enon map, problems associated with inverse controllers are illustrated, and solutions to these problems are proposed. copyright 1997 The American Physical Society

Multi-objective trajectory optimization of Space Manoeuvre Vehicle using adaptive differential evolution and modified game theory

Science.gov (United States)

Chai, Runqi; Savvaris, Al; Tsourdos, Antonios; Chai, Senchun

2017-07-01

Highly constrained trajectory optimization for Space Manoeuvre Vehicles (SMV) is a challenging problem. In practice, this problem becomes more difficult when multiple mission requirements are taken into account. Because of the nonlinearity in the dynamic model and even the objectives, it is usually hard for designers to generate a compromised trajectory without violating strict path and box constraints. In this paper, a new multi-objective SMV optimal control model is formulated and parameterized using combined shooting-collocation technique. A modified game theory approach, coupled with an adaptive differential evolution algorithm, is designed in order to generate the pareto front of the multi-objective trajectory optimization problem. In addition, to improve the quality of obtained solutions, a control logic is embedded in the framework of the proposed approach. Several existing multi-objective evolutionary algorithms are studied and compared with the proposed method. Simulation results indicate that without driving the solution out of the feasible region, the proposed method can perform better in terms of convergence ability and convergence speed than its counterparts. Moreover, the quality of the pareto set generated using the proposed method is higher than other multi-objective evolutionary algorithms, which means the newly proposed algorithm is more attractive for solving multi-criteria SMV trajectory planning problem.

Tracking error constrained robust adaptive neural prescribed performance control for flexible hypersonic flight vehicle

Directory of Open Access Journals (Sweden)

Zhonghua Wu

2017-02-01

Full Text Available A robust adaptive neural control scheme based on a back-stepping technique is developed for the longitudinal dynamics of a flexible hypersonic flight vehicle, which is able to ensure the state tracking error being confined in the prescribed bounds, in spite of the existing model uncertainties and actuator constraints. Minimal learning parameter technique–based neural networks are used to estimate the model uncertainties; thus, the amount of online updated parameters is largely lessened, and the prior information of the aerodynamic parameters is dispensable. With the utilization of an assistant compensation system, the problem of actuator constraint is overcome. By combining the prescribed performance function and sliding mode differentiator into the neural back-stepping control design procedure, a composite state tracking error constrained adaptive neural control approach is presented, and a new type of adaptive law is constructed. As compared with other adaptive neural control designs for hypersonic flight vehicle, the proposed composite control scheme exhibits not only low-computation property but also strong robustness. Finally, two comparative simulations are performed to demonstrate the robustness of this neural prescribed performance controller.

Adaptive Kalman Filter Applied to Vision Based Head Gesture Tracking for Playing Video Games

Directory of Open Access Journals (Sweden)

Mohammadreza Asghari Oskoei

2017-11-01

Full Text Available This paper proposes an adaptive Kalman filter (AKF to improve the performance of a vision-based human machine interface (HMI applied to a video game. The HMI identifies head gestures and decodes them into corresponding commands. Face detection and feature tracking algorithms are used to detect optical flow produced by head gestures. Such approaches often fail due to changes in head posture, occlusion and varying illumination. The adaptive Kalman filter is applied to estimate motion information and reduce the effect of missing frames in a real-time application. Failure in head gesture tracking eventually leads to malfunctioning game control, reducing the scores achieved, so the performance of the proposed vision-based HMI is examined using a game scoring mechanism. The experimental results show that the proposed interface has a good response time, and the adaptive Kalman filter improves the game scores by ten percent.

Observer-based design of set-point tracking adaptive controllers for nonlinear chaotic systems

International Nuclear Information System (INIS)

Khaki-Sedigh, A.; Yazdanpanah-Goharrizi, A.

2006-01-01

A gradient based approach for the design of set-point tracking adaptive controllers for nonlinear chaotic systems is presented. In this approach, Lyapunov exponents are used to select the controller gain. In the case of unknown or time varying chaotic plants, the Lyapunov exponents may vary during the plant operation. In this paper, an effective adaptive strategy is used for online identification of Lyapunov exponents and adaptive control of nonlinear chaotic plants. Also, a nonlinear observer for estimation of the states is proposed. Simulation results are provided to show the effectiveness of the proposed methodology

Observer-based design of set-point tracking adaptive controllers for nonlinear chaotic systems

Energy Technology Data Exchange (ETDEWEB)

Khaki-Sedigh, A. [Department of Electrical Engineering, K.N. Toosi University of Technology, Sayyed Khandan Bridge, Shariati Street, Tehran 16314 (Iran, Islamic Republic of)]. E-mail: sedigh@kntu.ac.ir; Yazdanpanah-Goharrizi, A. [Department of Electrical Engineering, K.N. Toosi University of Technology, Sayyed Khandan Bridge, Shariati Street, Tehran 16314 (Iran, Islamic Republic of)]. E-mail: yazdanpanah@ee.kntu.ac.ir

2006-09-15

A gradient based approach for the design of set-point tracking adaptive controllers for nonlinear chaotic systems is presented. In this approach, Lyapunov exponents are used to select the controller gain. In the case of unknown or time varying chaotic plants, the Lyapunov exponents may vary during the plant operation. In this paper, an effective adaptive strategy is used for online identification of Lyapunov exponents and adaptive control of nonlinear chaotic plants. Also, a nonlinear observer for estimation of the states is proposed. Simulation results are provided to show the effectiveness of the proposed methodology.

New Low Cost Structure for Dual Axis Mount Solar Tracking System Using Adaptive Solar Sensor

DEFF Research Database (Denmark)

Argeseanu, Alin; Ritchie, Ewen; Leban, Krisztina Monika

2010-01-01

A solar tracking system is designed to optimize the operation of solar energy receivers. The objective of this paper is proposing a new tracking system structure with two axis. The success strategy of this new project focuses on the economical analysis of solar energy. Therefore it is important...... to determine the most cost effective design, to consider the costs of production and maintenance, and operating. The proposed tracking system uses a new solar sensor position with an adaptive feature....

Direct adaptive control of manipulators in Cartesian space

Science.gov (United States)

Seraji, H.

1987-01-01

A new adaptive-control scheme for direct control of manipulator end effector to achieve trajectory tracking in Cartesian space is developed in this article. The control structure is obtained from linear multivariable theory and is composed of simple feedforward and feedback controllers and an auxiliary input. The direct adaptation laws are derived from model reference adaptive control theory and are not based on parameter estimation of the robot model. The utilization of adaptive feedforward control and the inclusion of auxiliary input are novel features of the present scheme and result in improved dynamic performance over existing adaptive control schemes. The adaptive controller does not require the complex mathematical model of the robot dynamics or any knowledge of the robot parameters or the payload, and is computationally fast for on-line implementation with high sampling rates. The control scheme is applied to a two-link manipulator for illustration.

Longitudinal trajectories of intellectual and adaptive functioning in adolescents and adults with Williams syndrome.

Science.gov (United States)

Fisher, M H; Lense, M D; Dykens, E M

2016-10-01

Williams syndrome (WS) is associated with a distinct cognitive-behavioural phenotype including mild to moderate intellectual disability, visual-spatial deficits, hypersociability, inattention and anxiety. Researchers typically characterise samples of individuals with WS by their intellectual functioning and adaptive behaviour. Because of the low prevalence of the syndrome, researchers often include participants with WS across a broad age range throughout childhood and adulthood and assume participants demonstrate consistent cognitive development across ages. Indeed, IQ scores are generally stable for children and adolescents with WS, although there are significant individual differences. It is less clear whether this pattern of stable intellectual ability persists into adulthood. Furthermore, while adaptive behaviour is an important indicator of an individual's ability to apply their conceptual skills to everyday functioning, conflicting findings on the trajectories of adaptive behaviour in adolescents and adults with WS have been reported. The current study examined longitudinal profiles of cognitive and adaptive functioning in adolescents and adults with WS. To examine cognitive functioning, participants included 52 individuals with WS (51.9% men) who were assessed with the Kaufman Brief Intelligence Test, 2nd edition (KBIT-2) between two and seven times. At their first assessment, participants had a mean age of 25.4 years (SD = 8.4), ranging in age from 14.2 to 48.9 years. To assess adaptive behaviour, participants included a subset of 28 individuals with WS whose parents completed the Vineland Adaptive Behavior Scale, 2nd edition (VABS-II) between two and five times. At their initial administration, participants ranged from 17.1-40.2 years of age, with a mean age of 26.5 years (SD = 7.3). A series of multilevel models were used to examine changes in KBIT-2 Composite IQ, Verbal IQ and Nonverbal IQ standard scores over time, as well as the

Optimized Adaptive Perturb and Observe Maximum Power Point Tracking Control for Photovoltaic Generation

Directory of Open Access Journals (Sweden)

Luigi Piegari

2015-04-01

Full Text Available The power extracted from PV arrays is usually maximized using maximum power point tracking algorithms. One of the most widely used techniques is the perturb & observe algorithm, which periodically perturbs the operating point of the PV array, sometime with an adaptive perturbation step, and compares the PV power before and after the perturbation. This paper analyses the most suitable perturbation step to optimize maximum power point tracking performance and suggests a design criterion to select the parameters of the controller. Using this proposed adaptive step, the MPPT perturb & observe algorithm achieves an excellent dynamic response by adapting the perturbation step to the actual operating conditions of the PV array. The proposed algorithm has been validated and tested in a laboratory using a dual input inductor push-pull converter. This particular converter topology is an efficient interface to boost the low voltage of PV arrays and effectively control the power flow when input or output voltages are variable. The experimental results have proved the superiority of the proposed algorithm in comparison of traditional perturb & observe and incremental conductance techniques.

Adaptive twisting sliding mode algorithm for hypersonic reentry vehicle attitude control based on finite-time observer.

Science.gov (United States)

Guo, Zongyi; Chang, Jing; Guo, Jianguo; Zhou, Jun

2018-06-01

This paper focuses on the adaptive twisting sliding mode control for the Hypersonic Reentry Vehicles (HRVs) attitude tracking issue. The HRV attitude tracking model is transformed into the error dynamics in matched structure, whereas an unmeasurable state is redefined by lumping the existing unmatched disturbance with the angular rate. Hence, an adaptive finite-time observer is used to estimate the unknown state. Then, an adaptive twisting algorithm is proposed for systems subject to disturbances with unknown bounds. The stability of the proposed observer-based adaptive twisting approach is guaranteed, and the case of noisy measurement is analyzed. Also, the developed control law avoids the aggressive chattering phenomenon of the existing adaptive twisting approaches because the adaptive gains decrease close to the disturbance once the trajectories reach the sliding surface. Finally, numerical simulations on the attitude control of the HRV are conducted to verify the effectiveness and benefit of the proposed approach. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

A new approach to motion control of torque-constrained manipulators by using time-scaling of reference trajectories

Energy Technology Data Exchange (ETDEWEB)

Moreno-Valenzuela, Javier; Orozco-Manriquez, Ernesto [Digital del IPN, CITEDI-IPN, Tijuana, (Mexico)

2009-12-15

We introduce a control scheme based on using a trajectory tracking controller and an algorithm for on-line time scaling of the reference trajectories. The reference trajectories are time-scaled according to the measured tracking errors and the detected torque/acceleration saturation. Experiments are presented to illustrate the advantages of the proposed approach

A new approach to motion control of torque-constrained manipulators by using time-scaling of reference trajectories

International Nuclear Information System (INIS)

Moreno-Valenzuela, Javier; Orozco-Manriquez, Ernesto

2009-01-01

We introduce a control scheme based on using a trajectory tracking controller and an algorithm for on-line time scaling of the reference trajectories. The reference trajectories are time-scaled according to the measured tracking errors and the detected torque/acceleration saturation. Experiments are presented to illustrate the advantages of the proposed approach

A Tracking Analyst for large 3D spatiotemporal data from multiple sources (case study: Tracking volcanic eruptions in the atmosphere)

Science.gov (United States)

Gad, Mohamed A.; Elshehaly, Mai H.; Gračanin, Denis; Elmongui, Hicham G.

2018-02-01

This research presents a novel Trajectory-based Tracking Analyst (TTA) that can track and link spatiotemporally variable data from multiple sources. The proposed technique uses trajectory information to determine the positions of time-enabled and spatially variable scatter data at any given time through a combination of along trajectory adjustment and spatial interpolation. The TTA is applied in this research to track large spatiotemporal data of volcanic eruptions (acquired using multi-sensors) in the unsteady flow field of the atmosphere. The TTA enables tracking injections into the atmospheric flow field, the reconstruction of the spatiotemporally variable data at any desired time, and the spatiotemporal join of attribute data from multiple sources. In addition, we were able to create a smooth animation of the volcanic ash plume at interactive rates. The initial results indicate that the TTA can be applied to a wide range of multiple-source data.

Cosmic ray particle dosimetry and trajectory tracing

International Nuclear Information System (INIS)

Cruty, M.R.; Benton, E.V.; Turnbill, C.E.; Philpott, D.E.

1975-01-01

Five pocket mice (Perognathus longimembris) were flown on Apollo XVII, each with a solid-state (plastic) nuclear track detector implanted beneath its scalp. The subscalp detectors were sensitive to HZE cosmic ray particles with a LET greater than or approximately equal to 0.15 million electron volts per micrometer (MeV/micron). A critical aspect of the dosimetry of the experiment involved tracing individual particle trajectories through each mouse head from particle tracks registered in the individual subscalp detectors, thereby establishing a one-to-one correspondence between a trajectory location in the tissue and the presence or absence of a lesion. The other major aspect was the identification of each registered particle. An average of 16 particles with Z greater than or equal to 6 and 2.2 particles with Z greater than or equal to 20 were found per detector. The track density, 29 tracks/sq cm, when adjusted for detection volume, was in agreement with the photographic emulsion data from an area dosimeter located next to the flight package

Computer modeling of oil spill trajectories with a high accuracy method

International Nuclear Information System (INIS)

Garcia-Martinez, Reinaldo; Flores-Tovar, Henry

1999-01-01

This paper proposes a high accuracy numerical method to model oil spill trajectories using a particle-tracking algorithm. The Euler method, used to calculate oil trajectories, can give adequate solutions in most open ocean applications. However, this method may not predict accurate particle trajectories in certain highly non-uniform velocity fields near coastal zones or in river problems. Simple numerical experiments show that the Euler method may also introduce artificial numerical dispersion that could lead to overestimation of spill areas. This article proposes a fourth-order Runge-Kutta method with fourth-order velocity interpolation to calculate oil trajectories that minimise these problems. The algorithm is implemented in the OilTrack model to predict oil trajectories following the 'Nissos Amorgos' oil spill accident that occurred in the Gulf of Venezuela in 1997. Despite lack of adequate field information, model results compare well with observations in the impacted area. (Author)

Adaptive estimation for control of uncertain nonlinear systems with applications to target tracking

Science.gov (United States)

Madyastha, Venkatesh Kattigari

2005-08-01

Design of nonlinear observers has received considerable attention since the early development of methods for linear state estimation. The most popular approach is the extended Kalman filter (EKF), that goes through significant degradation in the presence of nonlinearities, particularly if unmodeled dynamics are coupled to the process and the measurement. For uncertain nonlinear systems, adaptive observers have been introduced to estimate the unknown state variables where no priori information about the unknown parameters is available. While establishing global results, these approaches are applicable only to systems transformable to output feedback form. Over the recent years, neural network (NN) based identification and estimation schemes have been proposed that relax the assumptions on the system at the price of sacrificing on the global nature of the results. However, most of the NN based adaptive observer approaches in the literature require knowledge of the full dimension of the system, therefore may not be suitable for systems with unmodeled dynamics. We first propose a novel approach to nonlinear state estimation from the perspective of augmenting a linear time invariant observer with an adaptive element. The class of nonlinear systems treated here are finite but of otherwise unknown dimension. The objective is to improve the performance of the linear observer when applied to a nonlinear system. The approach relies on the ability of the NNs to approximate the unknown dynamics from finite time histories of available measurements. Next we investigate nonlinear state estimation from the perspective of adaptively augmenting an existing time varying observer, such as an EKF. EKFs find their applications mostly in target tracking problems. The proposed approaches are robust to unmodeled dynamics, including unmodeled disturbances. Lastly, we consider the problem of adaptive estimation in the presence of feedback control for a class of uncertain nonlinear systems

Dynamic optimization and adaptive controller design

Science.gov (United States)

Inamdar, S. R.

2010-10-01

In this work I present a new type of controller which is an adaptive tracking controller which employs dynamic optimization for optimizing current value of controller action for the temperature control of nonisothermal continuously stirred tank reactor (CSTR). We begin with a two-state model of nonisothermal CSTR which are mass and heat balance equations and then add cooling system dynamics to eliminate input multiplicity. The initial design value is obtained using local stability of steady states where approach temperature for cooling action is specified as a steady state and a design specification. Later we make a correction in the dynamics where material balance is manipulated to use feed concentration as a system parameter as an adaptive control measure in order to avoid actuator saturation for the main control loop. The analysis leading to design of dynamic optimization based parameter adaptive controller is presented. The important component of this mathematical framework is reference trajectory generation to form an adaptive control measure.

Rotational Kinematics Model Based Adaptive Particle Filter for Robust Human Tracking in Thermal Omnidirectional Vision

Directory of Open Access Journals (Sweden)

Yazhe Tang

2015-01-01

Full Text Available This paper presents a novel surveillance system named thermal omnidirectional vision (TOV system which can work in total darkness with a wild field of view. Different to the conventional thermal vision sensor, the proposed vision system exhibits serious nonlinear distortion due to the effect of the quadratic mirror. To effectively model the inherent distortion of omnidirectional vision, an equivalent sphere projection is employed to adaptively calculate parameterized distorted neighborhood of an object in the image plane. With the equivalent projection based adaptive neighborhood calculation, a distortion-invariant gradient coding feature is proposed for thermal catadioptric vision. For robust tracking purpose, a rotational kinematic modeled adaptive particle filter is proposed based on the characteristic of omnidirectional vision, which can handle multiple movements effectively, including the rapid motions. Finally, the experiments are given to verify the performance of the proposed algorithm for human tracking in TOV system.

System of automized determination of charged particle trajectories in extended magnetic fields

International Nuclear Information System (INIS)

Toumanian, A.R.

1981-01-01

An automized system for the determination of particle trajectories by the floating current-carrying wire method is described. The system is able to determine the charged particle trajectories with the energy above 100 MeV in magnetic systems of any configuration and with track extent up to several tens metres with momentum resolution up to 3.10 -4 . The system efficiency makes 1500 tracks/hour on the average [ru

Forward and Inverse Predictive Model for the Trajectory Tracking Control of a Lower Limb Exoskeleton for Gait Rehabilitation: Simulation modelling analysis

Science.gov (United States)

Zakaria, M. A.; Majeed, A. P. P. A.; Taha, Z.; Alim, M. M.; Baarath, K.

2018-03-01

The movement of a lower limb exoskeleton requires a reasonably accurate control method to allow for an effective gait therapy session to transpire. Trajectory tracking is a nontrivial means of passive rehabilitation technique to correct the motion of the patients’ impaired limb. This paper proposes an inverse predictive model that is coupled together with the forward kinematics of the exoskeleton to estimate the behaviour of the system. A conventional PID control system is used to converge the required joint angles based on the desired input from the inverse predictive model. It was demonstrated through the present study, that the inverse predictive model is capable of meeting the trajectory demand with acceptable error tolerance. The findings further suggest the ability of the predictive model of the exoskeleton to predict a correct joint angle command to the system.

Understanding Climate Adaptation on Public Lands in the Upper Midwest: Implications for Monitoring and Tracking Progress

Science.gov (United States)

Anhalt-Depies, Christine M.; Knoot, Tricia Gorby; Rissman, Adena R.; Sharp, Anthony K.; Martin, Karl J.

2016-05-01

There are limited examples of efforts to systematically monitor and track climate change adaptation progress in the context of natural resource management, despite substantial investments in adaptation initiatives. To better understand the status of adaptation within state natural resource agencies, we utilized and problematized a rational decision-making framework to characterize adaptation at the level of public land managers in the Upper Midwest. We conducted in-depth interviews with 29 biologists and foresters to provide an understanding of managers' experiences with, and perceptions of, climate change impacts, efforts towards planning for climate change, and a full range of actions implemented to address climate change. While the majority of managers identified climate change impacts affecting their region, they expressed significant uncertainty in interpreting those signals. Just under half of managers indicated planning efforts are underway, although most planning is remote from local management. Actions already implemented include both forward-looking measures and those aimed at coping with current impacts. In addition, cross-scale dynamics emerged as an important theme related to the overall adaptation process. The results hold implications for tracking future progress on climate change adaptation. Common definitions or measures of adaptation (e.g., presence of planning documents) may need to be reassessed for applicability at the level of public land managers.

A model of curved saccade trajectories: spike rate adaptation in the brainstem as the cause of deviation away.

Science.gov (United States)

Kruijne, Wouter; Van der Stigchel, Stefan; Meeter, Martijn

2014-03-01

The trajectory of saccades to a target is often affected whenever there is a distractor in the visual field. Distractors can cause a saccade to deviate towards their location or away from it. The oculomotor mechanisms that produce deviation towards distractors have been thoroughly explored in behavioral, neurophysiological and computational studies. The mechanisms underlying deviation away, on the other hand, remain unclear. Behavioral findings suggest a mechanism of spatially focused, top-down inhibition in a saccade map, and deviation away has become a tool to investigate such inhibition. However, this inhibition hypothesis has little neuroanatomical or neurophysiological support, and recent findings go against it. Here, we propose that deviation away results from an unbalanced saccade drive from the brainstem, caused by spike rate adaptation in brainstem long-lead burst neurons. Adaptation to stimulation in the direction of the distractor results in an unbalanced drive away from it. An existing model of the saccade system was extended with this theory. The resulting model simulates a wide range of findings on saccade trajectories, including findings that have classically been interpreted to support inhibition views. Furthermore, the model replicated the effect of saccade latency on deviation away, but predicted this effect would be absent with large (400 ms) distractor-target onset asynchrony. This prediction was confirmed in an experiment, which demonstrates that the theory both explains classical findings on saccade trajectories and predicts new findings. Copyright © 2014 Elsevier Inc. All rights reserved.

Optimal spectral tracking--adapting to dynamic regime change.

Science.gov (United States)

Brittain, John-Stuart; Halliday, David M

2011-01-30

Real world data do not always obey the statistical restraints imposed upon them by sophisticated analysis techniques. In spectral analysis for instance, an ergodic process--the interchangeability of temporal for spatial averaging--is assumed for a repeat-trial design. Many evolutionary scenarios, such as learning and motor consolidation, do not conform to such linear behaviour and should be approached from a more flexible perspective. To this end we previously introduced the method of optimal spectral tracking (OST) in the study of trial-varying parameters. In this extension to our work we modify the OST routines to provide an adaptive implementation capable of reacting to dynamic transitions in the underlying system state. In so doing, we generalise our approach to characterise both slow-varying and rapid fluctuations in time-series, simultaneously providing a metric of system stability. The approach is first applied to a surrogate dataset and compared to both our original non-adaptive solution and spectrogram approaches. The adaptive OST is seen to display fast convergence and desirable statistical properties. All three approaches are then applied to a neurophysiological recording obtained during a study on anaesthetic monitoring. Local field potentials acquired from the posterior hypothalamic region of a deep brain stimulation patient undergoing anaesthesia were analysed. The characterisation of features such as response delay, time-to-peak and modulation brevity are considered. Copyright © 2010 Elsevier B.V. All rights reserved.

Direct Adaptive Tracking Control for a Class of Pure-Feedback Stochastic Nonlinear Systems Based on Fuzzy-Approximation

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Huanqing Wang

2014-01-01

Full Text Available The problem of fuzzy-based direct adaptive tracking control is considered for a class of pure-feedback stochastic nonlinear systems. During the controller design, fuzzy logic systems are used to approximate the packaged unknown nonlinearities, and then a novel direct adaptive controller is constructed via backstepping technique. It is shown that the proposed controller guarantees that all the signals in the closed-loop system are bounded in probability and the tracking error eventually converges to a small neighborhood around the origin in the sense of mean quartic value. The main advantages lie in that the proposed controller structure is simpler and only one adaptive parameter needs to be updated online. Simulation results are used to illustrate the effectiveness of the proposed approach.

Lossy compression of TPC data and trajectory tracking efficiency for the ALICE experiment

CERN Document Server

Nicolaucig, A; Mattavelli, M

2003-01-01

In this paper a quasi-lossless algorithm for the on-line compression of the data generated by the Time Projection Chamber (TPC) detector of the ALICE experiment at CERN is described. The algorithm is based on a lossy source code modeling technique, i.e. it is based on a source model which is lossy if samples of the TPC signal are considered one by one; conversely, the source model is lossless or quasi-lossless if some physical quantities that are of main interest for the experiment are considered. These quantities are the area and the location of the center of mass of each TPC signal pulse, representing the pulse charge and the time localization of the pulse. So as to evaluate the consequences of the error introduced by the lossy compression process, the results of the trajectory tracking algorithms that process data off-line after the experiment are analyzed, in particular, versus their sensibility to the noise introduced by the compression. Two different versions of these off- line algorithms are described,...

Sliding-mode control combined with improved adaptive feedforward for wafer scanner

Science.gov (United States)

Li, Xiaojie; Wang, Yiguang

2018-03-01

In this paper, a sliding-mode control method combined with improved adaptive feedforward is proposed for wafer scanner to improve the tracking performance of the closed-loop system. Particularly, In addition to the inverse model, the nonlinear force ripple effect which may degrade the tracking accuracy of permanent magnet linear motor (PMLM) is considered in the proposed method. The dominant position periodicity of force ripple is determined by using the Fast Fourier Transform (FFT) analysis for experimental data and the improved feedforward control is achieved by the online recursive least-squares (RLS) estimation of the inverse model and the force ripple. The improved adaptive feedforward is given in a general form of nth-order model with force ripple effect. This proposed method is motivated by the motion controller design of the long-stroke PMLM and short-stroke voice coil motor for wafer scanner. The stability of the closed-loop control system and the convergence of the motion tracking are guaranteed by the proposed sliding-mode feedback and adaptive feedforward methods theoretically. Comparative experiments on a precision linear motion platform can verify the correctness and effectiveness of the proposed method. The experimental results show that comparing to traditional method the proposed one has better performance of rapidity and robustness, especially for high speed motion trajectory. And, the improvements on both tracking accuracy and settling time can be achieved.

Dynamic Surface Adaptive Robust Control of Unmanned Marine Vehicles with Disturbance Observer

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Pengchao Zhang

2018-01-01

Full Text Available This paper presents a dynamic surface adaptive robust control method with disturbance observer for unmanned marine vehicles (UMV. It uses adaptive law to estimate and compensate the disturbance observer error. Dynamic surface is introduced to solve the “differential explosion” caused by the virtual control derivation in traditional backstepping method. The final controlled system is proved to be globally uniformly bounded based on Lyapunov stability theory. Simulation results illustrate the effectiveness of the proposed controller, which can realize the three-dimensional trajectory tracking for UMV with the systematic uncertainty and time-varying disturbances.

Track reconstruction in CMS high luminosity environment

CERN Document Server

AUTHOR|(CDS)2067159

2016-01-01

The CMS tracker is the largest silicon detector ever built, covering 200 square meters and providing an average of 14 high-precision measurements per track. Tracking is essential for the reconstruction of objects like jets, muons, electrons and tau leptons starting from the raw data from the silicon pixel and strip detectors. Track reconstruction is widely used also at trigger level as it improves objects tagging and resolution.The CMS tracking code is organized in several levels, known as iterative steps, each optimized to reconstruct a class of particle trajectories, as the ones of particles originating from the primary vertex or displaced tracks from particles resulting from secondary vertices. Each iterative step consists of seeding, pattern recognition and fitting by a kalman filter, and a final filtering and cleaning. Each subsequent step works on hits not yet associated to a reconstructed particle trajectory.The CMS tracking code is continuously evolving to make the reconstruction computing load compat...

Track reconstruction in CMS high luminosity environment

CERN Document Server

Goetzmann, Christophe

2014-01-01

The CMS tracker is the largest silicon detector ever built, covering 200 square meters and providing an average of 14 high-precision measurements per track. Tracking is essential for the reconstruction of objects like jets, muons, electrons and tau leptons starting from the raw data from the silicon pixel and strip detectors. Track reconstruction is widely used also at trigger level as it improves objects tagging and resolution.The CMS tracking code is organized in several levels, known as iterative steps, each optimized to reconstruct a class of particle trajectories, as the ones of particles originating from the primary vertex or displaced tracks from particles resulting from secondary vertices. Each iterative step consists of seeding, pattern recognition and fitting by a kalman filter, and a final filtering and cleaning. Each subsequent step works on hits not yet associated to a reconstructed particle trajectory.The CMS tracking code is continuously evolving to make the reconstruction computing load compat...

LHCb: The LHCb tracking concept and performance

CERN Multimedia

Rodrigues, E

2009-01-01

The LHCb tracking system is designed to reconstruct charged particle trajectories in the forward spectrometer, in view of high precision studies of CP-violating phenomena and searches for rare b-hadron decays at the LHC. The system is composed of four major subdetectors and a dedicated magnet, providing an excellent momentum resolution just above 0.4%. The tracking model is based on the innovative trajectories concept introduced by the BaBar collaboration to reconstruct and fit the tracks, and has been further developed and improved. It is now able to cope with realistic geometries and misalignments in a sophisticated, robust and detector-independent way. The LHCb tracking concept including the interplay of various complementary pattern recognition algorithms and the bi-directional Kalman fitter will be described. The current performance of the tracking, based on the latest simulations, will be presented. Recent results obtained with the first LHC beam tracks from injection tests will be discussed.

Picking Robot Arm Trajectory Planning Method

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Zhang Zhiyong

2014-01-01

Full Text Available The picking robot arm is scheduled to complete picking tasks in the working space, to overcome the shaking vibration to improve the picking stability, its movement should follow specific consistence trajectory points. Usually we should give definite multiple feature picking points, map their inverse kinematics to the joint space, establish motion equation for the corresponding point in the joint space, then follow these equations motion for the interpolation on the joint so that we can meet the movement requirements. Trajectory planning is decisive significance for accuracy and stability of controlling robot arm. The key issue that picking arm complete picking task will be come true by trajectory planning, namely, robot arm track the desired trajectory. which based on kinematics and statics picking analysis in a joint space according to the requirements of picking tasks, and obtain the position and orientation for picking robot arm, study and calculate the theory of trajectory parameters timely.

Adaptive track scheduling to optimize concurrency and vectorization in GeantV

International Nuclear Information System (INIS)

Apostolakis, J; Brun, R; Carminati, F; Gheata, A; Novak, M; Wenzel, S; Bandieramonte, M; Bitzes, G; Canal, P; Elvira, V D; Jun, S Y; Lima, G; Licht, J C De Fine; Duhem, L; Sehgal, R; Shadura, O

2015-01-01

The GeantV project is focused on the R and D of new particle transport techniques to maximize parallelism on multiple levels, profiting from the use of both SIMD instructions and co-processors for the CPU-intensive calculations specific to this type of applications. In our approach, vectors of tracks belonging to multiple events and matching different locality criteria must be gathered and dispatched to algorithms having vector signatures. While the transport propagates tracks and changes their individual states, data locality becomes harder to maintain. The scheduling policy has to be changed to maintain efficient vectors while keeping an optimal level of concurrency. The model has complex dynamics requiring tuning the thresholds to switch between the normal regime and special modes, i.e. prioritizing events to allow flushing memory, adding new events in the transport pipeline to boost locality, dynamically adjusting the particle vector size or switching between vector to single track mode when vectorization causes only overhead. This work requires a comprehensive study for optimizing these parameters to make the behaviour of the scheduler self-adapting, presenting here its initial results. (paper)

Adaptive Disturbance Tracking Theory with State Estimation and State Feedback for Region II Control of Large Wind Turbines

Science.gov (United States)

Balas, Mark J.; Thapa Magar, Kaman S.; Frost, Susan A.

2013-01-01

A theory called Adaptive Disturbance Tracking Control (ADTC) is introduced and used to track the Tip Speed Ratio (TSR) of 5 MW Horizontal Axis Wind Turbine (HAWT). Since ADTC theory requires wind speed information, a wind disturbance generator model is combined with lower order plant model to estimate the wind speed as well as partial states of the wind turbine. In this paper, we present a proof of stability and convergence of ADTC theory with lower order estimator and show that the state feedback can be adaptive.

Handling Trajectory Uncertainties for Airborne Conflict Management

Science.gov (United States)

Barhydt, Richard; Doble, Nathan A.; Karr, David; Palmer, Michael T.

2005-01-01

Airborne conflict management is an enabling capability for NASA's Distributed Air-Ground Traffic Management (DAG-TM) concept. DAGTM has the goal of significantly increasing capacity within the National Airspace System, while maintaining or improving safety. Under DAG-TM, autonomous aircraft maintain separation from each other and from managed aircraft unequipped for autonomous flight. NASA Langley Research Center has developed the Autonomous Operations Planner (AOP), an onboard decision support system that provides airborne conflict management (ACM) and strategic flight planning support for autonomous aircraft pilots. The AOP performs conflict detection, prevention, and resolution from nearby traffic aircraft and area hazards. Traffic trajectory information is assumed to be provided by Automatic Dependent Surveillance Broadcast (ADS-B). Reliable trajectory prediction is a key capability for providing effective ACM functions. Trajectory uncertainties due to environmental effects, differences in aircraft systems and performance, and unknown intent information lead to prediction errors that can adversely affect AOP performance. To accommodate these uncertainties, the AOP has been enhanced to create cross-track, vertical, and along-track buffers along the predicted trajectories of both ownship and traffic aircraft. These buffers will be structured based on prediction errors noted from previous simulations such as a recent Joint Experiment between NASA Ames and Langley Research Centers and from other outside studies. Currently defined ADS-B parameters related to navigation capability, trajectory type, and path conformance will be used to support the algorithms that generate the buffers.

Adaptive Probabilistic Tracking Embedded in Smart Cameras for Distributed Surveillance in a 3D Model

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Sven Fleck

2006-12-01

Full Text Available Tracking applications based on distributed and embedded sensor networks are emerging today, both in the fields of surveillance and industrial vision. Traditional centralized approaches have several drawbacks, due to limited communication bandwidth, computational requirements, and thus limited spatial camera resolution and frame rate. In this article, we present network-enabled smart cameras for probabilistic tracking. They are capable of tracking objects adaptively in real time and offer a very bandwidthconservative approach, as the whole computation is performed embedded in each smart camera and only the tracking results are transmitted, which are on a higher level of abstraction. Based on this, we present a distributed surveillance system. The smart cameras' tracking results are embedded in an integrated 3D environment as live textures and can be viewed from arbitrary perspectives. Also a georeferenced live visualization embedded in Google Earth is presented.

Adaptive Probabilistic Tracking Embedded in Smart Cameras for Distributed Surveillance in a 3D Model

Directory of Open Access Journals (Sweden)

Fleck Sven

2007-01-01

Full Text Available Tracking applications based on distributed and embedded sensor networks are emerging today, both in the fields of surveillance and industrial vision. Traditional centralized approaches have several drawbacks, due to limited communication bandwidth, computational requirements, and thus limited spatial camera resolution and frame rate. In this article, we present network-enabled smart cameras for probabilistic tracking. They are capable of tracking objects adaptively in real time and offer a very bandwidthconservative approach, as the whole computation is performed embedded in each smart camera and only the tracking results are transmitted, which are on a higher level of abstraction. Based on this, we present a distributed surveillance system. The smart cameras' tracking results are embedded in an integrated 3D environment as live textures and can be viewed from arbitrary perspectives. Also a georeferenced live visualization embedded in Google Earth is presented.

An adaptive Multiplicative Extened Kalman Filter for Attitude Estimation of Marine Satellite Tracking Antenna

DEFF Research Database (Denmark)

Wang, Yunlong; Soltani, Mohsen; Hussain, Dil muhammed Akbar

2016-01-01

, an adaptive Multiplicative Extended Kalman Filter (MEKF) for attitude estimation of Marine Satellite Tracking Antenna (MSTA) is presented with the measurement noise covariance matrix adjusted according to the norm of accelerometer measurements, which can significantly reduce the slamming influence from waves...

Tracking of ball and players in beach volleyball videos.

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Gabriel Gomez

Full Text Available This paper presents methods for the determination of players' positions and contact time points by tracking the players and the ball in beach volleyball videos. Two player tracking methods are compared, a classical particle filter and a rigid grid integral histogram tracker. Due to mutual occlusion of the players and the camera perspective, results are best for the front players, with 74,6% and 82,6% of correctly tracked frames for the particle method and the integral histogram method, respectively. Results suggest an improved robustness against player confusion between different particle sets when tracking with a rigid grid approach. Faster processing and less player confusions make this method superior to the classical particle filter. Two different ball tracking methods are used that detect ball candidates from movement difference images using a background subtraction algorithm. Ball trajectories are estimated and interpolated from parabolic flight equations. The tracking accuracy of the ball is 54,2% for the trajectory growth method and 42,1% for the Hough line detection method. Tracking results of over 90% from the literature could not be confirmed. Ball contact frames were estimated from parabolic trajectory intersection, resulting in 48,9% of correctly estimated ball contact points.

Tracking of Ball and Players in Beach Volleyball Videos

Science.gov (United States)

Gomez, Gabriel; Herrera López, Patricia; Link, Daniel; Eskofier, Bjoern

2014-01-01

This paper presents methods for the determination of players' positions and contact time points by tracking the players and the ball in beach volleyball videos. Two player tracking methods are compared, a classical particle filter and a rigid grid integral histogram tracker. Due to mutual occlusion of the players and the camera perspective, results are best for the front players, with 74,6% and 82,6% of correctly tracked frames for the particle method and the integral histogram method, respectively. Results suggest an improved robustness against player confusion between different particle sets when tracking with a rigid grid approach. Faster processing and less player confusions make this method superior to the classical particle filter. Two different ball tracking methods are used that detect ball candidates from movement difference images using a background subtraction algorithm. Ball trajectories are estimated and interpolated from parabolic flight equations. The tracking accuracy of the ball is 54,2% for the trajectory growth method and 42,1% for the Hough line detection method. Tracking results of over 90% from the literature could not be confirmed. Ball contact frames were estimated from parabolic trajectory intersection, resulting in 48,9% of correctly estimated ball contact points. PMID:25426936

Actor-critic-based optimal tracking for partially unknown nonlinear discrete-time systems.

Science.gov (United States)

Kiumarsi, Bahare; Lewis, Frank L

2015-01-01

This paper presents a partially model-free adaptive optimal control solution to the deterministic nonlinear discrete-time (DT) tracking control problem in the presence of input constraints. The tracking error dynamics and reference trajectory dynamics are first combined to form an augmented system. Then, a new discounted performance function based on the augmented system is presented for the optimal nonlinear tracking problem. In contrast to the standard solution, which finds the feedforward and feedback terms of the control input separately, the minimization of the proposed discounted performance function gives both feedback and feedforward parts of the control input simultaneously. This enables us to encode the input constraints into the optimization problem using a nonquadratic performance function. The DT tracking Bellman equation and tracking Hamilton-Jacobi-Bellman (HJB) are derived. An actor-critic-based reinforcement learning algorithm is used to learn the solution to the tracking HJB equation online without requiring knowledge of the system drift dynamics. That is, two neural networks (NNs), namely, actor NN and critic NN, are tuned online and simultaneously to generate the optimal bounded control policy. A simulation example is given to show the effectiveness of the proposed method.

Trajectory Planning with Pose Feedback for a Dual-Arm Space Robot

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Yicheng Liu

2016-01-01

Full Text Available In order to obtain high precision path tracking for a dual-arm space robot, a trajectory planning method with pose feedback is proposed to be introduced into the design process in this paper. Firstly, pose error kinematic models are derived from the related kinematics and desired pose command for the end-effector and the base, respectively. On this basis, trajectory planning with pose feedback is proposed from a control perspective. Theoretical analyses show that the proposed trajectory planning algorithm can guarantee that pose error converges to zero exponentially for both the end-effector and the base when the robot is out of singular configuration. Compared with the existing algorithms, the proposed algorithm can lead to higher precision path tracking for the end-effector. Furthermore, the algorithm renders the system good anti-interference property for the base. Simulation results demonstrate the effectiveness of the proposed trajectory planning algorithm.

Computer vision elastography: speckle adaptive motion estimation for elastography using ultrasound sequences.

Science.gov (United States)

Revell, James; Mirmehdi, Majid; McNally, Donal

2005-06-01

We present the development and validation of an image based speckle tracking methodology, for determining temporal two-dimensional (2-D) axial and lateral displacement and strain fields from ultrasound video streams. We refine a multiple scale region matching approach incorporating novel solutions to known speckle tracking problems. Key contributions include automatic similarity measure selection to adapt to varying speckle density, quantifying trajectory fields, and spatiotemporal elastograms. Results are validated using tissue mimicking phantoms and in vitro data, before applying them to in vivo musculoskeletal ultrasound sequences. The method presented has the potential to improve clinical knowledge of tendon pathology from carpel tunnel syndrome, inflammation from implants, sport injuries, and many others.

TH-AB-202-05: BEST IN PHYSICS (JOINT IMAGING-THERAPY): First Online Ultrasound-Guided MLC Tracking for Real-Time Motion Compensation in Radiotherapy

Energy Technology Data Exchange (ETDEWEB)

Ipsen, S; Bruder, R; Schweikard, A [University of Luebeck, Luebeck, DE (United States); O’Brien, R; Keall, P [University of Sydney, Sydney (Australia); Poulsen, P [Aarhus University Hospital, Aarhus (Denmark)

2016-06-15

Purpose: While MLC tracking has been successfully used for motion compensation of moving targets, current real-time target localization methods rely on correlation models with x-ray imaging or implanted electromagnetic transponders rather than direct target visualization. In contrast, ultrasound imaging yields volumetric data in real-time (4D) without ionizing radiation. We report the first results of online 4D ultrasound-guided MLC tracking in a phantom. Methods: A real-time tracking framework was installed on a 4D ultrasound station (Vivid7 dimension, GE) and used to detect a 2mm spherical lead marker inside a water tank. The volumetric frame rate was 21.3Hz (47ms). The marker was rigidly attached to a motion stage programmed to reproduce nine tumor trajectories (five prostate, four lung). The 3D marker position from ultrasound was used for real-time MLC aperture adaption. The tracking system latency was measured and compensated by prediction for lung trajectories. To measure geometric accuracy, anterior and lateral conformal fields with 10cm circular aperture were delivered for each trajectory. The tracking error was measured as the difference between marker position and MLC aperture in continuous portal imaging. For dosimetric evaluation, 358° VMAT fields were delivered to a biplanar diode array dosimeter using the same trajectories. Dose measurements with and without MLC tracking were compared to a static reference dose using a 3%/3 mm γ-test. Results: The tracking system latency was 170ms. The mean root-mean-square tracking error was 1.01mm (0.75mm prostate, 1.33mm lung). Tracking reduced the mean γ-failure rate from 13.9% to 4.6% for prostate and from 21.8% to 0.6% for lung with high-modulation VMAT plans and from 5% (prostate) and 18% (lung) to 0% with low modulation. Conclusion: Real-time ultrasound tracking was successfully integrated with MLC tracking for the first time and showed similar accuracy and latency as other methods while holding the

A Cubature-Principle-Assisted IMM-Adaptive UKF Algorithm for Maneuvering Target Tracking Caused by Sensor Faults

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Huan Zhou

2017-09-01

Full Text Available Aimed at solving the problem of decreased filtering precision while maneuvering target tracking caused by non-Gaussian distribution and sensor faults, we developed an efficient interacting multiple model-unscented Kalman filter (IMM-UKF algorithm. By dividing the IMM-UKF into two links, the algorithm introduces the cubature principle to approximate the probability density of the random variable, after the interaction, by considering the external link of IMM-UKF, which constitutes the cubature-principle-assisted IMM method (CPIMM for solving the non-Gaussian problem, and leads to an adaptive matrix to balance the contribution of the state. The algorithm provides filtering solutions by considering the internal link of IMM-UKF, which is called a new adaptive UKF algorithm (NAUKF to address sensor faults. The proposed CPIMM-NAUKF is evaluated in a numerical simulation and two practical experiments including one navigation experiment and one maneuvering target tracking experiment. The simulation and experiment results show that the proposed CPIMM-NAUKF has greater filtering precision and faster convergence than the existing IMM-UKF. The proposed algorithm achieves a very good tracking performance, and will be effective and applicable in the field of maneuvering target tracking.

Stability Assessment and Tuning of an Adaptively Augmented Classical Controller for Launch Vehicle Flight Control

Science.gov (United States)

VanZwieten, Tannen; Zhu, J. Jim; Adami, Tony; Berry, Kyle; Grammar, Alex; Orr, Jeb S.; Best, Eric A.

2014-01-01

Recently, a robust and practical adaptive control scheme for launch vehicles [ [1] has been introduced. It augments a classical controller with a real-time loop-gain adaptation, and it is therefore called Adaptive Augmentation Control (AAC). The loop-gain will be increased from the nominal design when the tracking error between the (filtered) output and the (filtered) command trajectory is large; whereas it will be decreased when excitation of flex or sloshing modes are detected. There is a need to determine the range and rate of the loop-gain adaptation in order to retain (exponential) stability, which is critical in vehicle operation, and to develop some theoretically based heuristic tuning methods for the adaptive law gain parameters. The classical launch vehicle flight controller design technics are based on gain-scheduling, whereby the launch vehicle dynamics model is linearized at selected operating points along the nominal tracking command trajectory, and Linear Time-Invariant (LTI) controller design techniques are employed to ensure asymptotic stability of the tracking error dynamics, typically by meeting some prescribed Gain Margin (GM) and Phase Margin (PM) specifications. The controller gains at the design points are then scheduled, tuned and sometimes interpolated to achieve good performance and stability robustness under external disturbances (e.g. winds) and structural perturbations (e.g. vehicle modeling errors). While the GM does give a bound for loop-gain variation without losing stability, it is for constant dispersions of the loop-gain because the GM is based on frequency-domain analysis, which is applicable only for LTI systems. The real-time adaptive loop-gain variation of the AAC effectively renders the closed-loop system a time-varying system, for which it is well-known that the LTI system stability criterion is neither necessary nor sufficient when applying to a Linear Time-Varying (LTV) system in a frozen-time fashion. Therefore, a

Adaptive integral backstepping sliding mode control for opto-electronic tracking system based on modified LuGre friction model

Science.gov (United States)

Yue, Fengfa; Li, Xingfei; Chen, Cheng; Tan, Wenbin

2017-12-01

In order to improve the control accuracy and stability of opto-electronic tracking system fixed on reef or airport under friction and external disturbance conditions, adaptive integral backstepping sliding mode control approach with friction compensation is developed to achieve accurate and stable tracking for fast moving target. The nonlinear observer and slide mode controller based on modified LuGre model with friction compensation can effectively reduce the influence of nonlinear friction and disturbance of this servo system. The stability of the closed-loop system is guaranteed by Lyapunov theory. The steady-state error of the system is eliminated by integral action. The adaptive integral backstepping sliding mode controller and its performance are validated by a nonlinear modified LuGre dynamic model of the opto-electronic tracking system in simulation and practical experiments. The experiment results demonstrate that the proposed controller can effectively realise the accuracy and stability control of opto-electronic tracking system.

Loss of positional information when tracking multiple moving dots: the role of visual memory.

Science.gov (United States)

Narasimhan, Sathyasri; Tripathy, Srimant P; Barrett, Brendan T

2009-01-01

Pylyshyn, Z.W. and Storm, R.W. (1988) (Tracking multiple independent targets: Evidence for a parallel tracking mechanism. Spatial Vision, 3(3), 179-197) proposed that human observers could simultaneously track up to five dots when presented with an array of dots moving in a random manner. In contrast, Tripathy, S.P., and Barrett, B.T. (2004) (Severe loss of positional information when detecting deviations in multiple trajectories. Journal of Vision, 4(12):4, 1020-1043, http://journalofvision.org/4/14/4/, doi: 10.1167/4.12.4) showed that when a threshold paradigm was employed, observers' ability to track deviations in straight-line trajectories is severely compromised when attending to two or more dots. In this study we present a series of four experiments that investigates the role of attention and visual memory while tracking deviations in multiple trajectories using a threshold paradigm. Our stimuli consisted of several linear, non-parallel, left-to-right trajectories, each moving at the same speed. At the trajectory mid-point (reached simultaneously by all dots), one of the dots (target) deviated clockwise or counter-clockwise. The observers' task was to identify the direction of deviation. The target trajectory was cued in the second half of the trial either by disappearance of distractors at the monitor's mid-line (Experiment 1) or by means of a change in colour of the target (Experiment 2); in both cases deviation thresholds rose steeply when the number of distractor trajectories was increased from 0 (typical threshold approximately 2 degrees) to 3 (typical threshold>20 degrees). When all the trajectories were presented statically in a single frame (Experiment 3), thresholds for identifying the orientation change of the target trajectory remained relatively unchanged as the number of distractor trajectories was increased. When a temporal delay of a few hundred milliseconds was introduced between the first and second halves of trajectories (Experiment 4

An adaptive recurrent neural-network controller using a stabilization matrix and predictive inputs to solve a tracking problem under disturbances.

Science.gov (United States)

Fairbank, Michael; Li, Shuhui; Fu, Xingang; Alonso, Eduardo; Wunsch, Donald

2014-01-01

We present a recurrent neural-network (RNN) controller designed to solve the tracking problem for control systems. We demonstrate that a major difficulty in training any RNN is the problem of exploding gradients, and we propose a solution to this in the case of tracking problems, by introducing a stabilization matrix and by using carefully constrained context units. This solution allows us to achieve consistently lower training errors, and hence allows us to more easily introduce adaptive capabilities. The resulting RNN is one that has been trained off-line to be rapidly adaptive to changing plant conditions and changing tracking targets. The case study we use is a renewable-energy generator application; that of producing an efficient controller for a three-phase grid-connected converter. The controller we produce can cope with the random variation of system parameters and fluctuating grid voltages. It produces tracking control with almost instantaneous response to changing reference states, and virtually zero oscillation. This compares very favorably to the classical proportional integrator (PI) controllers, which we show produce a much slower response and settling time. In addition, the RNN we propose exhibits better learning stability and convergence properties, and can exhibit faster adaptation, than has been achieved with adaptive critic designs. Copyright © 2013 Elsevier Ltd. All rights reserved.

Reconstruction of pre-instrumental storm track trajectories across the U.S. Pacific Northwest using circulation-based field sampling of Pinus Ponderosa

Science.gov (United States)

Wise, E.; Dannenberg, M. P.

2015-12-01

The trajectory of incoming storms from the Pacific Ocean is a key influence on drought and flood regimes in western North America. Flow is typically from the west in a zonal pattern, but decadal shifts between zonal and meridional flow have been identified as key features in hydroclimatic variability over the instrumental period. In Washington and most of the Pacific Northwest, there tend to be lower-latitude storm systems that result in decreased precipitation in El Niño years. However, the Columbia Basin in central Washington behaves in opposition to the surrounding region and typically has average to above-average precipitation in El Niño years due to changing storm-track trajectories and a decreasing rain shadow effect on the leeward side of the Cascades. This direct connection between storm-track position and precipitation patterns in Washington provided an exceptional opportunity for circulation-based field sampling and chronology development. New Pinus ponderosa (Ponderosa pine) tree-ring chronologies were developed from eight sites around the Columbia Basin in Washington and used to examine year-to-year changes in moisture regimes. Results show that these sites are representative of the two distinct climate response areas. The divergence points between these two site responses allowed us to reconstruct changing precipitation patterns since the late-17th century, and to link these patterns to previously reconstructed atmospheric pressure and El Niño indices. This study highlights the potential for using synoptic climatology to inform field-based proxy collection.

On-Line Tracking Controller for Brushless DC Motor Drives Using Artificial Neural Networks

Science.gov (United States)

Rubaai, Ahmed

1996-01-01

A real-time control architecture is developed for time-varying nonlinear brushless dc motors operating in a high performance drives environment. The developed control architecture possesses the capabilities of simultaneous on-line identification and control. The dynamics of the motor are modeled on-line and controlled using an artificial neural network, as the system runs. The control architecture combines the experience and dependability of adaptive tracking systems with potential and promise of the neural computing technology. The sensitivity of real-time controller to parametric changes that occur during training is investigated. Such changes are usually manifested by rapid changes in the load of the brushless motor drives. This sudden change in the external load is simulated for the sigmoidal and sinusoidal reference tracks. The ability of the neuro-controller to maintain reasonable tracking accuracy in the presence of external noise is also verified for a number of desired reference trajectories.

A Mobility-Aware Adaptive Duty Cycling Mechanism for Tracking Objects during Tunnel Excavation

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Taesik Kim

2017-02-01

Full Text Available Tunnel construction workers face many dangers while working under dark conditions, with difficult access and egress, and many potential hazards. To enhance safety at tunnel construction sites, low latency tracking of mobile objects (e.g., heavy-duty equipment and construction workers is critical for managing the dangerous construction environment. Wireless Sensor Networks (WSNs are the basis for a widely used technology for monitoring the environment because of their energy-efficiency and scalability. However, their use involves an inherent point-to-point delay caused by duty cycling mechanisms that can result in a significant rise in the delivery latency for tracking mobile objects. To overcome this issue, we proposed a mobility-aware adaptive duty cycling mechanism for the WSNs based on object mobility. For the evaluation, we tested this mechanism for mobile object tracking at a tunnel excavation site. The evaluation results showed that the proposed mechanism could track mobile objects with low latency while they were moving, and could reduce energy consumption by increasing sleep time while the objects were immobile.

Self-adaptive robot training of stroke survivors for continuous tracking movements

Directory of Open Access Journals (Sweden)

Morasso Pietro

2010-03-01

Full Text Available Abstract Background Although robot therapy is progressively becoming an accepted method of treatment for stroke survivors, few studies have investigated how to adapt the robot/subject interaction forces in an automatic way. The paper is a feasibility study of a novel self-adaptive robot controller to be applied with continuous tracking movements. Methods The haptic robot Braccio di Ferro is used, in relation with a tracking task. The proposed control architecture is based on three main modules: 1 a force field generator that combines a non linear attractive field and a viscous field; 2 a performance evaluation module; 3 an adaptive controller. The first module operates in a continuous time fashion; the other two modules operate in an intermittent way and are triggered at the end of the current block of trials. The controller progressively decreases the gain of the force field, within a session, but operates in a non monotonic way between sessions: it remembers the minimum gain achieved in a session and propagates it to the next one, which starts with a block whose gain is greater than the previous one. The initial assistance gains are chosen according to a minimal assistance strategy. The scheme can also be applied with closed eyes in order to enhance the role of proprioception in learning and control. Results The preliminary results with a small group of patients (10 chronic hemiplegic subjects show that the scheme is robust and promotes a statistically significant improvement in performance indicators as well as a recalibration of the visual and proprioceptive channels. The results confirm that the minimally assistive, self-adaptive strategy is well tolerated by severely impaired subjects and is beneficial also for less severe patients. Conclusions The experiments provide detailed information about the stability and robustness of the adaptive controller of robot assistance that could be quite relevant for the design of future large scale

Comparative system identification of flower tracking performance in three hawkmoth species reveals adaptations for dim light vision.

Science.gov (United States)

Stöckl, Anna L; Kihlström, Klara; Chandler, Steven; Sponberg, Simon

2017-04-05

Flight control in insects is heavily dependent on vision. Thus, in dim light, the decreased reliability of visual signal detection also prompts consequences for insect flight. We have an emerging understanding of the neural mechanisms that different species employ to adapt the visual system to low light. However, much less explored are comparative analyses of how low light affects the flight behaviour of insect species, and the corresponding links between physiological adaptations and behaviour. We investigated whether the flower tracking behaviour of three hawkmoth species with different diel activity patterns revealed luminance-dependent adaptations, using a system identification approach. We found clear luminance-dependent differences in flower tracking in all three species, which were explained by a simple luminance-dependent delay model, which generalized across species. We discuss physiological and anatomical explanations for the variance in tracking responses, which could not be explained by such simple models. Differences between species could not be explained by the simple delay model. However, in several cases, they could be explained through the addition on a second model parameter, a simple scaling term, that captures the responsiveness of each species to flower movements. Thus, we demonstrate here that much of the variance in the luminance-dependent flower tracking responses of hawkmoths with different diel activity patterns can be captured by simple models of neural processing.This article is part of the themed issue 'Vision in dim light'. © 2017 The Author(s).

Mobile Robot Positioning by using Low-Cost Visual Tracking System

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Ruangpayoongsak Niramon

2017-01-01

Full Text Available This paper presents an application of visual tracking system on mobile robot positioning. The proposed method is verified on a constructed low-cost tracking system consisting of 2 DOF pan-tilt unit, web camera and distance sensor. The motion of pan-tilt joints is realized and controlled by using LQR controller running on microcontroller. Without needs of camera calibration, robot trajectory is tracked by Kalman filter integrating distance information and joint positions. The experimental results demonstrate validity of the proposed positioning technique and the obtained mobile robot trajectory is benchmarked against laser rangefinder positioning. The implemented system can successfully track a mobile robot driving at 14 cm/s.

Real-time dynamic MLC tracking for inversely optimized arc radiotherapy

DEFF Research Database (Denmark)

Falk, Marianne; af Rosenschöld, Per Munck; Keall, Paul

2010-01-01

Motion compensation with MLC tracking was tested for inversely optimized arc radiotherapy with special attention to the impact of the size of the target displacements and the angle of the leaf trajectory.......Motion compensation with MLC tracking was tested for inversely optimized arc radiotherapy with special attention to the impact of the size of the target displacements and the angle of the leaf trajectory....

Robust Optimal Adaptive Control Method with Large Adaptive Gain

Science.gov (United States)

Nguyen, Nhan T.

2009-01-01

In the presence of large uncertainties, a control system needs to be able to adapt rapidly to regain performance. Fast adaptation is referred to the implementation of adaptive control with a large adaptive gain to reduce the tracking error rapidly. However, a large adaptive gain can lead to high-frequency oscillations which can adversely affect robustness of an adaptive control law. A new adaptive control modification is presented that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. The modification is based on the minimization of the Y2 norm of the tracking error, which is formulated as an optimal control problem. The optimality condition is used to derive the modification using the gradient method. The optimal control modification results in a stable adaptation and allows a large adaptive gain to be used for better tracking while providing sufficient stability robustness. Simulations were conducted for a damaged generic transport aircraft with both standard adaptive control and the adaptive optimal control modification technique. The results demonstrate the effectiveness of the proposed modification in tracking a reference model while maintaining a sufficient time delay margin.

Kick-Off Point (KOP and End of Buildup (EOB Data Analysis in Trajectory Design

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Novrianti Novrianti

2017-06-01

Full Text Available Well X is a development well which is directionally drilled. Directional drilling is choosen because the coordinate target of Well X is above the buffer zone. The directional track plan needs accurate survey calculation in order to make the righ track for directional drilling. There are many survey calculation in directional drilling such as tangential, underbalance, average angle, radius of curvature, and mercury method. Minimum curvature method is used in this directional track plan calculation. This method is used because it gives less error than other method.  Kick-Off Point (KOP and End of Buildup (EOB analysis is done at 200 ft, 400 ft, and 600 ft depth to determine the trajectory design and optimal inclination. The hole problem is also determined in this trajectory track design. Optimal trajectory design determined at 200 ft depth because the inclination below 35º and also already reach the target quite well at 1632.28 ft TVD and 408.16 AHD. The optimal inclination at 200 ft KOP depth because the maximum inclination is 18.87º which is below 35º. Hole problem will occur if the trajectory designed at 600 ft. The problems are stuck pipe and the casing or tubing will not able to bend.

Lane-Level Road Information Mining from Vehicle GPS Trajectories Based on Naïve Bayesian Classification

Directory of Open Access Journals (Sweden)

Luliang Tang

2015-11-01

Full Text Available In this paper, we propose a novel approach for mining lane-level road network information from low-precision vehicle GPS trajectories (MLIT, which includes the number and turn rules of traffic lanes based on naïve Bayesian classification. First, the proposed method (MLIT uses an adaptive density optimization method to remove outliers from the raw GPS trajectories based on their space-time distribution and density clustering. Second, MLIT acquires the number of lanes in two steps. The first step establishes a naïve Bayesian classifier according to the trace features of the road plane and road profiles and the real number of lanes, as found in the training samples. The second step confirms the number of lanes using test samples in reference to the naïve Bayesian classifier using the known trace features of test sample. Third, MLIT infers the turn rules of each lane through tracking GPS trajectories. Experiments were conducted using the GPS trajectories of taxis in Wuhan, China. Compared with human-interpreted results, the automatically generated lane-level road network information was demonstrated to be of higher quality in terms of displaying detailed road networks with the number of lanes and turn rules of each lane.

Lossy compression of TPC data and trajectory tracking efficiency for the ALICE experiment

International Nuclear Information System (INIS)

Nicolaucig, A.; Ivanov, M.; Mattavelli, M.

2003-01-01

In this paper a quasi-lossless algorithm for the on-line compression of the data generated by the Time Projection Chamber (TPC) detector of the ALICE experiment at CERN is described. The algorithm is based on a lossy source code modeling technique, i.e. it is based on a source model which is lossy if samples of the TPC signal are considered one by one; conversely, the source model is lossless or quasi-lossless if some physical quantities that are of main interest for the experiment are considered. These quantities are the area and the location of the center of mass of each TPC signal pulse, representing the pulse charge and the time localization of the pulse. So as to evaluate the consequences of the error introduced by the lossy compression process, the results of the trajectory tracking algorithms that process data off-line after the experiment are analyzed, in particular, versus their sensibility to the noise introduced by the compression. Two different versions of these off-line algorithms are described, performing cluster finding and particle tracking. The results on how these algorithms are affected by the lossy compression are reported. Entropy coding can be applied to the set of events defined by the source model to reduce the bit rate to the corresponding source entropy. Using TPC simulated data according to the expected ALICE TPC performance, the compression algorithm achieves a data reduction in the range of 34.2% down to 23.7% of the original data rate depending on the desired precision on the pulse center of mass. The number of operations per input symbol required to implement the algorithm is relatively low, so that a real-time implementation of the compression process embedded in the TPC data acquisition chain using low-cost integrated electronics is a realistic option to effectively reduce the data storing cost of ALICE experiment

Knowledge-Based Trajectory Error Pattern Method Applied to an Active Force Control Scheme

Directory of Open Access Journals (Sweden)

Endra Pitowarno, Musa Mailah, Hishamuddin Jamaluddin

2012-08-01

Full Text Available The active force control (AFC method is known as a robust control scheme that dramatically enhances the performance of a robot arm particularly in compensating the disturbance effects. The main task of the AFC method is to estimate the inertia matrix in the feedback loop to provide the correct (motor torque required to cancel out these disturbances. Several intelligent control schemes have already been introduced to enhance the estimation methods of acquiring the inertia matrix such as those using neural network, iterative learning and fuzzy logic. In this paper, we propose an alternative scheme called Knowledge-Based Trajectory Error Pattern Method (KBTEPM to suppress the trajectory track error of the AFC scheme. The knowledge is developed from the trajectory track error characteristic based on the previous experimental results of the crude approximation method. It produces a unique, new and desirable error pattern when a trajectory command is forced. An experimental study was performed using simulation work on the AFC scheme with KBTEPM applied to a two-planar manipulator in which a set of rule-based algorithm is derived. A number of previous AFC schemes are also reviewed as benchmark. The simulation results show that the AFC-KBTEPM scheme successfully reduces the trajectory track error significantly even in the presence of the introduced disturbances.Key Words:  Active force control, estimated inertia matrix, robot arm, trajectory error pattern, knowledge-based.

Eye tracking a self-moved target with complex hand-target dynamics

Science.gov (United States)

Landelle, Caroline; Montagnini, Anna; Madelain, Laurent

2016-01-01

Previous work has shown that the ability to track with the eye a moving target is substantially improved when the target is self-moved by the subject's hand compared with when being externally moved. Here, we explored a situation in which the mapping between hand movement and target motion was perturbed by simulating an elastic relationship between the hand and target. Our objective was to determine whether the predictive mechanisms driving eye-hand coordination could be updated to accommodate this complex hand-target dynamics. To fully appreciate the behavioral effects of this perturbation, we compared eye tracking performance when self-moving a target with a rigid mapping (simple) and a spring mapping as well as when the subject tracked target trajectories that he/she had previously generated when using the rigid or spring mapping. Concerning the rigid mapping, our results confirmed that smooth pursuit was more accurate when the target was self-moved than externally moved. In contrast, with the spring mapping, eye tracking had initially similar low spatial accuracy (though shorter temporal lag) in the self versus externally moved conditions. However, within ∼5 min of practice, smooth pursuit improved in the self-moved spring condition, up to a level similar to the self-moved rigid condition. Subsequently, when the mapping unexpectedly switched from spring to rigid, the eye initially followed the expected target trajectory and not the real one, thereby suggesting that subjects used an internal representation of the new hand-target dynamics. Overall, these results emphasize the stunning adaptability of smooth pursuit when self-maneuvering objects with complex dynamics. PMID:27466129

Personalized trajectory matching in spatial networks

KAUST Repository

Shang, Shuo

2013-07-31

With the increasing availability of moving-object tracking data, trajectory search and matching is increasingly important. We propose and investigate a novel problem called personalized trajectory matching (PTM). In contrast to conventional trajectory similarity search by spatial distance only, PTM takes into account the significance of each sample point in a query trajectory. A PTM query takes a trajectory with user-specified weights for each sample point in the trajectory as its argument. It returns the trajectory in an argument data set with the highest similarity to the query trajectory. We believe that this type of query may bring significant benefits to users in many popular applications such as route planning, carpooling, friend recommendation, traffic analysis, urban computing, and location-based services in general. PTM query processing faces two challenges: how to prune the search space during the query processing and how to schedule multiple so-called expansion centers effectively. To address these challenges, a novel two-phase search algorithm is proposed that carefully selects a set of expansion centers from the query trajectory and exploits upper and lower bounds to prune the search space in the spatial and temporal domains. An efficiency study reveals that the algorithm explores the minimum search space in both domains. Second, a heuristic search strategy based on priority ranking is developed to schedule the multiple expansion centers, which can further prune the search space and enhance the query efficiency. The performance of the PTM query is studied in extensive experiments based on real and synthetic trajectory data sets. © 2013 Springer-Verlag Berlin Heidelberg.

Adaptive filtering for hidden node detection and tracking in networks.

Science.gov (United States)

Hamilton, Franz; Setzer, Beverly; Chavez, Sergio; Tran, Hien; Lloyd, Alun L

2017-07-01

The identification of network connectivity from noisy time series is of great interest in the study of network dynamics. This connectivity estimation problem becomes more complicated when we consider the possibility of hidden nodes within the network. These hidden nodes act as unknown drivers on our network and their presence can lead to the identification of false connections, resulting in incorrect network inference. Detecting the parts of the network they are acting on is thus critical. Here, we propose a novel method for hidden node detection based on an adaptive filtering framework with specific application to neuronal networks. We consider the hidden node as a problem of missing variables when model fitting and show that the estimated system noise covariance provided by the adaptive filter can be used to localize the influence of the hidden nodes and distinguish the effects of different hidden nodes. Additionally, we show that the sequential nature of our algorithm allows for tracking changes in the hidden node influence over time.

GPS-Aided Video Tracking

Directory of Open Access Journals (Sweden)

Udo Feuerhake

2015-08-01

Full Text Available Tracking moving objects is both challenging and important for a large variety of applications. Different technologies based on the global positioning system (GPS and video or radio data are used to obtain the trajectories of the observed objects. However, in some use cases, they fail to provide sufficiently accurate, complete and correct data at the same time. In this work we present an approach for fusing GPS- and video-based tracking in order to exploit their individual advantages. In this way we aim to combine the reliability of GPS tracking with the high geometric accuracy of camera detection. For the fusion of the movement data provided by the different devices we use a hidden Markov model (HMM formulation and the Viterbi algorithm to extract the most probable trajectories. In three experiments, we show that our approach is able to deal with challenging situations like occlusions or objects which are temporarily outside the monitored area. The results show the desired increase in terms of accuracy, completeness and correctness.

Adaptive Parameter Estimation of Person Recognition Model in a Stochastic Human Tracking Process

Science.gov (United States)

Nakanishi, W.; Fuse, T.; Ishikawa, T.

2015-05-01

This paper aims at an estimation of parameters of person recognition models using a sequential Bayesian filtering method. In many human tracking method, any parameters of models used for recognize the same person in successive frames are usually set in advance of human tracking process. In real situation these parameters may change according to situation of observation and difficulty level of human position prediction. Thus in this paper we formulate an adaptive parameter estimation using general state space model. Firstly we explain the way to formulate human tracking in general state space model with their components. Then referring to previous researches, we use Bhattacharyya coefficient to formulate observation model of general state space model, which is corresponding to person recognition model. The observation model in this paper is a function of Bhattacharyya coefficient with one unknown parameter. At last we sequentially estimate this parameter in real dataset with some settings. Results showed that sequential parameter estimation was succeeded and were consistent with observation situations such as occlusions.

Vulnerability of Australian agriculture to climate change: sequencing impacts over IPCC trajectories for adaptation planning

International Nuclear Information System (INIS)

Mallawaarachchi, Thilak; Hodges, Andrew; Wicks, Santhi; Kokic, Phil; Nelson, Rohan

2007-01-01

Full text: Full text: Agricultural systems are susceptible to adverse effects of climate change, including climate variability and extremes. While the degree of vulnerability is a function of the magnitude and the rate of variation in climate exposure, agricultural systems with a stronger adaptive capacity are likely to be less vulnerable to climate change. In preparing the agriculture sector for ongoing climate change, adaptation planning to moderate potential impacts and to take advantage of opportunities, has emerged as an effective strategic response. Global climate change scenarios developed by the IPCC indicate that changes in climate may alter the production potential of agriculture across many regions. Wide regional variability in productivity, extensive land use and the dominance in rural economies across Australia could expose agriculture to considerable risks from climate change impacts. In many cases these risks could cascade across a range of sectors and vary overtime, reflecting the capacity of exposed enterprises to adapt to a changing climate by taking advantage of opportunities. Effective planning of adaptation responses will require integrated assessments of regional vulnerability to climate risks over IPCC projection trajectories. In this paper, we present a method for estimating and mapping vulnerability to climate risks at the regional level, and apply this method to examine the vulnerability of Australian agriculture to climate change, focusing on case studies drawn from dryland broadacre and irrigated horticulture industries. In developing a conceptual framework for assessing vulnerability and adaptation options, the paper provides a review of key approaches used globally for the assessment of vulnerability to climate change in agriculture. It presents an approach to link global climate change scenario-based projections for assessing economic impacts on industries and regions through a process that maps climate risks to factors contributing

Positron emission zone plate holography for particle tracking

Energy Technology Data Exchange (ETDEWEB)

Gundogdu, O. [University of Birmingham, School of Physics and Astronomy, Birmingham B15 2TT (United Kingdom)]. E-mail: o.gundogdu@surrey.ac.uk

2006-01-15

Positron Emission Particle Tracking (PEPT) is a powerful non-invasive technique that has been used extensively for tracking a single particle. In this paper, we present a study of zone plate holography method in order to track multiple particles, mainly two particles. The main aim is to use as small number of events as possible in the order to make it possible to track particles in fast moving industrial systems. A zone plate with 100% focal efficiency is simulated and applied to the Positron Emission Tomography (PET) data for multiple particle tracking. A simple trajectory code was employed to explore the effects of the nature of the experimental trajectories. A computer holographic reconstruction code that simulates optical reconstruction was developed. The different aspects of the particle location, particle activity ratios for enabling tagging of particles and zone plate and hologram locations are investigated. The effect of the shot noise is investigated and the limitations of the zone plate holography are reported.

Positron emission zone plate holography for particle tracking

International Nuclear Information System (INIS)

Gundogdu, O.

2006-01-01

Positron Emission Particle Tracking (PEPT) is a powerful non-invasive technique that has been used extensively for tracking a single particle. In this paper, we present a study of zone plate holography method in order to track multiple particles, mainly two particles. The main aim is to use as small number of events as possible in the order to make it possible to track particles in fast moving industrial systems. A zone plate with 100% focal efficiency is simulated and applied to the Positron Emission Tomography (PET) data for multiple particle tracking. A simple trajectory code was employed to explore the effects of the nature of the experimental trajectories. A computer holographic reconstruction code that simulates optical reconstruction was developed. The different aspects of the particle location, particle activity ratios for enabling tagging of particles and zone plate and hologram locations are investigated. The effect of the shot noise is investigated and the limitations of the zone plate holography are reported

Front tracking based modeling of the solid grain growth on the adaptive control volume grid

Science.gov (United States)

Seredyński, Mirosław; Łapka, Piotr

2017-07-01

The paper presents the micro-scale model of unconstrained solidification of the grain immersed in under-cooled liquid, based on the front tracking approach. For this length scale, the interface tracked through the domain is meant as the solid-liquid boundary. To prevent generation of huge meshes the energy transport equation is discretized on the adaptive control volume (c.v.) mesh. The coupling of dynamically changing mesh and moving front position is addressed. Preliminary results of simulation of a test case, the growth of single grain, are presented and discussed.

A simultaneous localization and tracking method for a worm tracking system

Directory of Open Access Journals (Sweden)

Kowalski Mateusz

2014-09-01

Full Text Available The idea of worm tracking refers to the path analysis of Caenorhabditis elegans nematodes and is an important tool in neurobiology which helps to describe their behavior. Knowledge about nematode behavior can be applied as a model to study the physiological addiction process or other nervous system processes in animals and humans. Tracking is performed by using a special manipulator positioning a microscope with a camera over a dish with an observed individual. In the paper, the accuracy of a nematode’s trajectory reconstruction is investigated. Special attention is paid to analyzing errors that occurred during the microscope displacements. Two sources of errors in the trajectory reconstruction are shown. One is due to the difficulty in accurately measuring the microscope shift, the other is due to a nematode displacement during the microscope movement. A new method that increases path reconstruction accuracy based only on the registered sequence of images is proposed. The method Simultaneously Localizes And Tracks (SLAT the nematodes, and is robust to the positioning system displacement errors. The proposed method predicts the nematode position by using NonParametric Regression (NPR. In addition, two other methods of the SLAT problem are implemented to evaluate the NPR method. The first consists in ignoring the nematode displacement during microscope movement, and the second is based on a Kalman filter. The results suggest that the SLAT method based on nonparametric regression gives the most promising results and decreases the error of trajectory reconstruction by 25% compared with reconstruction based on data from the positioning system

Approximation-Based Discrete-Time Adaptive Position Tracking Control for Interior Permanent Magnet Synchronous Motors.

Science.gov (United States)

Yu, Jinpeng; Shi, Peng; Yu, Haisheng; Chen, Bing; Lin, Chong

2015-07-01

This paper considers the problem of discrete-time adaptive position tracking control for a interior permanent magnet synchronous motor (IPMSM) based on fuzzy-approximation. Fuzzy logic systems are used to approximate the nonlinearities of the discrete-time IPMSM drive system which is derived by direct discretization using Euler method, and a discrete-time fuzzy position tracking controller is designed via backstepping approach. In contrast to existing results, the advantage of the scheme is that the number of the adjustable parameters is reduced to two only and the problem of coupling nonlinearity can be overcome. It is shown that the proposed discrete-time fuzzy controller can guarantee the tracking error converges to a small neighborhood of the origin and all the signals are bounded. Simulation results illustrate the effectiveness and the potentials of the theoretic results obtained.

Searching Trajectories by Regions of Interest

KAUST Repository

Shang, Shuo

2017-03-22

With the increasing availability of moving-object tracking data, trajectory search is increasingly important. We propose and investigate a novel query type named trajectory search by regions of interest (TSR query). Given an argument set of trajectories, a TSR query takes a set of regions of interest as a parameter and returns the trajectory in the argument set with the highest spatial-density correlation to the query regions. This type of query is useful in many popular applications such as trip planning and recommendation, and location based services in general. TSR query processing faces three challenges: how to model the spatial-density correlation between query regions and data trajectories, how to effectively prune the search space, and how to effectively schedule multiple so-called query sources. To tackle these challenges, a series of new metrics are defined to model spatial-density correlations. An efficient trajectory search algorithm is developed that exploits upper and lower bounds to prune the search space and that adopts a query-source selection strategy, as well as integrates a heuristic search strategy based on priority ranking to schedule multiple query sources. The performance of TSR query processing is studied in extensive experiments based on real and synthetic spatial data.

Searching Trajectories by Regions of Interest

KAUST Repository

Shang, Shuo; chen, Lisi; Jensen, Christian S.; Wen, Ji-Rong; Kalnis, Panos

2017-01-01

With the increasing availability of moving-object tracking data, trajectory search is increasingly important. We propose and investigate a novel query type named trajectory search by regions of interest (TSR query). Given an argument set of trajectories, a TSR query takes a set of regions of interest as a parameter and returns the trajectory in the argument set with the highest spatial-density correlation to the query regions. This type of query is useful in many popular applications such as trip planning and recommendation, and location based services in general. TSR query processing faces three challenges: how to model the spatial-density correlation between query regions and data trajectories, how to effectively prune the search space, and how to effectively schedule multiple so-called query sources. To tackle these challenges, a series of new metrics are defined to model spatial-density correlations. An efficient trajectory search algorithm is developed that exploits upper and lower bounds to prune the search space and that adopts a query-source selection strategy, as well as integrates a heuristic search strategy based on priority ranking to schedule multiple query sources. The performance of TSR query processing is studied in extensive experiments based on real and synthetic spatial data.

A Semiactive and Adaptive Hybrid Control System for a Tracked Vehicle Hydropneumatic Suspension Based on Disturbance Identification

Directory of Open Access Journals (Sweden)

Shousong Han

2017-01-01

Full Text Available The riding conditions for a high-speed tracked vehicle are quite complex. To enhance the adaptability of suspension systems to different riding conditions, a semiactive and self-adaptive hybrid control strategy based on disturbance velocity and frequency identification was proposed. A mathematical model of the semiactive, self-adaptive hybrid suspension control system, along with a performance evaluation function, was established. Based on a two-degree-of-freedom (DOF suspension system, the kinematic relations and frequency zero-crossing detection method were defined, and expressions for the disturbance velocity and disturbance frequency of the road were obtained. Optimal scheduling of the semiactive hybrid damping control gain (csky, cground, chybrid and self-adaptive control gain (cv under different disturbances were realized by exploiting the particle swarm multiobjective optimization algorithm. An experimental study using a carefully designed test rig was performed under a number of typical riding conditions of tracked vehicles, and the results showed that the proposed control strategy is capable of accurately recognizing different disturbances, shifting between control modes (semiactive/self-adaptive, and scheduling the damping control gain according to the disturbance identification outcomes; hence, the proposed strategy could achieve a good trade-off between ride comfort and ride safety and efficiently increase the overall performance of the suspension under various riding conditions.

Track Reconstruction in the ATLAS Experiment The Deterministic Annealing Filter

CERN Document Server

Fleischmann, S

2006-01-01

The reconstruction of the trajectories of charged particles is essential for experiments at the LHC. The experiments contain precise tracking systems structured in layers around the collision point which measure the positions where particle trajectories intersect those layers. The physics analysis on the other hand mainly needs the momentum and direction of the particle at the estimated creation or reaction point. It is therefore needed to determine these parameters from the initial measurements. At the LHC one has to deal with high backgrounds while even small deficits or artifacts can reduce the signal or may produce additional background after event selection. The track reconstruction does not only contain the estimation of the track parameters, but also a pattern recognition deciding which measurements belong to a track and how many particle tracks can be found. Track reconstruction at the ATLAS experiment suffers from the high event rate at the LHC resulting in a high occupancy of the tracking devices. A...

Sensor-Based Trajectory Generation for Advanced Driver Assistance System

Directory of Open Access Journals (Sweden)

Christopher James Shackleton

2013-03-01

Full Text Available This paper investigates the trajectory generation problem for an advanced driver assistance system that could sense the driving state of the vehicle, so that a collision free trajectory can be generated safely. Specifically, the problem of trajectory generation is solved for the safety assessment of the driving state and to manipulate the vehicle in order to avoid any possible collisions. The vehicle senses the environment so as to obtain information about other vehicles and static obstacles ahead. Vehicles may share the perception of the environment via an inter-vehicle communication system. The planning algorithm is based on a visibility graph. A lateral repulsive potential is applied to adaptively maintain a trade-off between the trajectory length and vehicle clearance, which is the greatest problem associated with visibility graphs. As opposed to adaptive roadmap approaches, the algorithm exploits the structured nature of the environment for construction of the roadmap. Furthermore, the mostly organized nature of traffic systems is exploited to obtain orientation invariance, which is another limitation of both visibility graphs and adaptive roadmaps. Simulation results show that the algorithm can successfully solve the problem for a variety of commonly found scenarios.

Trajectory planning and tracking for autonomous vehicles navigation

OpenAIRE

Chebly , Alia

2017-01-01

In this thesis, the trajectory planning and the control of autonomous vehicles are addressed. As a first step, a multi-body modeling technique is used to develop a four wheeled vehicle planar model. This technique considers the vehicle as a robot consisting of articulated bodies. The geometric description of the vehicle system is derived using the modified Denavit Hartenberg parameterization and then the dynamic model of the vehicle is computed by applying a recursive method used in robotics,...

Laser fusion: an assessment of pellet injection, tracking and beam pointing

International Nuclear Information System (INIS)

Monsler, M.J.

1978-01-01

A conceptual design is presented for a target injection and final optical system which can be integrated with a lithium waterfall laser fusion reactor and operate repetitively within the presented tolerances. A high f-number focusing system using coated metal optics at 30 to 60 meters distance is suggested. An intermediate section of the differentially pumped beam tube contains flowing xenon which effectively shields the optics from debris and x rays, allowing the mirrors to operate at least a year without optical degradation. Pellets are injected with a repeating gas gun positioned horizontally just above the laser beam. No pellet trajectory correction is desired or required. Simple tracking of the target using a low power laser illuminator, a position sensing photodetector, and a trajectory prediction scheme are assumed. Two-degree of freedom x-y beam steering is preferred, without focus capability. Both the tracker and the adaptive mirror are placed in the laser building, well away from the fixed final optical mirror which faces the microexplosion

Tracking Maneuvering Group Target with Extension Predicted and Best Model Augmentation Method Adapted

Directory of Open Access Journals (Sweden)

Linhai Gan

2017-01-01

Full Text Available The random matrix (RM method is widely applied for group target tracking. The assumption that the group extension keeps invariant in conventional RM method is not yet valid, as the orientation of the group varies rapidly while it is maneuvering; thus, a new approach with group extension predicted is derived here. To match the group maneuvering, a best model augmentation (BMA method is introduced. The existing BMA method uses a fixed basic model set, which may lead to a poor performance when it could not ensure basic coverage of true motion modes. Here, a maneuvering group target tracking algorithm is proposed, where the group extension prediction and the BMA adaption are exploited. The performance of the proposed algorithm will be illustrated by simulation.

COGNITIVE DIALOG GAMES AS COGNITIVE ASSISTANTS: TRACKING AND ADAPTING KNOWLEDGE AND INTERACTIONS IN STUDENT’S DIALOGS

Directory of Open Access Journals (Sweden)

Adem Karahoca

2018-04-01

Full Text Available This study introduces a system design in a form of cognitive dialog game (DiaCog to support pedagogical factors and student learning model ideas. The purpose of the study is to describe how such a design achieves tracking and adapting students’ knowledge and mastery learning levels as a cognitive assistant. Also, this study shows alternative ways for supporting intelligent personal learning, tutoring systems, and MOOCS. This paper explains method called DiaCog that uses structure for students` thinking in an online dialog by tracking student`s level of learning/knowledge status. The methodology of computing is the semantic that match between students` interactions in a dialog. By this way it informs DiaCog’s learner model to inform the pedagogical model. Semantic fingerprint matching method of DiaCog allows making comparisons with expert knowledge to detect students` mastery levels in learning. The paper concludes with the DiaCog tool and methodologies that used for intelligent cognitive assistant design to implement pedagogical and learner model to track and adapt students’ learning. Finally, this paper discusses future improvements and planned experimental set up to advance the techniques introduced in DiaCog design.

Tracking Mobile Robot in Indoor Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Liping Zhang

2014-01-01

Full Text Available This work addresses the problem of tracking mobile robots in indoor wireless sensor networks (WSNs. Our approach is based on a localization scheme with RSSI (received signal strength indication which is used widely in WSN. The developed tracking system is designed for continuous estimation of the robot’s trajectory. A WSN, which is composed of many very simple and cheap wireless sensor nodes, is deployed at a specific region of interest. The wireless sensor nodes collect RSSI information sent by mobile robots. A range-based data fusion scheme is used to estimate the robot’s trajectory. Moreover, a Kalman filter is designed to improve tracking accuracy. Experiments are provided to assess the performance of the proposed scheme.

Automatic trajectory measurement of large numbers of crowded objects

Science.gov (United States)

Li, Hui; Liu, Ye; Chen, Yan Qiu

2013-06-01

Complex motion patterns of natural systems, such as fish schools, bird flocks, and cell groups, have attracted great attention from scientists for years. Trajectory measurement of individuals is vital for quantitative and high-throughput study of their collective behaviors. However, such data are rare mainly due to the challenges of detection and tracking of large numbers of objects with similar visual features and frequent occlusions. We present an automatic and effective framework to measure trajectories of large numbers of crowded oval-shaped objects, such as fish and cells. We first use a novel dual ellipse locator to detect the coarse position of each individual and then propose a variance minimization active contour method to obtain the optimal segmentation results. For tracking, cost matrix of assignment between consecutive frames is trainable via a random forest classifier with many spatial, texture, and shape features. The optimal trajectories are found for the whole image sequence by solving two linear assignment problems. We evaluate the proposed method on many challenging data sets.

Real-Time Motion Tracking for Mobile Augmented/Virtual Reality Using Adaptive Visual-Inertial Fusion.

Science.gov (United States)

Fang, Wei; Zheng, Lianyu; Deng, Huanjun; Zhang, Hongbo

2017-05-05

In mobile augmented/virtual reality (AR/VR), real-time 6-Degree of Freedom (DoF) motion tracking is essential for the registration between virtual scenes and the real world. However, due to the limited computational capacity of mobile terminals today, the latency between consecutive arriving poses would damage the user experience in mobile AR/VR. Thus, a visual-inertial based real-time motion tracking for mobile AR/VR is proposed in this paper. By means of high frequency and passive outputs from the inertial sensor, the real-time performance of arriving poses for mobile AR/VR is achieved. In addition, to alleviate the jitter phenomenon during the visual-inertial fusion, an adaptive filter framework is established to cope with different motion situations automatically, enabling the real-time 6-DoF motion tracking by balancing the jitter and latency. Besides, the robustness of the traditional visual-only based motion tracking is enhanced, giving rise to a better mobile AR/VR performance when motion blur is encountered. Finally, experiments are carried out to demonstrate the proposed method, and the results show that this work is capable of providing a smooth and robust 6-DoF motion tracking for mobile AR/VR in real-time.

A Novel Method of Robust Trajectory Linearization Control Based on Disturbance Rejection

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Xingling Shao

2014-01-01

Full Text Available A novel method of robust trajectory linearization control for a class of nonlinear systems with uncertainties based on disturbance rejection is proposed. Firstly, on the basis of trajectory linearization control (TLC method, a feedback linearization based control law is designed to transform the original tracking error dynamics to the canonical integral-chain form. To address the issue of reducing the influence made by uncertainties, with tracking error as input, linear extended state observer (LESO is constructed to estimate the tracking error vector, as well as the uncertainties in an integrated manner. Meanwhile, the boundedness of the estimated error is investigated by theoretical analysis. In addition, decoupled controller (which has the characteristic of well-tuning and simple form based on LESO is synthesized to realize the output tracking for closed-loop system. The closed-loop stability of the system under the proposed LESO-based control structure is established. Also, simulation results are presented to illustrate the effectiveness of the control strategy.

Robust model reference adaptive output feedback tracking for uncertain linear systems with actuator fault based on reinforced dead-zone modification.

Science.gov (United States)

Bagherpoor, H M; Salmasi, Farzad R

2015-07-01

In this paper, robust model reference adaptive tracking controllers are considered for Single-Input Single-Output (SISO) and Multi-Input Multi-Output (MIMO) linear systems containing modeling uncertainties, unknown additive disturbances and actuator fault. Two new lemmas are proposed for both SISO and MIMO, under which dead-zone modification rule is improved such that the tracking error for any reference signal tends to zero in such systems. In the conventional approach, adaption of the controller parameters is ceased inside the dead-zone region which results tracking error, while preserving the system stability. In the proposed scheme, control signal is reinforced with an additive term based on tracking error inside the dead-zone which results in full reference tracking. In addition, no Fault Detection and Diagnosis (FDD) unit is needed in the proposed approach. Closed loop system stability and zero tracking error are proved by considering a suitable Lyapunov functions candidate. It is shown that the proposed control approach can assure that all the signals of the close loop system are bounded in faulty conditions. Finally, validity and performance of the new schemes have been illustrated through numerical simulations of SISO and MIMO systems in the presence of actuator faults, modeling uncertainty and output disturbance. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Optimizing experimental parameters for tracking of diffusing particles

DEFF Research Database (Denmark)

Vestergaard, Christian L.

2016-01-01

We describe how a single-particle tracking experiment should be designed in order for its recorded trajectories to contain the most information about a tracked particle's diffusion coefficient. The precision of estimators for the diffusion coefficient is affected by motion blur, limited photon st...

Velocity Tracking Control of Wheeled Mobile Robots by Iterative Learning Control

Directory of Open Access Journals (Sweden)

Xiaochun Lu

2016-05-01

Full Text Available This paper presents an iterative learning control (ILC strategy to resolve the trajectory tracking problem of wheeled mobile robots (WMRs based on dynamic model. In the previous study of WMRs’ trajectory tracking, ILC was usually applied to the kinematical model of WMRs with the assumption that desired velocity can be tracked immediately. However, this assumption cannot be realized in the real world at all. The kinematic and dynamic models of WMRs are deduced in this chapter, and a novel combination of D-type ILC algorithm and dynamic model of WMR with random bounded disturbances are presented. To analyze the convergence of the algorithm, the method of contracting mapping, which shows that the designed controller can make the velocity tracking errors converge to zero completely when the iteration times tend to infinite, is adopted. Simulation results show the effectiveness of D-type ILC in the trajectory tracking problem of WMRs, demonstrating the effectiveness and robustness of the algorithm in the condition of random bounded disturbance. A comparative study conducted between D-type ILC and compound cosine function neural network (NN controller also demonstrates the effectiveness of the ILC strategy.

Children with Williams syndrome: Developmental trajectories for intellectual abilities, vocabulary abilities, and adaptive behavior.

Science.gov (United States)

Mervis, Carolyn B; Pitts, C Holley

2015-06-01

To examine longitudinal trajectories of intellectual abilities, single-word vocabulary abilities, and adaptive behavior for 76 children with Williams syndrome (WS) aged 4-15 years, we compared their standard scores (SSs) at two time points approximately 3 years apart on the same standardized measures. At the group level, mean SS declined significantly for 8 of the 12 measures and showed a slight (nonsignificant) increase or decrease for 4 measures. However, for most measures significant changes in SS were found for only a small proportion of the children, with some children evidencing significant declines and a smaller proportion evidencing significant increases. Significant SS changes were most common for adaptive behavior. For all measures, the mean magnitude of SS change was smaller for older children (>7.5 years at Time 1) than for younger children (general population peers who earned the same SS at Time 1, there was little evidence either of regression (loss of skills) or stagnation (failure to increase raw scores). The relations of these results to those of previous smaller-sample longitudinal studies of children with WS and the implications of the findings are considered. © 2015 Wiley Periodicals, Inc.

Automatic Generation of Complex Spatial Trajectories of the UAV and Synthesis of Control

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S. B. Tkachev

2015-01-01

Full Text Available In this paper, we propose a new method and algorithms that allow us to design complex spatial trajectories for an unmanned aerial vehicle (UAV passing through a given sequence of waypoints in the three-dimensional space.The nonlinear six-dimensional model of the UAV center-of-mass motion given in the trajectory frame is used for calculations. The state vector includes the altitude, the along-track deviation, the cross-track position, the velocity, the flight-path angle and the heading angle. The longitudinal and transverse overloads and the angle between the cross overload vector and vertical plane are considered as controls. This angle is often named as the roll angle.The feature of the problem is that both positions at waypoints and additional conditions are given. These conditions determine orientation of the velocity vector at each point (using the flight path angle and the heading angle. We also set either the point-visiting time or the pointvisiting velocity. The full state vector and controls are fixed at the starting waypoint.To construct a spatial trajectory, the concept of inverse dynamics problems is applied, as well as modern results of mathematical control theory of nonlinear dynamical systems. The introduction of new virtual controls allows us to represent the original system as an affine (linear in control system. Then, the designed system is converted into the regular canonical form.When we set flight times between any two waypoints, the corresponding segments of the trajectory are designed using time-dependent polynomials of the fifth degree. These polynomials specify the altitude variation, the variation of the along-track deviation and that of the cross-track position. If the point-visiting times are not fixed, the transition to a new independent variable (the normalized mechanical energy of the system is used. This transition is possible if the energy varies monotonically. In this case, the spatial trajectory is defined as a

Distributed Time-Varying Formation Robust Tracking for General Linear Multiagent Systems With Parameter Uncertainties and External Disturbances.

Science.gov (United States)

Hua, Yongzhao; Dong, Xiwang; Li, Qingdong; Ren, Zhang

2017-05-18

This paper investigates the time-varying formation robust tracking problems for high-order linear multiagent systems with a leader of unknown control input in the presence of heterogeneous parameter uncertainties and external disturbances. The followers need to accomplish an expected time-varying formation in the state space and track the state trajectory produced by the leader simultaneously. First, a time-varying formation robust tracking protocol with a totally distributed form is proposed utilizing the neighborhood state information. With the adaptive updating mechanism, neither any global knowledge about the communication topology nor the upper bounds of the parameter uncertainties, external disturbances and leader's unknown input are required in the proposed protocol. Then, in order to determine the control parameters, an algorithm with four steps is presented, where feasible conditions for the followers to accomplish the expected time-varying formation tracking are provided. Furthermore, based on the Lyapunov-like analysis theory, it is proved that the formation tracking error can converge to zero asymptotically. Finally, the effectiveness of the theoretical results is verified by simulation examples.

Development of Adaptive Tilt Tracker that Utilizes QUAD-cell Detector to Track Extended Objects

Science.gov (United States)

2014-03-17

tracked low Earth orbit (LEO) object and atmospheric seeing govern spot characteristics. Unlike static natural or laser guide stars, a LEO object’s...image spot characteristics .......................................................... 101 56. Response for non-adaptive tilt tracker with α equal to...applications toward natural and laser guide stars. The system was innovative and is a relevant forerunner to the tracker proposed in this research. The

BMI trajectory groups in veterans of the Iraq and Afghanistan wars.

Science.gov (United States)

Rosenberger, Patricia H; Ning, Yuming; Brandt, Cynthia; Allore, Heather; Haskell, Sally

2011-09-01

The study sought to determine BMI trajectories in Iraq/Afghanistan veterans over 6 years and to examine sociodemographic factors associated with BMI trajectory membership. Our study sample included 16,656 veterans post-deployment and entering the Veteran Healthcare Administration (VHA) healthcare system. We used national VHA administrative sociodemographic data, tracked veteran BMI for 6 years, and used trajectory modeling to identify BMI trajectories and sociodemographic characteristics associated with trajectory membership. Five trajectory groups determined in the full sample were primarily differentiated by their post-deployment initial BMI: "healthy" (14.1%), "overweight" (36.3%), "borderline obese" (27.9%), "obese" (15.7%), and "severely obese" (6.0). Being female, younger, and white were associated with lower initial BMI trajectory group membership (p'seducation and white female Veterans were associated with the lowest initial BMI group (p'sEducation level and racial status are differentially related to BMI trajectory by gender. Published by Elsevier Inc.

Adaptive Correlation Model for Visual Tracking Using Keypoints Matching and Deep Convolutional Feature

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Yuankun Li

2018-02-01

Full Text Available Although correlation filter (CF-based visual tracking algorithms have achieved appealing results, there are still some problems to be solved. When the target object goes through long-term occlusions or scale variation, the correlation model used in existing CF-based algorithms will inevitably learn some non-target information or partial-target information. In order to avoid model contamination and enhance the adaptability of model updating, we introduce the keypoints matching strategy and adjust the model learning rate dynamically according to the matching score. Moreover, the proposed approach extracts convolutional features from a deep convolutional neural network (DCNN to accurately estimate the position and scale of the target. Experimental results demonstrate that the proposed tracker has achieved satisfactory performance in a wide range of challenging tracking scenarios.

Placement Stability, Cumulative Time in Care, and Permanency: Using Administrative Data from CPS to Track Placement Trajectories.

Science.gov (United States)

Hélie, Sonia; Poirier, Marie-Andrée; Esposito, Tonino; Turcotte, Daniel

2017-11-17

Objectives : The Quebec Youth Protection Act was amended in 2007. The main goal of this reform was to improve placement stability for children who are removed from their home for their protection. Among several legal provisions introduced was the establishment of maximum age-specific durations of out-of-home care, after which a plan must be established to provide stability for children placed in substitute care by finding permanent homes for them. The purpose of this study is (1) to examine trends in placement use and placement stability since the reform and (2) to document the current frequency of each type of placement setting, the cumulative time in care before the exit to permanency, and the sustainability of the permanency outcome. Methods: The study relies on 3 entry cohorts of all children investigated who received protection measures in the province of Quebec during 3 specific time frames before and after the reform ( n = 9620, 8676, 8425). Cohorts were observed for a period varying from 3 to 4 years. Administrative data from all 16 child protection agencies were used to track placement trajectory indicators and to compare cohorts. Results : There has been a decrease in the proportion of children receiving protection measures who were placed in care since the reform, and placement in kinship care has become more frequent among children placed. Placement stability improved slightly after the reform. Overall, for infants, the most frequent type of permanency attained is adoption, while reunification is the option most often indicated for older children. Some children are at a greater risk of experiencing unstable placement trajectories: young children have a high rate of reunification breakdown, some wait a long time to be adopted, and adolescents are frequently removed from the substitute care setting where they were supposed to stay until the age of 18. Conclusions : The results suggest interesting avenues for policy makers and service providers to improve

Placement Stability, Cumulative Time in Care, and Permanency: Using Administrative Data from CPS to Track Placement Trajectories

Directory of Open Access Journals (Sweden)

Sonia Hélie

2017-11-01

Full Text Available Objectives: The Quebec Youth Protection Act was amended in 2007. The main goal of this reform was to improve placement stability for children who are removed from their home for their protection. Among several legal provisions introduced was the establishment of maximum age-specific durations of out-of-home care, after which a plan must be established to provide stability for children placed in substitute care by finding permanent homes for them. The purpose of this study is (1 to examine trends in placement use and placement stability since the reform and (2 to document the current frequency of each type of placement setting, the cumulative time in care before the exit to permanency, and the sustainability of the permanency outcome. Methods: The study relies on 3 entry cohorts of all children investigated who received protection measures in the province of Quebec during 3 specific time frames before and after the reform (n = 9620, 8676, 8425. Cohorts were observed for a period varying from 3 to 4 years. Administrative data from all 16 child protection agencies were used to track placement trajectory indicators and to compare cohorts. Results: There has been a decrease in the proportion of children receiving protection measures who were placed in care since the reform, and placement in kinship care has become more frequent among children placed. Placement stability improved slightly after the reform. Overall, for infants, the most frequent type of permanency attained is adoption, while reunification is the option most often indicated for older children. Some children are at a greater risk of experiencing unstable placement trajectories: young children have a high rate of reunification breakdown, some wait a long time to be adopted, and adolescents are frequently removed from the substitute care setting where they were supposed to stay until the age of 18. Conclusions: The results suggest interesting avenues for policy makers and service

Placement Stability, Cumulative Time in Care, and Permanency: Using Administrative Data from CPS to Track Placement Trajectories

Science.gov (United States)

Hélie, Sonia; Poirier, Marie-Andrée; Esposito, Tonino; Turcotte, Daniel

2017-01-01

Objectives: The Quebec Youth Protection Act was amended in 2007. The main goal of this reform was to improve placement stability for children who are removed from their home for their protection. Among several legal provisions introduced was the establishment of maximum age-specific durations of out-of-home care, after which a plan must be established to provide stability for children placed in substitute care by finding permanent homes for them. The purpose of this study is (1) to examine trends in placement use and placement stability since the reform and (2) to document the current frequency of each type of placement setting, the cumulative time in care before the exit to permanency, and the sustainability of the permanency outcome. Methods: The study relies on 3 entry cohorts of all children investigated who received protection measures in the province of Quebec during 3 specific time frames before and after the reform (n = 9620, 8676, 8425). Cohorts were observed for a period varying from 3 to 4 years. Administrative data from all 16 child protection agencies were used to track placement trajectory indicators and to compare cohorts. Results: There has been a decrease in the proportion of children receiving protection measures who were placed in care since the reform, and placement in kinship care has become more frequent among children placed. Placement stability improved slightly after the reform. Overall, for infants, the most frequent type of permanency attained is adoption, while reunification is the option most often indicated for older children. Some children are at a greater risk of experiencing unstable placement trajectories: young children have a high rate of reunification breakdown, some wait a long time to be adopted, and adolescents are frequently removed from the substitute care setting where they were supposed to stay until the age of 18. Conclusions: The results suggest interesting avenues for policy makers and service providers to improve the

Tracking an open quantum system using a finite state machine: Stability analysis

International Nuclear Information System (INIS)

Karasik, R. I.; Wiseman, H. M.

2011-01-01

A finite-dimensional Markovian open quantum system will undergo quantum jumps between pure states, if we can monitor the bath to which it is coupled with sufficient precision. In general these jumps, plus the between-jump evolution, create a trajectory which passes through infinitely many different pure states, even for ergodic systems. However, as shown recently by us [Phys. Rev. Lett. 106, 020406 (2011)], it is possible to construct adaptive monitorings which restrict the system to jumping between a finite number of states. That is, it is possible to track the system using a finite state machine as the apparatus. In this paper we consider the question of the stability of these monitoring schemes. Restricting to cyclic jumps for a qubit, we give a strong analytical argument that these schemes are always stable and supporting analytical and numerical evidence for the example of resonance fluorescence. This example also enables us to explore a range of behaviors in the evolution of individual trajectories, for several different monitoring schemes.

Synthetic Jet Actuator-Based Aircraft Tracking Using a Continuous Robust Nonlinear Control Strategy

Directory of Open Access Journals (Sweden)

N. Ramos-Pedroza

2017-01-01

Full Text Available A robust nonlinear control law that achieves trajectory tracking control for unmanned aerial vehicles (UAVs equipped with synthetic jet actuators (SJAs is presented in this paper. A key challenge in the control design is that the dynamic characteristics of SJAs are nonlinear and contain parametric uncertainty. The challenge resulting from the uncertain SJA actuator parameters is mitigated via innovative algebraic manipulation in the tracking error system derivation along with a robust nonlinear control law employing constant SJA parameter estimates. A key contribution of the paper is a rigorous analysis of the range of SJA actuator parameter uncertainty within which asymptotic UAV trajectory tracking can be achieved. A rigorous stability analysis is carried out to prove semiglobal asymptotic trajectory tracking. Detailed simulation results are included to illustrate the effectiveness of the proposed control law in the presence of wind gusts and varying levels of SJA actuator parameter uncertainty.

Integrated trajectory control and collision avoidance for automated driving

NARCIS (Netherlands)

Verhaegh, J.; Ploeg, J.; Nunen, E. van; Teerhuis, A.

2017-01-01

This paper presents a method for trajectory control, based on feedback linearization to guide an Automatic Guided Vehicle (AGV). The novelty of this work, is the adaptation of a reference trajectory with respect to a desired velocity in real-time to avoid collisions using a time-scaling mechanism.

Sustaining trajectory flexibility for air traffic complexity alleviation

Science.gov (United States)

Hasan, Saam N.; Rossiter, J. A.

2012-11-01

Despite the fact that several Air Traffic Management (ATM) complexity metrics have been proposed in the past few years, very few of these studies incorporate a control independent intrinsic approach to the problem with the aim of sustaining trajectory flexibility. This paper proposes the introduction of novel decision making metrics for sustaining user trajectory flexibility. The hypothesis is, if all aircraft apply a flexibility preservation function, complexity may reduce automatically. The functions proposed combine concepts of adaptability, robustness and intrinsic traffic complexity metrics based on Lyapunov exponents. Adaptability is defined as a measure of the ability of the aircraft to change its planned trajectory in response to the occurrence of a disturbance that renders the current planned trajectory infeasible. The Robustness metric is defined as the ability of the aircraft to keep its planned trajectory unchanged in response to the occurrence of disturbances. An Intrinsic complexity measure is used to evaluate the level of disorder with regards to the aircraft trajectory; disorder is defined in this context as the level of consistency in the flow patterns of aircraft and their proximity. A point mass model for multiple aircraft(s) is used to extract the trajectories and computing a form of characterisation of sensitivity and interdependencies of a set of aircraft trajectories. Lyapunov exponents are used to compute this measure. The main contribution of this paper will be to test the hypothesis by combining the complexity metrics described above. Different operational scenarios are simulated using a airspace environment developed in MATLAB which shows how well the traffic is structured by varying the metrics defined. The simulation shows the efficacy of the metrics to alleviate complexity in a heavily congested airspace.

A Dropsonde Glider with Adaptive Trajectory Planning, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — Dropsondes are one of the primary atmospheric measurement tools available to researchers. Current dropsondes are deployed with a free fall parachute trajectory,...

Trajectory Specification for Terminal Air Traffic: Pairwise Conflict Detection and Resolution

Science.gov (United States)

Paielli, Russ; Erzberger, Heinz

2017-01-01

Trajectory specification is the explicit bounding and control of aircraft trajectories such that the position at each point in time is constrained to a precisely defined volume of space. The bounding space is defined by cross-track, along-track, and vertical tolerances relative to a reference trajectory that specifies position as a function of time. The tolerances are dynamic and will be based on the aircraft navigation capabilities and the current traffic situation. A standard language will be developed to represent these specifications and to communicate them by datalink. Assuming conformance, trajectory specification can guarantee safe separation for an arbitrary period of time even in the event of an air traffic control (ATC) system or datalink failure, hence it can help to achieve the high level of safety and reliability needed for ATC automation. As a more proactive form of ATC, it can also maximize airspace capacity and reduce the reliance on tactical backup systems during normal operation. It applies to both enroute airspace and the terminal area around airports, but this paper focuses on the terminal area and presents algorithms and software for spacing arrivals and deconflicting both arrivals and departures.

Dense Trajectories and DHOG for Classification of Viewpoints from Echocardiogram Videos

Directory of Open Access Journals (Sweden)

Liqin Huang

2016-01-01

Full Text Available In echo-cardiac clinical computer-aided diagnosis, an important step is to automatically classify echocardiography videos from different angles and different regions. We propose a kind of echocardiography video classification algorithm based on the dense trajectory and difference histograms of oriented gradients (DHOG. First, we use the dense grid method to describe feature characteristics in each frame of echocardiography sequence and then track these feature points by applying the dense optical flow. In order to overcome the influence of the rapid and irregular movement of echocardiography videos and get more robust tracking results, we also design a trajectory description algorithm which uses the derivative of the optical flow to obtain the motion trajectory information and associates the different characteristics (e.g., the trajectory shape, DHOG, HOF, and MBH with embedded structural information of the spatiotemporal pyramid. To avoid “dimension disaster,” we apply Fisher’s vector to reduce the dimension of feature description followed by the SVM linear classifier to improve the final classification result. The average accuracy of echocardiography video classification is 77.12% for all eight viewpoints and 100% for three primary viewpoints.

A System based on Adaptive Background Subtraction Approach for Moving Object Detection and Tracking in Videos

Directory of Open Access Journals (Sweden)

Bahadır KARASULU

2013-04-01

Full Text Available Video surveillance systems are based on video and image processing research areas in the scope of computer science. Video processing covers various methods which are used to browse the changes in existing scene for specific video. Nowadays, video processing is one of the important areas of computer science. Two-dimensional videos are used to apply various segmentation and object detection and tracking processes which exists in multimedia content-based indexing, information retrieval, visual and distributed cross-camera surveillance systems, people tracking, traffic tracking and similar applications. Background subtraction (BS approach is a frequently used method for moving object detection and tracking. In the literature, there exist similar methods for this issue. In this research study, it is proposed to provide a more efficient method which is an addition to existing methods. According to model which is produced by using adaptive background subtraction (ABS, an object detection and tracking system’s software is implemented in computer environment. The performance of developed system is tested via experimental works with related video datasets. The experimental results and discussion are given in the study

On the design of fuzzified trajectory shaping guidance law.

Science.gov (United States)

Lin, Chun-Liang; Lin, Yu-Ping; Chen, Kai-Ming

2009-04-01

Midcourse guidance is commonly designed to save as much energy as possible so that the missile's final speed can be maximized while entering the homing stage. For this purpose, a competitive guidance design should be able to generate an admissible flight trajectory as to bring the interceptor to a superior altitude for a favorable target engagement. In this paper, a new adaptive trajectory shaping guidance scheme based on the adaptive fuzzy inference system, which is capable of generating a variety of trajectories for efficient target interception, is presented. The guidance law is developed with the aim of saving the interceptor's energy conservation while improving performance robustness. Applications of the presented approach have included a variety of mission oriented guidance, such as cruise missile guidance, anti-ballistic missile guidance, etc.

Trajectory Analysis and Prediction for Improved Pedestrian Safety

DEFF Research Database (Denmark)

Møgelmose, Andreas; Trivedi, Mohan M.; Moeslund, Thomas B.

2015-01-01

This paper presents a monocular and purely vision based pedestrian trajectory tracking and prediction framework with integrated map-based hazard inference. In Advanced Driver Assistance systems research, a lot of effort has been put into pedestrian detection over the last decade, and several pede...

Identification of digitized particle trajectories

CERN Document Server

Grote, H; Lassalle, J C; Zanella, P

1973-01-01

High-energy Physics Laboratories make increasing use of particle detectors which directly produce digital measurements of trajectories at very high rates. Data collected in vast amounts during experiments are then analysed by computer programs whose first task is the recognition of tracks and reconstruction of the interesting events. This paper discusses the applicability of various Pattern Recognition approaches. Examples are given of the problems and the practical achievements in this field.

Real-time tracking control of electro-hydraulic force servo systems using offline feedback control and adaptive control.

Science.gov (United States)

Shen, Gang; Zhu, Zhencai; Zhao, Jinsong; Zhu, Weidong; Tang, Yu; Li, Xiang

2017-03-01

This paper focuses on an application of an electro-hydraulic force tracking controller combined with an offline designed feedback controller (ODFC) and an online adaptive compensator in order to improve force tracking performance of an electro-hydraulic force servo system (EHFS). A proportional-integral controller has been employed and a parameter-based force closed-loop transfer function of the EHFS is identified by a continuous system identification algorithm. By taking the identified system model as a nominal plant model, an H ∞ offline design method is employed to establish an optimized feedback controller with consideration of the performance, control efforts, and robustness of the EHFS. In order to overcome the disadvantage of the offline designed controller and cope with the varying dynamics of the EHFS, an online adaptive compensator with a normalized least-mean-square algorithm is cascaded to the force closed-loop system of the EHFS compensated by the ODFC. Some comparative experiments are carried out on a real-time EHFS using an xPC rapid prototype technology, and the proposed controller yields a better force tracking performance improvement. Copyright © 2016. Published by Elsevier Ltd.

A model of chemical etching of olivine in the vicinity of the trajectory of a swift heavy ion

Energy Technology Data Exchange (ETDEWEB)

Gorbunov, S.A., E-mail: s.a.gorbunov@mail.ru [Lebedev Physical Institute of the Russian Academy of Sciences, Leninskij pr. 53, 119991 Moscow (Russian Federation); Rymzhanov, R.A. [Joint Institute for Nuclear Research, Joliot-Curie 6, 141980 Dubna, Moscow Region (Russian Federation); Starkov, N.I. [Lebedev Physical Institute of the Russian Academy of Sciences, Leninskij pr. 53, 119991 Moscow (Russian Federation); Volkov, A.E. [Lebedev Physical Institute of the Russian Academy of Sciences, Leninskij pr. 53, 119991 Moscow (Russian Federation); Joint Institute for Nuclear Research, Joliot-Curie 6, 141980 Dubna, Moscow Region (Russian Federation); National Research Centre ‘Kurchatov Institute’, Kurchatov Sq. 1, 123182 Moscow (Russian Federation); Malakhov, A.I. [Joint Institute for Nuclear Research, Joliot-Curie 6, 141980 Dubna, Moscow Region (Russian Federation)

2015-12-15

Searching of superheavy elements, the charge spectra of heavy nuclei in Galactic Cosmic Rays was investigated within the OLYMPIA experiment using the database of etched ion tracks in meteorite olivine. Etching results in the formation of hollow syringe-like channels with diameters of 1–10 μm along the trajectories of these swift heavy ions (SHI). According to the activated complex theory, the local chemical activity is determined by an increase of the specific Gibbs energy of the lattice stimulated by structure transformations, long-range elastic fields, and interatomic bonds breaking generated in the vicinity of the ion trajectory. To determine the dependencies of the Gibbs free energy increase in SHI tracks in olivine on the mass, energy and charge of a projectile, we apply a multiscale model of excitation and relaxation of materials in the vicinity of the SHI trajectory (SHI tracks). Effect of spreading of fast electrons from the ion trajectory causing neutralization of metallic atoms resulting in an increase of the chemical activity of olivine at long distances from the ion trajectory (up to 5 μm) is estimated and discussed.

Trajectory Specification for Automation of Terminal Air Traffic Control

Science.gov (United States)

Paielli, Russell A.

2016-01-01

"Trajectory specification" is the explicit bounding and control of aircraft tra- jectories such that the position at each point in time is constrained to a precisely defined volume of space. The bounding space is defined by cross-track, along-track, and vertical tolerances relative to a reference trajectory that specifies position as a function of time. The tolerances are dynamic and will be based on the aircraft nav- igation capabilities and the current traffic situation. A standard language will be developed to represent these specifications and to communicate them by datalink. Assuming conformance, trajectory specification can guarantee safe separation for an arbitrary period of time even in the event of an air traffic control (ATC) sys- tem or datalink failure, hence it can help to achieve the high level of safety and reliability needed for ATC automation. As a more proactive form of ATC, it can also maximize airspace capacity and reduce the reliance on tactical backup systems during normal operation. It applies to both enroute airspace and the terminal area around airports, but this paper focuses on arrival spacing in the terminal area and presents ATC algorithms and software for achieving a specified delay of runway arrival time.

CMS reconstruction improvements for the tracking in large pileup events

CERN Document Server

Rovere, M

2015-01-01

The CMS tracking code is organized in several levels, known as iterative steps, each optimized to reconstruct a class of particle trajectories, as the ones of particles originating from the primary vertex or displaced tracks from particles resulting from secondary vertices. Each iterative step consists of seeding, pattern recognition and fitting by a kalman filter, and a final filtering and cleaning. Each subsequent step works on hits not yet associated to a reconstructed particle trajectory.The CMS tracking code is continuously evolving to make the reconstruction computing load compatible with the increasing instantaneous luminosity of LHC, resulting in a large number of primary vertices and tracks per bunch crossing.The major upgrade put in place during the present LHC Long Shutdown will allow the tracking code to comply with the conditions expected during RunII and the much larger pileup. In particular, new algorithms that are intrinsically more robust in high occupancy conditions were developed, iteration...

Tracking Control of a 2-DOF Arm Actuated by Pneumatic Muscle Actuators Using Adaptive Fuzzy Sliding Mode Control

Science.gov (United States)

Chang, Ming-Kun; Wu, Jui-Chi

Pneumatic muscle actuators (PMAs) have the highest power/weight ratio and power/volume ratio of any actuator. Therefore, they can be used not only in the rehabilitation engineering, but also as an actuator in robots, including industrial robots and therapy robots. It is difficult to achieve excellent tracking performance using classical control methods because the compressibility of gas and the nonlinear elasticity of bladder container causes parameter variations. An adaptive fuzzy sliding mode control is developed in this study. The fuzzy sliding surface can be used to reduce fuzzy rule numbers, and the adaptive control law is used to modify fuzzy rules on-line. A model matching technique is then adopted to adjust scaling factors. The experimental results show that this control strategy can attain excellent tracking performance.

Iterative learning-based decentralized adaptive tracker for large-scale systems: a digital redesign approach.

Science.gov (United States)

Tsai, Jason Sheng-Hong; Du, Yan-Yi; Huang, Pei-Hsiang; Guo, Shu-Mei; Shieh, Leang-San; Chen, Yuhua

2011-07-01

In this paper, a digital redesign methodology of the iterative learning-based decentralized adaptive tracker is proposed to improve the dynamic performance of sampled-data linear large-scale control systems consisting of N interconnected multi-input multi-output subsystems, so that the system output will follow any trajectory which may not be presented by the analytic reference model initially. To overcome the interference of each sub-system and simplify the controller design, the proposed model reference decentralized adaptive control scheme constructs a decoupled well-designed reference model first. Then, according to the well-designed model, this paper develops a digital decentralized adaptive tracker based on the optimal analog control and prediction-based digital redesign technique for the sampled-data large-scale coupling system. In order to enhance the tracking performance of the digital tracker at specified sampling instants, we apply the iterative learning control (ILC) to train the control input via continual learning. As a result, the proposed iterative learning-based decentralized adaptive tracker not only has robust closed-loop decoupled property but also possesses good tracking performance at both transient and steady state. Besides, evolutionary programming is applied to search for a good learning gain to speed up the learning process of ILC. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

Measuring and tracking the flow of climate change adaptation aid to the developing world

Science.gov (United States)

Donner, Simon D.; Kandlikar, Milind; Webber, Sophie

2016-05-01

The developed world has pledged to mobilize at least US 100 billion per year of ‘new’ and ‘additional’ funds by 2020 to help the developing world respond to climate change. Tracking this finance is particularly problematic for climate change adaptation, as there is no clear definition of what separates adaptation aid from standard development aid. Here we use a historical database of overseas development assistance projects to test the effect of different accounting assumptions on the delivery of adaptation finance to the developing countries of Oceania, using machine algorithms developed from a manual pilot study. The results show that explicit adaptation finance grew to 3%-4% of all development aid to Oceania by the 2008-2012 period, but that total adaptation finance could be as high as 37% of all aid, depending on potentially politically motivated assumptions about what counts as adaptation. There was also an uneven distribution of adaptation aid between countries facing similar challenges like Kiribati, the Marshall Islands, and the Federated States of Micronesia. The analysis indicates that data allowing individual projects to be weighted by their climate change relevance is needed. A robust and mandatory metadata system for all aid projects would allow multilateral aid agencies and independent third parties to perform their own analyses using different assumptions and definitions, and serve as a key check on international climate aid promises.

Pulse width modulation-based temperature tracking for feedback control of a shape memory alloy actuator.

Science.gov (United States)

Ayvali, Elif; Desai, Jaydev P

2014-04-01

This work presents a temperature-feedback approach to control the radius of curvature of an arc-shaped shape memory alloy (SMA) wire. The nonlinear properties of the SMA such as phase transformation and its dependence on temperature and stress make SMA actuators difficult to control. Tracking a desired trajectory is more challenging than controlling just the position of the SMA actuator since the desired path is continuously changing. Consequently, tracking the desired strain directly or tracking the parameters such as temperature and electrical resistance that are related to strain with a model is a challenging task. Temperature-feedback is an attractive approach when direct measurement of strain is not practical. Pulse width modulation (PWM) is an effective method for SMA actuation and it can be used along with a compensator to control the temperature of the SMA. Using the constitutive model of the SMA, the desired temperature profile can be obtained for a given strain trajectory. A PWM-based nonlinear PID controller with a feed-forward heat transfer model is proposed to use temperature-feedback for tracking a desired temperature trajectory. The proposed controller is used during the heating phase of the SMA actuator. The controller proves to be effective in tracking step-wise and continuous trajectories.

Expectations on Track? High School Tracking and Adolescent Educational Expectations

DEFF Research Database (Denmark)

Karlson, Kristian Bernt

2015-01-01

This paper examines the role of adaptation in expectation formation processes by analyzing how educational tracking in high schools affects adolescents' educational expectations. I argue that adolescents view track placement as a signal about their academic abilities and respond to it in terms...... of modifying their educational expectations. Applying a difference-in-differences approach to the National Educational Longitudinal Study of 1988, I find that being placed in an advanced or honors class in high school positively affects adolescents’ expectations, particularly if placement is consistent across...... subjects and if placement contradicts tracking experiences in middle school. My findings support the hypothesis that adolescents adapt their educational expectations to ability signals sent by schools....

First evaluation of the feasibility of MLC tracking using ultrasound motion estimation

Energy Technology Data Exchange (ETDEWEB)

Fast, Martin F., E-mail: martin.fast@icr.ac.uk; O’Shea, Tuathan P., E-mail: tuathan.oshea@nhs.net; Nill, Simeon; Oelfke, Uwe; Harris, Emma J. [Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London SM2 5NG (United Kingdom)

2016-08-15

Purpose: To quantify the performance of the Clarity ultrasound (US) imaging system (Elekta AB, Stockholm, Sweden) for real-time dynamic multileaf collimator (MLC) tracking. Methods: The Clarity calibration and quality assurance phantom was mounted on a motion platform moving with a periodic sine wave trajectory. The detected position of a 30 mm hypoechogenic sphere within the phantom was continuously reported via Clarity’s real-time streaming interface to an in-house tracking and delivery software and subsequently used to adapt the MLC aperture. A portal imager measured MV treatment field/MLC apertures and motion platform positions throughout each experiment to independently quantify system latency and geometric error. Based on the measured range of latency values, a prostate stereotactic body radiation therapy (SBRT) delivery was performed with three realistic motion trajectories. The dosimetric impact of system latency on MLC tracking was directly measured using a 3D dosimeter mounted on the motion platform. Results: For 2D US imaging, the overall system latency, including all delay times from the imaging and delivery chain, ranged from 392 to 424 ms depending on the lateral sector size. For 3D US imaging, the latency ranged from 566 to 1031 ms depending on the elevational sweep. The latency-corrected geometric root-mean squared error was below 0.75 mm (2D US) and below 1.75 mm (3D US). For the prostate SBRT delivery, the impact of a range of system latencies (400–1000 ms) on the MLC tracking performance was minimal in terms of gamma failure rate. Conclusions: Real-time MLC tracking based on a noninvasive US input is technologically feasible. Current system latencies are higher than those for x-ray imaging systems, but US can provide full volumetric image data and the impact of system latency was measured to be small for a prostate SBRT case when using a US-like motion input.

First evaluation of the feasibility of MLC tracking using ultrasound motion estimation

International Nuclear Information System (INIS)

Fast, Martin F.; O’Shea, Tuathan P.; Nill, Simeon; Oelfke, Uwe; Harris, Emma J.

2016-01-01

Purpose: To quantify the performance of the Clarity ultrasound (US) imaging system (Elekta AB, Stockholm, Sweden) for real-time dynamic multileaf collimator (MLC) tracking. Methods: The Clarity calibration and quality assurance phantom was mounted on a motion platform moving with a periodic sine wave trajectory. The detected position of a 30 mm hypoechogenic sphere within the phantom was continuously reported via Clarity’s real-time streaming interface to an in-house tracking and delivery software and subsequently used to adapt the MLC aperture. A portal imager measured MV treatment field/MLC apertures and motion platform positions throughout each experiment to independently quantify system latency and geometric error. Based on the measured range of latency values, a prostate stereotactic body radiation therapy (SBRT) delivery was performed with three realistic motion trajectories. The dosimetric impact of system latency on MLC tracking was directly measured using a 3D dosimeter mounted on the motion platform. Results: For 2D US imaging, the overall system latency, including all delay times from the imaging and delivery chain, ranged from 392 to 424 ms depending on the lateral sector size. For 3D US imaging, the latency ranged from 566 to 1031 ms depending on the elevational sweep. The latency-corrected geometric root-mean squared error was below 0.75 mm (2D US) and below 1.75 mm (3D US). For the prostate SBRT delivery, the impact of a range of system latencies (400–1000 ms) on the MLC tracking performance was minimal in terms of gamma failure rate. Conclusions: Real-time MLC tracking based on a noninvasive US input is technologically feasible. Current system latencies are higher than those for x-ray imaging systems, but US can provide full volumetric image data and the impact of system latency was measured to be small for a prostate SBRT case when using a US-like motion input.

Sliding Mode Tracking Control of Manipulator Based on the Improved Reaching Law

Directory of Open Access Journals (Sweden)

Wei-Na ZHAI

2013-04-01

Full Text Available Due to the mechanical hand often have serious uncertainty, as the state in which the different and external changes, also its parameters are changing, this is very adverse to achieve precise control. In this paper, the traditional sliding mode variable structure was improved, the sign function is replaced by saturated function based on the double power reaching law, by adjusting the values of e1, e2, a, b, g and k to effectively improve the manipulator joint reaching speed, track expected trajectory fast and shorten the system response time. Finally, the method is used for simulation of manipulator trajectory tracking, compared to two reaching law control algorithms. The simulation results show that the control algorithm has good dynamic performance, which can effectively restrain the chattering and quickly track the desired trajectory. Therefore, the improved reaching law can effectively improve the performance of robotic manipulator.

On Synergistic Integration of Adaptive Dithering Based Internal Model Control for Hysteresis Compensation in Piezoactuated Nanopositioner

Directory of Open Access Journals (Sweden)

Saikat Kumar Shome

2015-01-01

Full Text Available Piezoelectric-stack actuated platforms are very popular in the parlance of nanopositioning with myriad applications like micro/nanofactory, atomic force microscopy, scanning probe microscopy, wafer design, biological cell manipulation, and so forth. Motivated by the necessity to improve trajectory tracking in such applications, this paper addresses the problem of rate dependent hysteretic nonlinearity in piezoelectric actuators (PEA. The classical second order Dahl model for hysteresis encapsulation is introduced first, followed by the identification of parameters through particle swarm optimization. A novel inversion based feedforward mechanism in combination with a feedback compensator is proposed to achieve high-precision tracking wherein the paradoxical concept of noise as a performance enhancer is introduced in the realm of PZAs. Having observed that dither induced stochastic resonance in the presence of periodic forcing reduces tracking error, dither capability is further explored in conjunction with a novel output harmonics based adaptive control scheme. The proposed adaptive controller is then augmented with an internal model control based approach to impart robustness against parametric variations and external disturbances. The proposed control law has been employed to track multifrequency signals with consistent compensation of rate dependent hysteresis of the PEA. The results indicate a greatly improved positioning accuracy along with considerable robustness achieved with the proposed integrated approach even for dual axis tracking applications.

Adaptive NN tracking control of uncertain nonlinear discrete-time systems with nonaffine dead-zone input.

Science.gov (United States)

Liu, Yan-Jun; Tong, Shaocheng

2015-03-01

In the paper, an adaptive tracking control design is studied for a class of nonlinear discrete-time systems with dead-zone input. The considered systems are of the nonaffine pure-feedback form and the dead-zone input appears nonlinearly in the systems. The contributions of the paper are that: 1) it is for the first time to investigate the control problem for this class of discrete-time systems with dead-zone; 2) there are major difficulties for stabilizing such systems and in order to overcome the difficulties, the systems are transformed into an n-step-ahead predictor but nonaffine function is still existent; and 3) an adaptive compensative term is constructed to compensate for the parameters of the dead-zone. The neural networks are used to approximate the unknown functions in the transformed systems. Based on the Lyapunov theory, it is proven that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded and the tracking error converges to a small neighborhood of zero. Two simulation examples are provided to verify the effectiveness of the control approach in the paper.

Robust Target Tracking with Multi-Static Sensors under Insufficient TDOA Information.

Science.gov (United States)

Shin, Hyunhak; Ku, Bonhwa; Nelson, Jill K; Ko, Hanseok

2018-05-08

This paper focuses on underwater target tracking based on a multi-static sonar network composed of passive sonobuoys and an active ping. In the multi-static sonar network, the location of the target can be estimated using TDOA (Time Difference of Arrival) measurements. However, since the sensor network may obtain insufficient and inaccurate TDOA measurements due to ambient noise and other harsh underwater conditions, target tracking performance can be significantly degraded. We propose a robust target tracking algorithm designed to operate in such a scenario. First, track management with track splitting is applied to reduce performance degradation caused by insufficient measurements. Second, a target location is estimated by a fusion of multiple TDOA measurements using a Gaussian Mixture Model (GMM). In addition, the target trajectory is refined by conducting a stack-based data association method based on multiple-frames measurements in order to more accurately estimate target trajectory. The effectiveness of the proposed method is verified through simulations.

Analysis of Tropical Cyclone Tracks in the North Indian Ocean

Science.gov (United States)

Patwardhan, A.; Paliwal, M.; Mohapatra, M.

2011-12-01

Cyclones are regarded as one of the most dangerous meteorological phenomena of the tropical region. The probability of landfall of a tropical cyclone depends on its movement (trajectory). Analysis of trajectories of tropical cyclones could be useful for identifying potentially predictable characteristics. There is long history of analysis of tropical cyclones tracks. A common approach is using different clustering techniques to group the cyclone tracks on the basis of certain characteristics. Various clustering method have been used to study the tropical cyclones in different ocean basins like western North Pacific ocean (Elsner and Liu, 2003; Camargo et al., 2007), North Atlantic Ocean (Elsner, 2003; Gaffney et al. 2007; Nakamura et al., 2009). In this study, tropical cyclone tracks in the North Indian Ocean basin, for the period 1961-2010 have been analyzed and grouped into clusters based on their spatial characteristics. A tropical cyclone trajectory is approximated as an open curve and described by its first two moments. The resulting clusters have different centroid locations and also differently shaped variance ellipses. These track characteristics are then used in the standard clustering algorithms which allow the whole track shape, length, and location to be incorporated into the clustering methodology. The resulting clusters have different genesis locations and trajectory shapes. We have also examined characteristics such as life span, maximum sustained wind speed, landfall, seasonality, many of which are significantly different across the identified clusters. The clustering approach groups cyclones with higher maximum wind speed and longest life span in to one cluster. Another cluster includes short duration cyclonic events that are mostly deep depressions and significant for rainfall over Eastern and Central India. The clustering approach is likely to prove useful for analysis of events of significance with regard to impacts.

On-Line Fringe Tracking and Prediction at IOTA

Science.gov (United States)

Wilson, Edward; Mah, Robert; Lau, Sonie (Technical Monitor)

1999-01-01

The Infrared/Optical Telescope Array (IOTA) is a multi-aperture Michelson interferometer located on Mt. Hopkins near Tucson, Arizona. To enable viewing of fainter targets, an on-line fringe tracking system is presently under development at NASA Ames Research Center. The system has been developed off-line using actual data from IOTA, and is presently undergoing on-line implementation at IOTA. The system has two parts: (1) a fringe tracking system that identifies the center of a fringe packet by fitting a parametric model to the data; and (2) a fringe packet motion prediction system that uses characteristics of past fringe packets to predict fringe packet motion. Combined, this information will be used to optimize on-line the scanning trajectory, resulting in improved visibility of faint targets. Fringe packet identification is highly accurate and robust (99% of the 4000 fringe packets were identified correctly, the remaining 1% were either out of the scan range or too noisy to be seen) and is performed in 30-90 milliseconds on a Pentium II-based computer. Fringe packet prediction, currently performed using an adaptive linear predictor, delivers a 10% improvement over the baseline of predicting no motion.

Tracking Genomic Cancer Evolution for Precision Medicine: The Lung TRACERx Study

DEFF Research Database (Denmark)

Jamal-Hanjani, Mariam; Hackshaw, Alan; Ngai, Yenting

2014-01-01

. TRACERx (TRAcking non-small cell lung Cancer Evolution through therapy [Rx]), a prospective study of patients with primary non-small cell lung cancer (NSCLC), aims to define the evolutionary trajectories of lung cancer in both space and time through multiregion and longitudinal tumour sampling and genetic...... analysis. By following cancers from diagnosis to relapse, tracking the evolutionary trajectories of tumours in relation to therapeutic interventions, and determining the impact of clonal heterogeneity on clinical outcomes, TRACERx may help to identify novel therapeutic targets for NSCLC and may also serve...

Optimal trajectories for flexible-link manipulator slewing using recursive quadratic programming: Experimental verification

International Nuclear Information System (INIS)

Parker, G.G.; Eisler, G.R.; Feddema, J.T.

1994-01-01

Procedures for trajectory planning and control of flexible link robots are becoming increasingly important to satisfy performance requirements of hazardous waste removal efforts. It has been shown that utilizing link flexibility in designing open loop joint commands can result in improved performance as opposed to damping vibration throughout a trajectory. The efficient use of link compliance is exploited in this work. Specifically, experimental verification of minimum time, straight line tracking using a two-link planar flexible robot is presented. A numerical optimization process, using an experimentally verified modal model, is used for obtaining minimum time joint torque and angle histories. The optimal joint states are used as commands to the proportional-derivative servo actuated joints. These commands are precompensated for the nonnegligible joint servo actuator dynamics. Using the precompensated joint commands, the optimal joint angles are tracked with such fidelity that the tip tracking error is less than 2.5 cm

Geometric accuracy of a novel gimbals based radiation therapy tumor tracking system.

Science.gov (United States)

Depuydt, Tom; Verellen, Dirk; Haas, Olivier; Gevaert, Thierry; Linthout, Nadine; Duchateau, Michael; Tournel, Koen; Reynders, Truus; Leysen, Katrien; Hoogeman, Mischa; Storme, Guy; De Ridder, Mark

2011-03-01

VERO is a novel platform for image guided stereotactic body radiotherapy. Orthogonal gimbals hold the linac-MLC assembly allowing real-time moving tumor tracking. This study determines the geometric accuracy of the tracking. To determine the tracking error, an 1D moving phantom produced sinusoidal motion with frequencies up to 30 breaths per minute (bpm). Tumor trajectories of patients were reproduced using a 2D robot and pursued with the gimbals tracking system prototype. Using the moving beam light field and a digital-camera-based detection unit tracking errors, system lag and equivalence of pan/tilt performance were measured. The system lag was 47.7 ms for panning and 47.6 ms for tilting. Applying system lag compensation, sinusoidal motion tracking was accurate, with a tracking error 90% percentile E(90%)tracking errors were below 0.14 mm. The 2D tumor trajectories were tracked with an average E(90%) of 0.54 mm, and tracking error standard deviations of 0.20 mm for pan and 0.22 mm for tilt. In terms of dynamic behavior, the gimbaled linac of the VERO system showed to be an excellent approach for providing accurate real-time tumor tracking in radiation therapy. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Dynamic Trajectory Extraction from Stereo Vision Using Fuzzy Clustering

Science.gov (United States)

Onishi, Masaki; Yoda, Ikushi

In recent years, many human tracking researches have been proposed in order to analyze human dynamic trajectory. These researches are general technology applicable to various fields, such as customer purchase analysis in a shopping environment and safety control in a (railroad) crossing. In this paper, we present a new approach for tracking human positions by stereo image. We use the framework of two-stepped clustering with k-means method and fuzzy clustering to detect human regions. In the initial clustering, k-means method makes middle clusters from objective features extracted by stereo vision at high speed. In the last clustering, c-means fuzzy method cluster middle clusters based on attributes into human regions. Our proposed method can be correctly clustered by expressing ambiguity using fuzzy clustering, even when many people are close to each other. The validity of our technique was evaluated with the experiment of trajectories extraction of doctors and nurses in an emergency room of a hospital.

On Integral Invariants for Effective 3-D Motion Trajectory Matching and Recognition.

Science.gov (United States)

Shao, Zhanpeng; Li, Youfu

2016-02-01

Motion trajectories tracked from the motions of human, robots, and moving objects can provide an important clue for motion analysis, classification, and recognition. This paper defines some new integral invariants for a 3-D motion trajectory. Based on two typical kernel functions, we design two integral invariants, the distance and area integral invariants. The area integral invariants are estimated based on the blurred segment of noisy discrete curve to avoid the computation of high-order derivatives. Such integral invariants for a motion trajectory enjoy some desirable properties, such as computational locality, uniqueness of representation, and noise insensitivity. Moreover, our formulation allows the analysis of motion trajectories at a range of scales by varying the scale of kernel function. The features of motion trajectories can thus be perceived at multiscale levels in a coarse-to-fine manner. Finally, we define a distance function to measure the trajectory similarity to find similar trajectories. Through the experiments, we examine the robustness and effectiveness of the proposed integral invariants and find that they can capture the motion cues in trajectory matching and sign recognition satisfactorily.

Trajectory Shape Analysis and Anomaly Detection Utilizing Information Theory Tools

Directory of Open Access Journals (Sweden)

Yuejun Guo

2017-06-01

Full Text Available In this paper, we propose to improve trajectory shape analysis by explicitly considering the speed attribute of trajectory data, and to successfully achieve anomaly detection. The shape of object motion trajectory is modeled using Kernel Density Estimation (KDE, making use of both the angle attribute of the trajectory and the speed of the moving object. An unsupervised clustering algorithm, based on the Information Bottleneck (IB method, is employed for trajectory learning to obtain an adaptive number of trajectory clusters through maximizing the Mutual Information (MI between the clustering result and a feature set of the trajectory data. Furthermore, we propose to effectively enhance the performance of IB by taking into account the clustering quality in each iteration of the clustering procedure. The trajectories are determined as either abnormal (infrequently observed or normal by a measure based on Shannon entropy. Extensive tests on real-world and synthetic data show that the proposed technique behaves very well and outperforms the state-of-the-art methods.

Robust Takagi-Sugeno Fuzzy Dynamic Regulator for Trajectory Tracking of a Pendulum-Cart System

Directory of Open Access Journals (Sweden)

Miguel A. Llama

2015-01-01

Full Text Available Starting from a nonlinear model for a pendulum-cart system, on which viscous friction is considered, a Takagi-Sugeno (T-S fuzzy augmented model (TSFAM as well as a TSFAM with uncertainty (TSFAMwU is proposed. Since the design of a T-S fuzzy controller is based on the T-S fuzzy model of the nonlinear system, then, to address the trajectory tracking problem of the pendulum-cart system, three T-S fuzzy controllers are proposed via parallel distributed compensation: (1 a T-S fuzzy servo controller (TSFSC designed from the TSFAM; (2 a robust TSFSC (RTSFSC designed from the TSFAMwU; and (3 a robust T-S fuzzy dynamic regulator (RTSFDR designed from the RTSFSC with the addition of a T-S fuzzy observer, which estimates cart and pendulum velocities. Both TSFAM and TSFAMwU are comprised of two fuzzy rules and designed via local approximation in fuzzy partition spaces technique. Feedback gains for the three fuzzy controllers are obtained via linear matrix inequalities approach. A swing-up controller is developed to swing the pendulum up from its pendant position to its upright position. Real-time experiments validate the effectiveness of the proposed schemes, keeping the pendulum in its upright position while the cart follows a reference signal, standing out the RTSFDR.

An Optimal Control Modification to Model-Reference Adaptive Control for Fast Adaptation

Science.gov (United States)

Nguyen, Nhan T.; Krishnakumar, Kalmanje; Boskovic, Jovan

2008-01-01

This paper presents a method that can achieve fast adaptation for a class of model-reference adaptive control. It is well-known that standard model-reference adaptive control exhibits high-gain control behaviors when a large adaptive gain is used to achieve fast adaptation in order to reduce tracking error rapidly. High gain control creates high-frequency oscillations that can excite unmodeled dynamics and can lead to instability. The fast adaptation approach is based on the minimization of the squares of the tracking error, which is formulated as an optimal control problem. The necessary condition of optimality is used to derive an adaptive law using the gradient method. This adaptive law is shown to result in uniform boundedness of the tracking error by means of the Lyapunov s direct method. Furthermore, this adaptive law allows a large adaptive gain to be used without causing undesired high-gain control effects. The method is shown to be more robust than standard model-reference adaptive control. Simulations demonstrate the effectiveness of the proposed method.

Dual color single particle tracking via nanobodies

International Nuclear Information System (INIS)

Albrecht, David; Winterflood, Christian M; Ewers, Helge

2015-01-01

Single particle tracking is a powerful tool to investigate the function of biological molecules by following their motion in space. However, the simultaneous tracking of two different species of molecules is still difficult to realize without compromising the length or density of trajectories, the localization accuracy or the simplicity of the assay. Here, we demonstrate a simple dual color single particle tracking assay using small, bright, high-affinity labeling via nanobodies of accessible targets with widely available instrumentation. We furthermore apply a ratiometric step-size analysis method to visualize differences in apparent membrane viscosity. (paper)

Temperature uniformity control in RTP using multivariable adaptive control

Energy Technology Data Exchange (ETDEWEB)

Morales, S.; Dahhou, B.; Dilhac, J.M. [Centre National de la Recherche Scientifique (CNRS), 31 - Toulouse (France); Morales, S.

1995-12-31

In Rapid Thermal Processing (RTP) control of the wafer temperature during all processing to get good trajectory following, together with spatial temperature uniformity, is essential. It is well know as RTP process is nonlinear, classical control laws are not very efficient. In this work, the authors aim at studying the applicability of MIMO (Multiple Inputs Multiple Outputs) adaptive techniques to solve the temperature control problems in RTP. A multivariable linear discrete time CARIMA (Controlled Auto Regressive Integrating Moving Average) model of the highly non-linear process is identified on-line using a robust identification technique. The identified model is used to compute an infinite time LQ (Linear Quadratic) based control law, with a partial state reference model. This reference model smooths the original setpoint sequence, and at the same time gives a tracking capability to the LQ control law. After an experimental open-loop investigation, the results of the application of the adaptive control law are presented. Finally, some comments on the future difficulties and developments of the application of adaptive control in RTP are given. (author) 13 refs.

Non-MTC gait cycles: An adaptive toe trajectory control strategy in older adults.

Science.gov (United States)

Santhiranayagam, Braveena K; Sparrow, W A; Lai, Daniel T H; Begg, Rezaul K

2017-03-01

Minimum-toe-clearance (MTC) above the walking surface is a critical representation of toe-trajectory control due to its association with tripping risk. Not all gait cycles exhibit a clearly defined MTC within the swing phase but there have been few previous accounts of the biomechanical characteristics of non-MTC gait cycles. The present report investigated the within-subject non-MTC gait cycle characteristics of 15 older adults (mean 73.1 years) and 15 young controls (mean 26.1 years). Participants performed the following tasks on a motorized treadmill: preferred speed walking, dual task walking (carrying a glass of water) and a dual-task speed-matched control. Toe position-time coordinates were acquired using a 3 dimensional motion capture system. When MTC was present, toe height at MTC (MTC height ) was extracted. The proportion of non-MTC gait cycles was computed for the age groups and individuals. For non-MTC gait cycles an 'indicative' toe height at the individual's average swing phase time (MTC time ) for observed MTC cycles was averaged across multiple non-MTC gait cycles. In preferred-speed walking Young demonstrated 2.9% non-MTC gait cycles and Older 18.7%. In constrained walking conditions both groups increased non-MTC gait cycles and some older adults revealed over 90%, confirming non-MTC gait cycles as an ageing-related phenomenon in lower limb trajectory control. For all participants median indicative toe-height on non-MTC gait cycles was greater than median MTC height . This result suggests that eliminating the biomechanically hazardous MTC event by adopting more of the higher-clearance non-MTC gait cycles, is adaptive in reducing the likelihood of toe-ground contact. Copyright © 2017 Elsevier B.V. All rights reserved.

Adaptive vehicle motion estimation and prediction

Science.gov (United States)

Zhao, Liang; Thorpe, Chuck E.

1999-01-01

Accurate motion estimation and reliable maneuver prediction enable an automated car to react quickly and correctly to the rapid maneuvers of the other vehicles, and so allow safe and efficient navigation. In this paper, we present a car tracking system which provides motion estimation, maneuver prediction and detection of the tracked car. The three strategies employed - adaptive motion modeling, adaptive data sampling, and adaptive model switching probabilities - result in an adaptive interacting multiple model algorithm (AIMM). The experimental results on simulated and real data demonstrate that our tracking system is reliable, flexible, and robust. The adaptive tracking makes the system intelligent and useful in various autonomous driving tasks.

Improving Energy Efficiency of an Autonomous Bicycle with Adaptive Controller Design

Directory of Open Access Journals (Sweden)

David Rodriguez-Rosa

2017-05-01

Full Text Available A method is proposed to achieve lateral stability of an autonomous bicycle with only the rotation of the front wheel. This can be achieved with a classic controller. However, if the energy consumption of the bicycle also has to be minimized, this solution is not valid. To solve this problem, an adaptive controller has been designed, which modifies its gains according to the bicycle’s forward velocity, adapting its response with minimum energy consumption and satisfying the design specifications. The study demonstrates the efficiency of the proposed control, achieving an energy saving of 73 . 8 % in trajectory tracking with respect to a conventional proportional-integral ( P I controller. These results show the importance of designing energy-efficient controllers, not only for autonomous vehicles but also for any automatic system where the energy consumption can be minimized.

Adaptive tracking control for active suspension systems with non-ideal actuators

Science.gov (United States)

Pan, Huihui; Sun, Weichao; Jing, Xingjian; Gao, Huijun; Yao, Jianyong

2017-07-01

As a critical component of transportation vehicles, active suspension systems are instrumental in the improvement of ride comfort and maneuverability. However, practical active suspensions commonly suffer from parameter uncertainties (e.g., the variations of payload mass and suspension component parameters), external disturbances and especially the unknown non-ideal actuators (i.e., dead-zone and hysteresis nonlinearities), which always significantly deteriorate the control performance in practice. To overcome these issues, this paper synthesizes an adaptive tracking control strategy for vehicle suspension systems to achieve suspension performance improvements. The proposed control algorithm is formulated by developing a unified framework of non-ideal actuators rather than a separate way, which is a simple yet effective approach to remove the unexpected nonlinear effects. From the perspective of practical implementation, the advantages of the presented controller for active suspensions include that the assumptions on the measurable actuator outputs, the prior knowledge of nonlinear actuator parameters and the uncertain parameters within a known compact set are not required. Furthermore, the stability of the closed-loop suspension system is theoretically guaranteed by rigorous mathematical analysis. Finally, the effectiveness of the presented adaptive control scheme is confirmed using comparative numerical simulation validations.

Trajectories of suicidal ideation over 6 months among 482 outpatients with bipolar disorder

DEFF Research Database (Denmark)

Köhler-Forsberg, Ole; Madsen, Trine; Behrendt-Møller, Ida

2017-01-01

INTRODUCTION: Suicidal ideation occurs frequently among individuals with bipolar disorder; however, its course and persistence over time remains unclear. We aimed to investigate 6-months trajectories of suicidal ideation among adults with bipolar disorder. METHODS: The Bipolar CHOICE study...... randomized 482 outpatients with bipolar disorder to 6 months of lithium- or quetiapine-based treatment including other psychotropic medications as clinically indicated. Participants were asked at 9 visits about suicidal ideation using the Concise Health Risk Tracking scale. We performed latent Growth Mixture...... Modelling analysis to empirically identify trajectories of suicidal ideation. Multinomial logistic regression analyses were applied to estimate associations between trajectories and potential predictors. RESULTS: We identified four distinct trajectories. The Moderate-Stable group represented 11...

Detection of Diffusion Heterogeneity in Single Particle Tracking Trajectories Using a Hidden Markov Model with Measurement Noise Propagation

Science.gov (United States)

Slator, Paddy J.; Cairo, Christopher W.; Burroughs, Nigel J.

2015-01-01

We develop a Bayesian analysis framework to detect heterogeneity in the diffusive behaviour of single particle trajectories on cells, implementing model selection to classify trajectories as either consistent with Brownian motion or with a two-state (diffusion coefficient) switching model. The incorporation of localisation accuracy is essential, as otherwise false detection of switching within a trajectory was observed and diffusion coefficient estimates were inflated. Since our analysis is on a single trajectory basis, we are able to examine heterogeneity between trajectories in a quantitative manner. Applying our method to the lymphocyte function-associated antigen 1 (LFA-1) receptor tagged with latex beads (4 s trajectories at 1000 frames s−1), both intra- and inter-trajectory heterogeneity were detected; 12–26% of trajectories display clear switching between diffusive states dependent on condition, whilst the inter-trajectory variability is highly structured with the diffusion coefficients being related by D 1 = 0.68D 0 − 1.5 × 104 nm2 s−1, suggestive that on these time scales we are detecting switching due to a single process. Further, the inter-trajectory variability of the diffusion coefficient estimates (1.6 × 102 − 2.6 × 105 nm2 s−1) is very much larger than the measurement uncertainty within trajectories, suggesting that LFA-1 aggregation and cytoskeletal interactions are significantly affecting mobility, whilst the timescales of these processes are distinctly different giving rise to inter- and intra-trajectory variability. There is also an ‘immobile’ state (defined as D models within membranes incorporating aggregation, binding to the cytoskeleton, or traversing membrane microdomains. PMID:26473352

Track models and radiation chemical yields

International Nuclear Information System (INIS)

Chatterjee, A.; Magee, J.L.

1987-01-01

The authors are concerned only with systems in which single track effects dominate and radiation chemical yields are sums of yields for individual tracks. The authors know that the energy deposits of heavy particle tracks are composed of spurs along the particle trajectory (about one-half of the energy) and a more diffuse pattern composed of the tracks of knock-on electrons, called the penumbra (about one-half of the energy). The simplest way to introduce the concept of a unified track model for heavy particles is to consider the special case of the track of a heavy particle with an LET below 0.2-0.3eV/A, which in practice limits us to protons, deuterons, or particles with energy above 100 MeV per nucleon. At these LET values, to a good approximation, spurs formed by the main particle track can be considered to remain isolated throughout the radiation chemical reactions

Robotic excavator trajectory control using an improved GA based PID controller

Science.gov (United States)

Feng, Hao; Yin, Chen-Bo; Weng, Wen-wen; Ma, Wei; Zhou, Jun-jing; Jia, Wen-hua; Zhang, Zi-li

2018-05-01

In order to achieve excellent trajectory tracking performances, an improved genetic algorithm (IGA) is presented to search for the optimal proportional-integral-derivative (PID) controller parameters for the robotic excavator. Firstly, the mathematical model of kinematic and electro-hydraulic proportional control system of the excavator are analyzed based on the mechanism modeling method. On this basis, the actual model of the electro-hydraulic proportional system are established by the identification experiment. Furthermore, the population, the fitness function, the crossover probability and mutation probability of the SGA are improved: the initial PID parameters are calculated by the Ziegler-Nichols (Z-N) tuning method and the initial population is generated near it; the fitness function is transformed to maintain the diversity of the population; the probability of crossover and mutation are adjusted automatically to avoid premature convergence. Moreover, a simulation study is carried out to evaluate the time response performance of the proposed controller, i.e., IGA based PID against the SGA and Z-N based PID controllers with a step signal. It was shown from the simulation study that the proposed controller provides the least rise time and settling time of 1.23 s and 1.81 s, respectively against the other tested controllers. Finally, two types of trajectories are designed to validate the performances of the control algorithms, and experiments are performed on the excavator trajectory control experimental platform. It was demonstrated from the experimental work that the proposed IGA based PID controller improves the trajectory accuracy of the horizontal line and slope line trajectories by 23.98% and 23.64%, respectively in comparison to the SGA tuned PID controller. The results further indicate that the proposed IGA tuning based PID controller is effective for improving the tracking accuracy, which may be employed in the trajectory control of an actual excavator.

An automated dose tracking system for adaptive radiation therapy.

Science.gov (United States)

Liu, Chang; Kim, Jinkoo; Kumarasiri, Akila; Mayyas, Essa; Brown, Stephen L; Wen, Ning; Siddiqui, Farzan; Chetty, Indrin J

2018-02-01

The implementation of adaptive radiation therapy (ART) into routine clinical practice is technically challenging and requires significant resources to perform and validate each process step. The objective of this report is to identify the key components of ART, to illustrate how a specific automated procedure improves efficiency, and to facilitate the routine clinical application of ART. Data was used from patient images, exported from a clinical database and converted to an intermediate format for point-wise dose tracking and accumulation. The process was automated using in-house developed software containing three modularized components: an ART engine, user interactive tools, and integration tools. The ART engine conducts computing tasks using the following modules: data importing, image pre-processing, dose mapping, dose accumulation, and reporting. In addition, custom graphical user interfaces (GUIs) were developed to allow user interaction with select processes such as deformable image registration (DIR). A commercial scripting application programming interface was used to incorporate automated dose calculation for application in routine treatment planning. Each module was considered an independent program, written in C++or C#, running in a distributed Windows environment, scheduled and monitored by integration tools. The automated tracking system was retrospectively evaluated for 20 patients with prostate cancer and 96 patients with head and neck cancer, under institutional review board (IRB) approval. In addition, the system was evaluated prospectively using 4 patients with head and neck cancer. Altogether 780 prostate dose fractions and 2586 head and neck cancer dose fractions went processed, including DIR and dose mapping. On average, daily cumulative dose was computed in 3 h and the manual work was limited to 13 min per case with approximately 10% of cases requiring an additional 10 min for image registration refinement. An efficient and convenient

Robust multiple cue fusion-based high-speed and nonrigid object tracking algorithm for short track speed skating

Science.gov (United States)

Liu, Chenguang; Cheng, Heng-Da; Zhang, Yingtao; Wang, Yuxuan; Xian, Min

2016-01-01

This paper presents a methodology for tracking multiple skaters in short track speed skating competitions. Nonrigid skaters move at high speed with severe occlusions happening frequently among them. The camera is panned quickly in order to capture the skaters in a large and dynamic scene. To automatically track the skaters and precisely output their trajectories becomes a challenging task in object tracking. We employ the global rink information to compensate camera motion and obtain the global spatial information of skaters, utilize random forest to fuse multiple cues and predict the blob of each skater, and finally apply a silhouette- and edge-based template-matching and blob-evolving method to labelling pixels to a skater. The effectiveness and robustness of the proposed method are verified through thorough experiments.

Studying precipitation recycling over the Tibetan Plateau using evaporation-tagging and back-trajectory analysis

Science.gov (United States)

Gao, Y.

2017-12-01

Regional precipitation recycling (i.e., the contribution of local evaporation to local precipitation) is an important component of water cycle over the Tibetan Plateau (TP). Two methods were used to investigate regional precipitation recycling: 1) tracking of tagged atmospheric water parcels originating from evaporation in a source region (i.e., E-tagging), and 2) back-trajectory approach to track the evaporative sources contributed to precipitation in a specific region. These two methods were applied to Weather Research and Forecasting (WRF) regional climate simulations to quantify the precipitation recycling ratio in the TP for three selected years: climatologically normal, dry and wet year. The simulation region is characterized by high average elevation above 4000 m and complex terrain. The back-trajectory approach is also calculated over three sub-regions over the TP: namely western, northeastern and southeastern TP, and the E-tagging approach could provide recycling-ratio distributions over the whole TP. Three aspects are investigated to characterize the precipitation recycling: annual mean, seasonal variations and spatial distributions. Averaged over the TP, the precipitation recycling ratio estimated by the E-tagging approach is higher than that from the back-trajectory method. The back-trajectory approach uses a precipitation threshold as total precipitation in five days divided by a random number, and this number was set to 500 as a tread off between equilibrium and computational efficiency. Lower recycling ratio derived from the back-trajectory approach is related to the precipitation threshold used. The E-tagging, however, tracks every air parcel of evaporation regardless of the precipitation amount. There is no obvious seasonal variation in the recycling ratio using both methods. The E-tagging approach shows high recycling ratios in the center TP, indicating stronger land-atmospheric interactions than elsewhere.

A Path Tracking Algorithm Using Future Prediction Control with Spike Detection for an Autonomous Vehicle Robot

Directory of Open Access Journals (Sweden)

Muhammad Aizzat Zakaria

2013-08-01

Full Text Available Trajectory tracking is an important aspect of autonomous vehicles. The idea behind trajectory tracking is the ability of the vehicle to follow a predefined path with zero steady state error. The difficulty arises due to the nonlinearity of vehicle dynamics. Therefore, this paper proposes a stable tracking control for an autonomous vehicle. An approach that consists of steering wheel control and lateral control is introduced. This control algorithm is used for a non-holonomic navigation problem, namely tracking a reference trajectory in a closed loop form. A proposed future prediction point control algorithm is used to calculate the vehicle's lateral error in order to improve the performance of the trajectory tracking. A feedback sensor signal from the steering wheel angle and yaw rate sensor is used as feedback information for the controller. The controller consists of a relationship between the future point lateral error, the linear velocity, the heading error and the reference yaw rate. This paper also introduces a spike detection algorithm to track the spike error that occurs during GPS reading. The proposed idea is to take the advantage of the derivative of the steering rate. This paper aims to tackle the lateral error problem by applying the steering control law to the vehicle, and proposes a new path tracking control method by considering the future coordinate of the vehicle and the future estimated lateral error. The effectiveness of the proposed controller is demonstrated by a simulation and a GPS experiment with noisy data. The approach used in this paper is not limited to autonomous vehicles alone since the concept of autonomous vehicle tracking can be used in mobile robot platforms, as the kinematic model of these two platforms is similar.

Research on Ship Trajectory Tracking with High Precision Based on LOS

Directory of Open Access Journals (Sweden)

Hengzhi Liu

2018-01-01

Full Text Available Aiming at how precise to track by LOS, a method is proposed. The method combines the advantages of LOS simplicity and intuition, easy parameter setting and good convergence, with the features of GPC softening, multi-step prediction, rolling optimization and excellent controllability and robustness. In order to verify the effectiveness of the method, the method is simulated by Matlab. The simulation’s results show that it makes ship tracking highly precise.

Supervised Learning Applied to Air Traffic Trajectory Classification

Science.gov (United States)

Bosson, Christabelle; Nikoleris, Tasos

2018-01-01

Given the recent increase of interest in introducing new vehicle types and missions into the National Airspace System, a transition towards a more autonomous air traffic control system is required in order to enable and handle increased density and complexity. This paper presents an exploratory effort of the needed autonomous capabilities by exploring supervised learning techniques in the context of aircraft trajectories. In particular, it focuses on the application of machine learning algorithms and neural network models to a runway recognition trajectory-classification study. It investigates the applicability and effectiveness of various classifiers using datasets containing trajectory records for a month of air traffic. A feature importance and sensitivity analysis are conducted to challenge the chosen time-based datasets and the ten selected features. The study demonstrates that classification accuracy levels of 90% and above can be reached in less than 40 seconds of training for most machine learning classifiers when one track data point, described by the ten selected features at a particular time step, per trajectory is used as input. It also shows that neural network models can achieve similar accuracy levels but at higher training time costs.

Real-time Non-linear Target Tracking Control of Wheeled Mobile Robots

Institute of Scientific and Technical Information of China (English)

YU Wenyong

2006-01-01

A control strategy for real-time target tracking for wheeled mobile robots is presented. Using a modified Kalman filter for environment perception, a novel tracking control law derived from Lyapunov stability theory is introduced. Tuning of linear velocity and angular velocity with mechanical constraints is applied. The proposed control system can simultaneously solve the target trajectory prediction, real-time tracking, and posture regulation problems of a wheeled mobile robot. Experimental results illustrate the effectiveness of the proposed tracking control laws.

Online visual feedback during error-free channel trials leads to active unlearning of movement dynamics: evidence for adaptation to trajectory prediction errors.

Directory of Open Access Journals (Sweden)

Angel Lago-Rodriguez

2016-09-01

Full Text Available Prolonged exposure to movement perturbations leads to creation of motor memories which decay towards previous states when the perturbations are removed. However, it remains unclear whether this decay is due only to a spontaneous and passive recovery of the previous state. It has recently been reported that activation of reinforcement-based learning mechanisms delays the onset of the decay. This raises the question whether other motor learning mechanisms may also contribute to the retention and/or decay of the motor memory. Therefore, we aimed to test whether mechanisms of error-based motor adaptation are active during the decay of the motor memory. Forty-five right-handed participants performed point-to-point reaching movements under an external dynamic perturbation. We measured the expression of the motor memory through error-clamped (EC trials, in which lateral forces constrained movements to a straight line towards the target. We found greater and faster decay of the motor memory for participants who had access to full online visual feedback during these EC trials (Cursor group, when compared with participants who had no EC feedback regarding movement trajectory (Arc group. Importantly, we did not find between-group differences in adaptation to the external perturbation. In addition, we found greater decay of the motor memory when we artificially increased feedback errors through the manipulation of visual feedback (Augmented-Error group. Our results then support the notion of an active decay of the motor memory, suggesting that adaptive mechanisms are involved in correcting for the mismatch between predicted movement trajectories and actual sensory feedback, which leads to greater and faster decay of the motor memory.

Dynamic Learning from Adaptive Neural Control of Uncertain Robots with Guaranteed Full-State Tracking Precision

Directory of Open Access Journals (Sweden)

Min Wang

2017-01-01

Full Text Available A dynamic learning method is developed for an uncertain n-link robot with unknown system dynamics, achieving predefined performance attributes on the link angular position and velocity tracking errors. For a known nonsingular initial robotic condition, performance functions and unconstrained transformation errors are employed to prevent the violation of the full-state tracking error constraints. By combining two independent Lyapunov functions and radial basis function (RBF neural network (NN approximator, a novel and simple adaptive neural control scheme is proposed for the dynamics of the unconstrained transformation errors, which guarantees uniformly ultimate boundedness of all the signals in the closed-loop system. In the steady-state control process, RBF NNs are verified to satisfy the partial persistent excitation (PE condition. Subsequently, an appropriate state transformation is adopted to achieve the accurate convergence of neural weight estimates. The corresponding experienced knowledge on unknown robotic dynamics is stored in NNs with constant neural weight values. Using the stored knowledge, a static neural learning controller is developed to improve the full-state tracking performance. A comparative simulation study on a 2-link robot illustrates the effectiveness of the proposed scheme.

Post-flight trajectory reconstruction of suborbital free-flyers using GPS raw data

Science.gov (United States)

Ivchenko, N.; Yuan, Y.; Linden, E.

2017-08-01

This paper describes the reconstruction of postflight trajectories of suborbital free flying units by using logged GPS raw data. We took the reconstruction as a global least squares optimization problem, using both the pseudo-range and Doppler observables, and solved it by using the trust-region-reflective algorithm, which enabled navigational solutions of high accuracy. The code tracking was implemented with a large number of correlators and least squares curve fitting, in order to improve the precision of the code start times, while a more conventional phased lock loop was used for Doppler tracking. We proposed a weighting scheme to account for fast signal strength variation due to free-flier fast rotation, and a penalty for jerk to achieve a smooth solution. We applied these methods to flight data of two suborbital free flying units launched on REXUS 12 sounding rocket, reconstructing the trajectory, receiver clock error and wind up rates. The trajectory exhibits a parabola with the apogee around 80 km, and the velocity profile shows the details of payloadwobbling. The wind up rates obtained match the measurements from onboard angular rate sensors.

Post-flight trajectory reconstruction of suborbital free-flyers using GPS raw data

Directory of Open Access Journals (Sweden)

Ivchenko N.

2017-08-01

Full Text Available This paper describes the reconstruction of postflight trajectories of suborbital free flying units by using logged GPS raw data. We took the reconstruction as a global least squares optimization problem, using both the pseudo-range and Doppler observables, and solved it by using the trust-region-reflective algorithm, which enabled navigational solutions of high accuracy. The code tracking was implemented with a large number of correlators and least squares curve fitting, in order to improve the precision of the code start times, while a more conventional phased lock loop was used for Doppler tracking. We proposed a weighting scheme to account for fast signal strength variation due to free-flier fast rotation, and a penalty for jerk to achieve a smooth solution. We applied these methods to flight data of two suborbital free flying units launched on REXUS 12 sounding rocket, reconstructing the trajectory, receiver clock error and wind up rates. The trajectory exhibits a parabola with the apogee around 80 km, and the velocity profile shows the details of payloadwobbling. The wind up rates obtained match the measurements from onboard angular rate sensors.

Trajectory control of robot manipulators with closed-kinematic chain mechanism

Science.gov (United States)

Nguyen, Charles C.; Pooran, Farhad J.; Premack, Timothy

1987-01-01

The problem of Cartesian trajectory control of a closed-kinematic chain mechanism robot manipulator, recently built at CAIR to study the assembly of NASA hardware for the future Space Station, is considered. The study is performed by both computer simulation and experimentation for tracking of three different paths: a straight line, a sinusoid, and a circle. Linearization and pole placement methods are employed to design controller gains. Results show that the controllers are robust and there are good agreements between simulation and experimentation. The results also show excellent tracking quality and small overshoots.

Determining of the track parameters in solid state nuclear track detectors Cr 39 due to alpha particles

International Nuclear Information System (INIS)

Kostic, D.; Nikezic, D.

1997-01-01

An equation of the etch pit wall is proposed to be used for simulation of the track growth and calculating the major and the minor axis of etch pit opening. Dependence on the following parameters is set up: distance along a track from the point where the particle entered the detector, ratio of the track etch wall to the bulk etch rate, integration constant determined from particle penetration depth and normal distance from the particle trajectory to the etch pit wall. The corresponding computer program was written. The input parameters of this program are: alpha particles energy, incidence angle and removed layer; the output gives track parameters. The results obtained by this method are compared to another approach given by Somogy and Szalay (1973) and a reasonably good agreement is found. (author)

Performance enhancement for a GPS vector-tracking loop utilizing an adaptive iterated extended Kalman filter.

Science.gov (United States)

Chen, Xiyuan; Wang, Xiying; Xu, Yuan

2014-12-09

This paper deals with the problem of state estimation for the vector-tracking loop of a software-defined Global Positioning System (GPS) receiver. For a nonlinear system that has the model error and white Gaussian noise, a noise statistics estimator is used to estimate the model error, and based on this, a modified iterated extended Kalman filter (IEKF) named adaptive iterated Kalman filter (AIEKF) is proposed. A vector-tracking GPS receiver utilizing AIEKF is implemented to evaluate the performance of the proposed method. Through road tests, it is shown that the proposed method has an obvious accuracy advantage over the IEKF and Adaptive Extended Kalman filter (AEKF) in position determination. The results show that the proposed method is effective to reduce the root-mean-square error (RMSE) of position (including longitude, latitude and altitude). Comparing with EKF, the position RMSE values of AIEKF are reduced by about 45.1%, 40.9% and 54.6% in the east, north and up directions, respectively. Comparing with IEKF, the position RMSE values of AIEKF are reduced by about 25.7%, 19.3% and 35.7% in the east, north and up directions, respectively. Compared with AEKF, the position RMSE values of AIEKF are reduced by about 21.6%, 15.5% and 30.7% in the east, north and up directions, respectively.

Hybrid Adaptive Flight Control with Model Inversion Adaptation

Science.gov (United States)

Nguyen, Nhan

2011-01-01

This study investigates a hybrid adaptive flight control method as a design possibility for a flight control system that can enable an effective adaptation strategy to deal with off-nominal flight conditions. The hybrid adaptive control blends both direct and indirect adaptive control in a model inversion flight control architecture. The blending of both direct and indirect adaptive control provides a much more flexible and effective adaptive flight control architecture than that with either direct or indirect adaptive control alone. The indirect adaptive control is used to update the model inversion controller by an on-line parameter estimation of uncertain plant dynamics based on two methods. The first parameter estimation method is an indirect adaptive law based on the Lyapunov theory, and the second method is a recursive least-squares indirect adaptive law. The model inversion controller is therefore made to adapt to changes in the plant dynamics due to uncertainty. As a result, the modeling error is reduced that directly leads to a decrease in the tracking error. In conjunction with the indirect adaptive control that updates the model inversion controller, a direct adaptive control is implemented as an augmented command to further reduce any residual tracking error that is not entirely eliminated by the indirect adaptive control.

Evaluation of an active magnetic resonance tracking system for interstitial brachytherapy

Energy Technology Data Exchange (ETDEWEB)

Wang, Wei, E-mail: wwang21@partners.org [Department of Radiology, Brigham and Women’s Hospital, Boston, Massachusetts 02115 and Department of Radiation Oncology, Dana-Farber Cancer Institute/Brigham and Women’s Hospital, Boston, Massachusetts 02115 (United States); Viswanathan, Akila N.; Damato, Antonio L.; Cormack, Robert A. [Department of Radiation Oncology, Dana-Farber Cancer Institute/Brigham and Women’s Hospital, Boston, Massachusetts 02115 (United States); Chen, Yue; Tse, Zion [Department of Engineering, The University of Georgia, Athens, Georgia 30602 (United States); Pan, Li [Siemens Healthcare USA, Baltimore, Maryland 21287 (United States); Tokuda, Junichi; Schmidt, Ehud J. [Department of Radiology, Brigham and Women’s Hospital, Boston, Massachusetts 02115 (United States); Seethamraju, Ravi T. [Siemens Healthcare USA, Boston, Massachusetts 02115 (United States); Dumoulin, Charles L. [Radiology, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio 45229 (United States)

2015-12-15

Purpose: In gynecologic cancers, magnetic resonance (MR) imaging is the modality of choice for visualizing tumors and their surroundings because of superior soft-tissue contrast. Real-time MR guidance of catheter placement in interstitial brachytherapy facilitates target coverage, and would be further improved by providing intraprocedural estimates of dosimetric coverage. A major obstacle to intraprocedural dosimetry is the time needed for catheter trajectory reconstruction. Herein the authors evaluate an active MR tracking (MRTR) system which provides rapid catheter tip localization and trajectory reconstruction. The authors assess the reliability and spatial accuracy of the MRTR system in comparison to standard catheter digitization using magnetic resonance imaging (MRI) and CT. Methods: The MRTR system includes a stylet with microcoils mounted on its shaft, which can be inserted into brachytherapy catheters and tracked by a dedicated MRTR sequence. Catheter tip localization errors of the MRTR system and their dependence on catheter locations and orientation inside the MR scanner were quantified with a water phantom. The distances between the tracked tip positions of the MRTR stylet and the predefined ground-truth tip positions were calculated for measurements performed at seven locations and with nine orientations. To evaluate catheter trajectory reconstruction, fifteen brachytherapy catheters were placed into a gel phantom with an embedded catheter fixation framework, with parallel or crossed paths. The MRTR stylet was then inserted sequentially into each catheter. During the removal of the MRTR stylet from within each catheter, a MRTR measurement was performed at 40 Hz to acquire the instantaneous stylet tip position, resulting in a series of three-dimensional (3D) positions along the catheter’s trajectory. A 3D polynomial curve was fit to the tracked positions for each catheter, and equally spaced dwell points were then generated along the curve. High

Evaluation of an active magnetic resonance tracking system for interstitial brachytherapy

International Nuclear Information System (INIS)

Wang, Wei; Viswanathan, Akila N.; Damato, Antonio L.; Cormack, Robert A.; Chen, Yue; Tse, Zion; Pan, Li; Tokuda, Junichi; Schmidt, Ehud J.; Seethamraju, Ravi T.; Dumoulin, Charles L.

2015-01-01

Purpose: In gynecologic cancers, magnetic resonance (MR) imaging is the modality of choice for visualizing tumors and their surroundings because of superior soft-tissue contrast. Real-time MR guidance of catheter placement in interstitial brachytherapy facilitates target coverage, and would be further improved by providing intraprocedural estimates of dosimetric coverage. A major obstacle to intraprocedural dosimetry is the time needed for catheter trajectory reconstruction. Herein the authors evaluate an active MR tracking (MRTR) system which provides rapid catheter tip localization and trajectory reconstruction. The authors assess the reliability and spatial accuracy of the MRTR system in comparison to standard catheter digitization using magnetic resonance imaging (MRI) and CT. Methods: The MRTR system includes a stylet with microcoils mounted on its shaft, which can be inserted into brachytherapy catheters and tracked by a dedicated MRTR sequence. Catheter tip localization errors of the MRTR system and their dependence on catheter locations and orientation inside the MR scanner were quantified with a water phantom. The distances between the tracked tip positions of the MRTR stylet and the predefined ground-truth tip positions were calculated for measurements performed at seven locations and with nine orientations. To evaluate catheter trajectory reconstruction, fifteen brachytherapy catheters were placed into a gel phantom with an embedded catheter fixation framework, with parallel or crossed paths. The MRTR stylet was then inserted sequentially into each catheter. During the removal of the MRTR stylet from within each catheter, a MRTR measurement was performed at 40 Hz to acquire the instantaneous stylet tip position, resulting in a series of three-dimensional (3D) positions along the catheter’s trajectory. A 3D polynomial curve was fit to the tracked positions for each catheter, and equally spaced dwell points were then generated along the curve. High

Adaptive eye-gaze tracking using neural-network-based user profiles to assist people with motor disability.

Science.gov (United States)

Sesin, Anaelis; Adjouadi, Malek; Cabrerizo, Mercedes; Ayala, Melvin; Barreto, Armando

2008-01-01

This study developed an adaptive real-time human-computer interface (HCI) that serves as an assistive technology tool for people with severe motor disability. The proposed HCI design uses eye gaze as the primary computer input device. Controlling the mouse cursor with raw eye coordinates results in sporadic motion of the pointer because of the saccadic nature of the eye. Even though eye movements are subtle and completely imperceptible under normal circumstances, they considerably affect the accuracy of an eye-gaze-based HCI. The proposed HCI system is novel because it adapts to each specific user's different and potentially changing jitter characteristics through the configuration and training of an artificial neural network (ANN) that is structured to minimize the mouse jitter. This task is based on feeding the ANN a user's initially recorded eye-gaze behavior through a short training session. The ANN finds the relationship between the gaze coordinates and the mouse cursor position based on the multilayer perceptron model. An embedded graphical interface is used during the training session to generate user profiles that make up these unique ANN configurations. The results with 12 subjects in test 1, which involved following a moving target, showed an average jitter reduction of 35%; the results with 9 subjects in test 2, which involved following the contour of a square object, showed an average jitter reduction of 53%. For both results, the outcomes led to trajectories that were significantly smoother and apt at reaching fixed or moving targets with relative ease and within a 5% error margin or deviation from desired trajectories. The positive effects of such jitter reduction are presented graphically for visual appreciation.

Almost-global tracking for a rigid body with internal rotors

OpenAIRE

Nayak, Aradhana; Banavar, Ravi N.

2017-01-01

Almost-global orientation trajectory tracking for a rigid body with external actuation has been well studied in the literature, and in the geometric setting as well. The tracking control law relies on the fact that a rigid body is a simple mechanical system (SMS) on the $3-$dimensional group of special orthogonal matrices. However, the problem of designing feedback control laws for tracking using internal actuation mechanisms, like rotors or control moment gyros, has received lesser attention...

Back to the Future: Consistency-Based Trajectory Tracking

Science.gov (United States)

Kurien, James; Nayak, P. Pandurand; Norvig, Peter (Technical Monitor)

2000-01-01

Given a model of a physical process and a sequence of commands and observations received over time, the task of an autonomous controller is to determine the likely states of the process and the actions required to move the process to a desired configuration. We introduce a representation and algorithms for incrementally generating approximate belief states for a restricted but relevant class of partially observable Markov decision processes with very large state spaces. The algorithm presented incrementally generates, rather than revises, an approximate belief state at any point by abstracting and summarizing segments of the likely trajectories of the process. This enables applications to efficiently maintain a partial belief state when it remains consistent with observations and revisit past assumptions about the process' evolution when the belief state is ruled out. The system presented has been implemented and results on examples from the domain of spacecraft control are presented.

Parameter trajectory analysis to identify treatment effects of pharmacological interventions.

Directory of Open Access Journals (Sweden)

Christian A Tiemann

Full Text Available The field of medical systems biology aims to advance understanding of molecular mechanisms that drive disease progression and to translate this knowledge into therapies to effectively treat diseases. A challenging task is the investigation of long-term effects of a (pharmacological treatment, to establish its applicability and to identify potential side effects. We present a new modeling approach, called Analysis of Dynamic Adaptations in Parameter Trajectories (ADAPT, to analyze the long-term effects of a pharmacological intervention. A concept of time-dependent evolution of model parameters is introduced to study the dynamics of molecular adaptations. The progression of these adaptations is predicted by identifying necessary dynamic changes in the model parameters to describe the transition between experimental data obtained during different stages of the treatment. The trajectories provide insight in the affected underlying biological systems and identify the molecular events that should be studied in more detail to unravel the mechanistic basis of treatment outcome. Modulating effects caused by interactions with the proteome and transcriptome levels, which are often less well understood, can be captured by the time-dependent descriptions of the parameters. ADAPT was employed to identify metabolic adaptations induced upon pharmacological activation of the liver X receptor (LXR, a potential drug target to treat or prevent atherosclerosis. The trajectories were investigated to study the cascade of adaptations. This provided a counter-intuitive insight concerning the function of scavenger receptor class B1 (SR-B1, a receptor that facilitates the hepatic uptake of cholesterol. Although activation of LXR promotes cholesterol efflux and -excretion, our computational analysis showed that the hepatic capacity to clear cholesterol was reduced upon prolonged treatment. This prediction was confirmed experimentally by immunoblotting measurements of SR-B1

The trajectory of hope: pathways to find meaning and reconstructing the self after a spinal cord injury.

Science.gov (United States)

Parashar, D

2015-07-01

This is a qualitative study. To evaluate and track the importance and the continuum of hope, and its trajectory, from the point of view of the individual with a spinal cord injury (SCI) and a rehabilitation psychologist. This study was conducted in the Indian Spinal Injuries Centre, New Delhi, India, and in patients' homes in the National Capital Region, India. Twenty individuals with an SCI were interviewed for the study at intervals of 2 weeks, 6 months, 1 year and 2 years since the time of the injury. Semi-structured interviews were conducted, in which the following theoretical research questions were investigated: 'What is the meaning, relevance and significance of hope in the individual's life following an SCI? Does the meaning and subject of hope change at different points in time?' Three distinctive themes markedly emerged in the trajectory of hope: (1) Hope for a complete recovery; (2) hope for self-reliance despite the injury; and (3) hope for an optimum quality of life. The make-up of each theme, its significance and contribution to recovery and/or rehabilitation, while tracking the influence of time since injury, family and friends, as well as other agencies and pathways, are discussed. After sustaining a life-altering injury, hope becomes the force that spurs individuals. Psychologists and rehabilitation counselors need to focus on instilling realistic hope, goal setting, sustaining motivation, enabling adaptive appraisals and problem-solving. Further recommendations include developing and testing interventions against the context of the continuum of hope.

Trajectory data analyses for pedestrian space-time activity study.

Science.gov (United States)

Qi, Feng; Du, Fei

2013-02-25

automatic module. Trajectory segmentation(5) involves the identification of indoor and outdoor parts from pre-processed space-time tracks. Again, both interactive visual segmentation and automatic segmentation are supported. Segmented space-time tracks are then analyzed to derive characteristics of one's activity space such as activity radius etc. Density estimation and visualization are used to examine large amount of trajectory data to model hot spots and interactions. We demonstrate both density surface mapping(6) and density volume rendering(7). We also include a couple of other exploratory data analyses (EDA) and visualizations tools, such as Google Earth animation support and connection analysis. The suite of analytical as well as visual methods presented in this paper may be applied to any trajectory data for space-time activity studies.

Advanced alignment of the ATLAS tracking system

CERN Document Server

AUTHOR|(CDS)2085334; The ATLAS collaboration

2016-01-01

In order to reconstruct the trajectories of charged particles, the ATLAS experiment exploits a tracking system built using different technologies, silicon planar modules or microstrips (PIX and SCT detectors) and gaseous drift tubes (TRT), all embedded in a 2T solenoidal magnetic field. Misalignments of the active detector elements and deformations of the structures (which can lead to \\textit{Weak Modes}) deteriorate resolution of the track reconstruction and lead to systematic biases on the measured track parameters. The applied alignment procedures exploit various advanced techniques in order to minimise track-hit residuals and remove detector deformations. For the LHC Run II, the Pixel Detector has been refurbished and upgraded with the installation of a new pixel layer, the Insertable B-layer (IBL).

Ground-based telescope pointing and tracking optimization using a neural controller.

Science.gov (United States)

Mancini, D; Brescia, M; Schipani, P

2003-01-01

Neural network models (NN) have emerged as important components for applications of adaptive control theories. Their basic generalization capability, based on acquired knowledge, together with execution rapidity and correlation ability between input stimula, are basic attributes to consider NN as an extremely powerful tool for on-line control of complex systems. By a control system point of view, not only accuracy and speed, but also, in some cases, a high level of adaptation capability is required in order to match all working phases of the whole system during its lifetime. This is particularly remarkable for a new generation ground-based telescope control system. Infact, strong changes in terms of system speed and instantaneous position error tolerance are necessary, especially in case of trajectory disturb induced by wind shake. The classical control scheme adopted in such a system is based on the proportional integral (PI) filter, already applied and implemented on a large amount of new generation telescopes, considered as a standard in this technological environment. In this paper we introduce the concept of a new approach, the neural variable structure proportional integral, (NVSPI), related to the implementation of a standard multi layer perceptron network in new generation ground-based Alt-Az telescope control systems. Its main purpose is to improve adaptive capability of the Variable structure proportional integral model, an already innovative control scheme recently introduced by authors [Proc SPIE (1997)], based on a modified version of classical PI control model, in terms of flexibility and accuracy of the dynamic response range also in presence of wind noise effects. The realization of a powerful well tested and validated telescope model simulation system allowed the possibility to directly compare performances of the two control schemes on simulated tracking trajectories, revealing extremely encouraging results in terms of NVSPI control robustness and

Advanced Alignment of the ATLAS Tracking System

CERN Document Server

Butti, P; The ATLAS collaboration

2014-01-01

In order to reconstruct the trajectories of charged particles, the ATLAS experiment exploits a tracking system built using different technologies, planar silicon modules or microstrips (PIX and SCT detectors) and gaseous drift tubes (TRT), all embedded in a 2T solenoidal magnetic field. Misalignments and deformations of the active detector elements deteriorate the track reconstruction resolution and lead to systematic biases on the measured track parameters. The alignment procedures exploits various advanced tools and techniques in order to determine for module positions and correct for deformations. For the LHC Run II, the system is being upgraded with the installation of a new pixel layer, the Insertable B-layer (IBL).

Global track finder for Belle II experiment

Energy Technology Data Exchange (ETDEWEB)

Trusov, Viktor; Feindt, Michael; Heck, Martin; Kuhr, Thomas; Goldenzweig, Pablo [Karlsruhe Institute of Technology, IEKP (Germany); Collaboration: Belle II-Collaboration

2015-07-01

We present an implementation of a method based on the Legendre transformation for reconstruction charged particle tracks in the central drift chamber of the Belle II experiment. The method is designed for fast track finding and restoring circular patterns of track hits in transverse plane. It is done by searching for common tangents to drift circles of hits in the conformal space. With known transverse trajectories longitudinal momentum estimation performed by assigning stereo hits followed by determination of the track parameters. The method includes algorithms responsible for track quality estimation and reduction of rate of fakes. The work is targeting at increasing the efficiency and reducing the execution time because the computing power available to the experiment is limited. The algorithm is developed within the Belle II software environment with using Monte-Carlo simulation for probing its efficiency.

Satellite Images-Based Obstacle Recognition and Trajectory Generation for Agricultural Vehicles

Directory of Open Access Journals (Sweden)

Mehmet Bodur

2015-12-01

Full Text Available In this study, a method for the generation of tracking trajectory points, detection and positioning of obstacles in agricultural fields have been presented. Our principal contribution is to produce traceable GPS trajectories for agricultural vehicles to be utilized by path planning algorithms, rather than a new path planning algorithm. The proposed system works with minimal initialization requirements, specifically, a single geographical coordinate entry of an agricultural field. The automation of agricultural plantation requires many aspects to be addressed, many of which have been covered in previous studies. Depending on the type of crop, different agricultural vehicles may be used in the field. However, regardless of their application, they all follow a specified trajectory in the field. This study takes advantage of satellite images for the detection and positioning of obstacles, and the generation of GPS trajectories in the agricultural realm. A set of image processing techniques is applied in Matlab for detection and positioning.

Feedback tracking control for dynamic morphing of piezocomposite actuated flexible wings

Science.gov (United States)

Wang, Xiaoming; Zhou, Wenya; Wu, Zhigang

2018-03-01

Aerodynamic properties of flexible wings can be improved via shape morphing using piezocomposite materials. Dynamic shape control of flexible wings is investigated in this study by considering the interactions between structural dynamics, unsteady aerodynamics and piezo-actuations. A novel antisymmetric angle-ply bimorph configuration of piezocomposite actuators is presented to realize coupled bending-torsional shape control. The active aeroelastic model is derived using finite element method and Theodorsen unsteady aerodynamic loads. A time-varying linear quadratic Gaussian (LQG) tracking control system is designed to enhance aerodynamic lift with pre-defined trajectories. Proof-of-concept simulations of static and dynamic shape control are presented for a scaled high-aspect-ratio wing model. Vibrations of the wing and fluctuations in aerodynamic forces are caused by using the static voltages directly in dynamic shape control. The lift response has tracked the trajectories well with favorable dynamic morphing performance via feedback tracking control.

Robust tracking control of uncertain Duffing-Holmes control systems

International Nuclear Information System (INIS)

Sun, Y.-J.

2009-01-01

In this paper, the notion of virtual stabilizability for dynamical systems is introduced and the virtual stabilizability of uncertain Duffing-Holmes control systems is investigated. Based on the time-domain approach with differential inequality, a tracking control is proposed such that the states of uncertain Duffing-Holmes control system track the desired trajectories with any pre-specified exponential decay rate and convergence radius. Moreover, we present an algorithm to find such a tracking control. Finally, a numerical example is provided to illustrate the use of the main results.

An incremental DPMM-based method for trajectory clustering, modeling, and retrieval.

Science.gov (United States)

Hu, Weiming; Li, Xi; Tian, Guodong; Maybank, Stephen; Zhang, Zhongfei

2013-05-01

Trajectory analysis is the basis for many applications, such as indexing of motion events in videos, activity recognition, and surveillance. In this paper, the Dirichlet process mixture model (DPMM) is applied to trajectory clustering, modeling, and retrieval. We propose an incremental version of a DPMM-based clustering algorithm and apply it to cluster trajectories. An appropriate number of trajectory clusters is determined automatically. When trajectories belonging to new clusters arrive, the new clusters can be identified online and added to the model without any retraining using the previous data. A time-sensitive Dirichlet process mixture model (tDPMM) is applied to each trajectory cluster for learning the trajectory pattern which represents the time-series characteristics of the trajectories in the cluster. Then, a parameterized index is constructed for each cluster. A novel likelihood estimation algorithm for the tDPMM is proposed, and a trajectory-based video retrieval model is developed. The tDPMM-based probabilistic matching method and the DPMM-based model growing method are combined to make the retrieval model scalable and adaptable. Experimental comparisons with state-of-the-art algorithms demonstrate the effectiveness of our algorithm.

PHENIX central arm tracking detectors

International Nuclear Information System (INIS)

Adcox, K.; Ajitanand, N.N.; Alexander, J.; Autrey, D.; Averbeck, R.; Azmoun, B.; Barish, K.N.; Baublis, V.V.; Belkin, R.; Bhaganatula, S.; Biggs, J.C.; Borland, D.; Botelho, S.; Bryan, W.L.; Burward-Hoy, J.; Butsyk, S.A.; Chang, W.C.; Christ, T.; Dietzsch, O.; Drees, A.; Rietz, R. du; El Chenawi, K.; Evseev, V.A.; Fellenstein, J.; Ferdousi, T.; Fraenkel, Z.; Franz, A.; Fung, S.Y.; Gannon, J.; Garpman, S.; Godoi, A.L.; Greene, S.V.; Gustafsson, H.-A.; Harder, J.; Hemmick, T.K.; Heuser, J.M.; Holzmann, W.; Hutter, R.; Issah, M.; Ivanov, V.I.; Jacak, B.V.; Jagadish, U.; Jia, J.; Johnson, S.C.; Kandasamy, A.; Kann, M.R.; Kelley, M.A.; Khanzadeev, A.V.; Khomutnikov, A.; Komkov, B.G.; Kopytine, M.L.; Kotchenda, L.; Kotchetkov, D.; Kozlov, V.S.; Kravtsov, P.A.; Kudin, L.G.; Kuriatkov, V.V.; Lacey, R.; Lauret, J.; Lebedev, A.; Lebedev, V.D.; Li, X.H.; Libby, B.; Liccardi, W.; Machnowski, R.; Mahon, J.; Markushin, D.G.; Matathias, F.; Marx, M.D.; Messer, F.; Miftakhov, N.M.; Milan, J.; Miller, T.E.; Milov, A.; Minuzzo, K.; Mioduszewski, S.; Mitchell, J.T.; Muniruzzamann, M.; Nandi, B.K.; Negrin, J.; Nilsson, P.; Nystrand, J.; O'Brien, E.; O'Connor, P.; Oskarsson, A.; Oesterman, L.; Otterlund, I.; Pancake, C.E.; Pantuev, V.S.; Petersen, R.; Pinkenburg, C.H.; Pisani, R.P.; Purwar, A.K.; Rankowitz, S.; Ravinovich, I.; Riabov, V.G.; Riabov, Yu.G.; Rosati, M.; Rose, A.A.; Roschin, E.V.; Samsonov, V.M.; Sangster, T.C.; Seto, R.; Silvermyr, D.; Sivertz, M.; Smith, M.; Solodov, G.P.; Stenlund, E.; Takagui, E.M.; Tarakanov, V.I.; Tarasenkova, O.P.; Thomas, J.L.; Trofimov, V.A.; Tserruya, I.; Tydesjoe, H.; Velkovska, J.; Velkovsky, M.; Vishnevskii, V.I.; Vorobyov, A.A.; Vznuzdaev, E.A.; Vznuzdaev, M.; Wang, H.Q.; Weimer, T.; Wolniewicz, K.; Wu, J.; Xie, W.; Young, G.R.

2003-01-01

The PHENIX tracking system consists of Drift Chambers (DC), Pad Chambers (PC) and the Time Expansion Chamber (TEC). PC1/DC and PC2/TEC/PC3 form the inner and outer tracking units, respectively. These units link the track segments that transverse the RICH and extend to the EMCal. The DC measures charged particle trajectories in the r-phi direction to determine p T of the particles and the invariant mass of particle pairs. The PCs perform 3D spatial point measurements for pattern recognition and longitudinal momentum reconstruction and provide spatial resolution of a few mm in both r-phi and z. The TEC tracks particles passing through the region between the RICH and the EMCal. The design and operational parameters of the detectors are presented and running experience during the first year of data taking with PHENIX is discussed. The observed spatial and momentum resolution is given which imposes a limitation on the identification and characterization of charged particles in various momentum ranges

Human action recognition using trajectory-based representation

Directory of Open Access Journals (Sweden)

Haiam A. Abdul-Azim

2015-07-01

Full Text Available Recognizing human actions in video sequences has been a challenging problem in the last few years due to its real-world applications. A lot of action representation approaches have been proposed to improve the action recognition performance. Despite the popularity of local features-based approaches together with “Bag-of-Words” model for action representation, it fails to capture adequate spatial or temporal relationships. In an attempt to overcome this problem, a trajectory-based local representation approaches have been proposed to capture the temporal information. This paper introduces an improvement of trajectory-based human action recognition approaches to capture discriminative temporal relationships. In our approach, we extract trajectories by tracking the detected spatio-temporal interest points named “cuboid features” with matching its SIFT descriptors over the consecutive frames. We, also, propose a linking and exploring method to obtain efficient trajectories for motion representation in realistic conditions. Then the volumes around the trajectories’ points are described to represent human actions based on the Bag-of-Words (BOW model. Finally, a support vector machine is used to classify human actions. The effectiveness of the proposed approach was evaluated on three popular datasets (KTH, Weizmann and UCF sports. Experimental results showed that the proposed approach yields considerable performance improvement over the state-of-the-art approaches.

Trajectory optimization for lunar rover performing vertical takeoff vertical landing maneuvers in the presence of terrain

Science.gov (United States)

Ma, Lin; Wang, Kexin; Xu, Zuhua; Shao, Zhijiang; Song, Zhengyu; Biegler, Lorenz T.

2018-05-01

This study presents a trajectory optimization framework for lunar rover performing vertical takeoff vertical landing (VTVL) maneuvers in the presence of terrain using variable-thrust propulsion. First, a VTVL trajectory optimization problem with three-dimensional kinematics and dynamics model, boundary conditions, and path constraints is formulated. Then, a finite-element approach transcribes the formulated trajectory optimization problem into a nonlinear programming (NLP) problem solved by a highly efficient NLP solver. A homotopy-based backtracking strategy is applied to enhance the convergence in solving the formulated VTVL trajectory optimization problem. The optimal thrust solution typically has a "bang-bang" profile considering that bounds are imposed on the magnitude of engine thrust. An adaptive mesh refinement strategy based on a constant Hamiltonian profile is designed to address the difficulty in locating the breakpoints in the thrust profile. Four scenarios are simulated. Simulation results indicate that the proposed trajectory optimization framework has sufficient adaptability to handle VTVL missions efficiently.

Finite-time tracking control for multiple non-holonomic mobile robots based on visual servoing

Science.gov (United States)

Ou, Meiying; Li, Shihua; Wang, Chaoli

2013-12-01

This paper investigates finite-time tracking control problem of multiple non-holonomic mobile robots via visual servoing. It is assumed that the pinhole camera is fixed to the ceiling, and camera parameters are unknown. The desired reference trajectory is represented by a virtual leader whose states are available to only a subset of the followers, and the followers have only interaction. First, the camera-objective visual kinematic model is introduced by utilising the pinhole camera model for each mobile robot. Second, a unified tracking error system between camera-objective visual servoing model and desired reference trajectory is introduced. Third, based on the neighbour rule and by using finite-time control method, continuous distributed cooperative finite-time tracking control laws are designed for each mobile robot with unknown camera parameters, where the communication topology among the multiple mobile robots is assumed to be a directed graph. Rigorous proof shows that the group of mobile robots converges to the desired reference trajectory in finite time. Simulation example illustrates the effectiveness of our method.

Laser tracker TSPI uncertainty quantification via centrifuge trajectory

Science.gov (United States)

Romero, Edward; Paez, Thomas; Brown, Timothy; Miller, Timothy

2009-08-01

Sandia National Laboratories currently utilizes two laser tracking systems to provide time-space-position-information (TSPI) and high speed digital imaging of test units under flight. These laser trackers have been in operation for decades under the premise of theoretical accuracies based on system design and operator estimates. Advances in optical imaging and atmospheric tracking technology have enabled opportunities to provide more precise six degree of freedom measurements from these trackers. Applying these technologies to the laser trackers requires quantified understanding of their current errors and uncertainty. It was well understood that an assortment of variables contributed to laser tracker uncertainty but the magnitude of these contributions was not quantified and documented. A series of experiments was performed at Sandia National Laboratories large centrifuge complex to quantify TSPI uncertainties of Sandia National Laboratories laser tracker III. The centrifuge was used to provide repeatable and economical test unit trajectories of a test-unit to use for TSPI comparison and uncertainty analysis. On a centrifuge, testunits undergo a known trajectory continuously with a known angular velocity. Each revolution may represent an independent test, which may be repeated many times over for magnitudes of data practical for statistical analysis. Previously these tests were performed at Sandia's rocket sled track facility but were found to be costly with challenges in the measurement ground truth TSPI. The centrifuge along with on-board measurement equipment was used to provide known ground truth position of test units. This paper discusses the experimental design and techniques used to arrive at measures of laser tracker error and uncertainty.

Particle filtering for passive fathometer tracking.

Science.gov (United States)

Michalopoulou, Zoi-Heleni; Yardim, Caglar; Gerstoft, Peter

2012-01-01

Seabed interface depths and fathometer amplitudes are tracked for an unknown and changing number of sub-bottom reflectors. This is achieved by incorporating conventional and adaptive fathometer processors into sequential Monte Carlo methods for a moving vertical line array. Sediment layering information and time-varying fathometer response amplitudes are tracked by using a multiple model particle filter with an uncertain number of reflectors. Results are compared to a classical particle filter where the number of reflectors is considered to be known. Reflector tracking is demonstrated for both conventional and adaptive processing applied to the drifting array data from the Boundary 2003 experiment. The layering information is successfully tracked by the multiple model particle filter even for noisy fathometer outputs. © 2012 Acoustical Society of America.

Adaptive Sampling of Time Series During Remote Exploration

Science.gov (United States)

Thompson, David R.

2012-01-01

This work deals with the challenge of online adaptive data collection in a time series. A remote sensor or explorer agent adapts its rate of data collection in order to track anomalous events while obeying constraints on time and power. This problem is challenging because the agent has limited visibility (all its datapoints lie in the past) and limited control (it can only decide when to collect its next datapoint). This problem is treated from an information-theoretic perspective, fitting a probabilistic model to collected data and optimizing the future sampling strategy to maximize information gain. The performance characteristics of stationary and nonstationary Gaussian process models are compared. Self-throttling sensors could benefit environmental sensor networks and monitoring as well as robotic exploration. Explorer agents can improve performance by adjusting their data collection rate, preserving scarce power or bandwidth resources during uninteresting times while fully covering anomalous events of interest. For example, a remote earthquake sensor could conserve power by limiting its measurements during normal conditions and increasing its cadence during rare earthquake events. A similar capability could improve sensor platforms traversing a fixed trajectory, such as an exploration rover transect or a deep space flyby. These agents can adapt observation times to improve sample coverage during moments of rapid change. An adaptive sampling approach couples sensor autonomy, instrument interpretation, and sampling. The challenge is addressed as an active learning problem, which already has extensive theoretical treatment in the statistics and machine learning literature. A statistical Gaussian process (GP) model is employed to guide sample decisions that maximize information gain. Nonsta tion - ary (e.g., time-varying) covariance relationships permit the system to represent and track local anomalies, in contrast with current GP approaches. Most common GP models

The trajectory prediction of spacecraft by grey method

International Nuclear Information System (INIS)

Wang, Qiyue; Wang, Zhongyu; Zhang, Zili; Wang, Yanqing; Zhou, Weihu

2016-01-01

The real-time and high-precision trajectory prediction of a moving object is a core technology in the field of aerospace engineering. The real-time monitoring and tracking technology are also significant guarantees of aerospace equipment. A dynamic trajectory prediction method called grey dynamic filter (GDF) which combines the dynamic measurement theory and grey system theory is proposed. GDF can use coordinates of the current period to extrapolate coordinates of the following period. At meantime, GDF can also keep the instantaneity of measured coordinates by the metabolism model. In this paper the optimal model length of GDF is firstly selected to improve the prediction accuracy. Then the simulation for uniformly accelerated motion and variably accelerated motion is conducted. The simulation results indicate that the mean composite position error of GDF prediction is one-fifth to that of Kalman filter (KF). By using a spacecraft landing experiment, the prediction accuracy of GDF is compared with the KF method and the primitive grey method (GM). The results show that the motion trajectory of spacecraft predicted by GDF is much closer to actual trajectory than the other two methods. The mean composite position error calculated by GDF is one-eighth to KF and one-fifth to GM respectively. (paper)

Radiation-hardened fast acquisition/weak signal tracking system and method

Science.gov (United States)

Winternitz, Luke (Inventor); Boegner, Gregory J. (Inventor); Sirotzky, Steve (Inventor)

2009-01-01

A global positioning system (GPS) receiver and method of acquiring and tracking GPS signals comprises an antenna adapted to receive GPS signals; an analog radio frequency device operatively connected to the antenna and adapted to convert the GPS signals from an analog format to a digital format; a plurality of GPS signal tracking correlators operatively connected to the analog RF device; a GPS signal acquisition component operatively connected to the analog RF device and the plurality of GPS signal tracking correlators, wherein the GPS signal acquisition component is adapted to calculate a maximum vector on a databit correlation grid; and a microprocessor operatively connected to the plurality of GPS signal tracking correlators and the GPS signal acquisition component, wherein the microprocessor is adapted to compare the maximum vector with a predetermined correlation threshold to allow the GPS signal to be fully acquired and tracked.

Principal direction of inertia for 3D trajectories from patient-specific TMJ movement.

Science.gov (United States)

Kim, Dae-Seung; Choi, Soon-Chul; Lee, Sam-Sun; Heo, Min-Suk; Huh, Kyung-Hoe; Hwang, Soon-Jung; Kim, Seong-Ha; Yi, Won-Jin

2013-03-01

Accurate simulation and evaluation of mandibular movement is fundamental for the analysis of functional changes and effects of the mandible and maxilla before and after surgical treatments. We applied principal axes of inertia to the three-dimensional (3D) trajectories generated by patient-specific simulations of TMJ movements for the functional evaluations of mandible movement. Three-dimensional movements of the mandible and the maxilla were tracked based on a patient-specific splint and an optical tracking system. The dental occlusion recorded on the sprint provided synchronization for initial movement in the tracking and the simulation phases. The translation and rotation recorded during movement tracking was applied sequentially to the mandibular model in relation to a fixed maxilla model. The sequential 3D positions of selected landmarks on the mandible were calculated based on the reference coordinate system. The landmarks selected for analysis were bilateral condyles and pogonion points. The moment of inertia tensor was calculated with respect to the 3D trajectory points. Using the unit vectors along the principal axes derived from the tensor matrix, α, β and γ rotations around z-, y- and x-axes were determined to represent the principal directions as principal rotations respectively. The γ direction showed the higher standard deviation, variation of directions, than other directions at all the landmarks. The mandible movement has larger kinematic redundancy in the γ direction than α and β during mouth opening and closing. Principal directions of inertia would be applied to analyzing the changes in angular motion of trajectories introduced by mandibular shape changes from surgical treatments and also to the analysis of the influence of skeletal deformities on mandibular movement asymmetry. Copyright © 2012 Elsevier Ltd. All rights reserved.

Development of an Integrated Intelligent Multi -Objective Framework for UAV Trajectory Generation

Science.gov (United States)

Wilburn, Jennifer Nicole

This thesis explores a variety of path planning and trajectory generation schemes intended for small, fixed-wing Unmanned Aerial Vehicles. Throughout this analysis, discrete and pose-based methods are investigated. Pose-based methods are the focus of this research due to their increased flexibility and typically lower computational overhead. Path planning in 3 dimensions is also performed. The 3D Dubins methodology presented is an extension of a previously suggested approach and addresses both the mathematical formulation of the methodology, as well as an assessment of numerical issues encountered and the solutions implemented for these. The main contribution of this thesis is a 3-dimensional clothoid trajectory generation algorithm, which produces flyable paths of continuous curvature to ensure a more followable commanded path. This methodology is an extension of the 3D Dubins method and the 2D clothoid method, which have been implemented herein. To ensure flyability of trajectories produced by 3D pose-based trajectory generation methodologies, a set of criteria are specified to limit the possible solutions to only those flyable by the aircraft. Additionally, several assumptions are made concerning the motion of the aircraft in order to simplify the path generation problem. The 2D and 3D clothoid and Dubins trajectory planners are demonstrated through a trajectory tracking performance comparison between first the 2D Dubins and 2D clothoid methods using a position proportional-integral-derivative controller, then the 3D Dubins and 3D clothoid methods using both a position proportional-integral-derivative controller and an outer-loop non-linear dynamic inversion controller, within the WVU UAV Simulation Environment. These comparisons are demonstrated for both nominal and off-nominal conditions, and show that for both 2D and 3D implementations, the clothoid path planners yields paths with better trajectory tracking performance as compared to the Dubins path planners

Alignment of the ATLAS Inner Detector Tracking System

CERN Document Server

Lacuesta, V; The ATLAS collaboration

2010-01-01

ATLAS is a multipurpose experiment that records the LHC collisions. To reconstruct trajectories of charged particles produced in these collisions, ATLAS tracking system is equipped with silicon planar sensors and drift‐tube based detectors. They constitute the ATLAS Inner Detector. In order to achieve its scientific goals, the alignment of the ATLAS tracking system requires the determine accurately its almost 36000 degrees of freedom. Thus the demanded precision for the alignment of the silicon sensors is below 10 micrometers. This implies to use a large sample of high momentum and isolated charge particle tracks. The high level trigger selects those tracks online. Then the raw data with the hits information of the triggered tracks is stored in a calibration stream. Tracks from cosmic trigger during empty LHC bunches are also used as input for the alignment. The implementation of the track based alignment within the ATLAS software framework unifies different alignment approaches and allows the alignment of ...

Adaptive PID and Model Reference Adaptive Control Switch Controller for Nonlinear Hydraulic Actuator

Directory of Open Access Journals (Sweden)

Xin Zuo

2017-01-01

Full Text Available Nonlinear systems are modeled as piecewise linear systems at multiple operating points, where the operating points are modeled as switches between constituent linearized systems. In this paper, adaptive piecewise linear switch controller is proposed for improving the response time and tracking performance of the hydraulic actuator control system, which is essentially piecewise linear. The controller composed of PID and Model Reference Adaptive Control (MRAC adaptively chooses the proportion of these two components and makes the designed system have faster response time at the transient phase and better tracking performance, simultaneously. Then, their stability and tracking performance are analyzed and evaluated by the hydraulic actuator control system, the hydraulic actuator is controlled by the electrohydraulic system, and its model is built, which has piecewise linear characteristic. Then the controller results are compared between PID and MRAC and the switch controller designed in this paper is applied to the hydraulic actuator; it is obvious that adaptive switch controller has better effects both on response time and on tracking performance.

Tracking career performance of successful triathletes.

Science.gov (United States)

Malcata, Rita M; Hopkins, Will G; Pearson, Simon N

2014-06-01

Tracking athletes' performances over time is important but problematic for sports with large environmental effects. Here we have developed career performance trajectories for elite triathletes, investigating changes in swim, cycle, run stages, and total performance times while accounting for environmental and other external factors. Performance times of 337 female and 427 male triathletes competing in 419 international races between 2000 and 2012 were obtained from triathlon.org. Athletes were categorized according to any top 16 placing at World Championships or Olympics between 2008 and 2012. A mixed linear model accounting for race distance (sprint and Olympic), level of competition, calendar-year trend, athlete's category, and clustering of times within athletes and races was used to derive athletes' individual quadratic performance trajectories. These trajectories provided estimates of age of peak performance and predictions for the 2012 London Olympic Games. By markedly reducing the scatter of individual race times, the model produced well-fitting trajectories suitable for comparison of triathletes. Trajectories for top 16 triathletes showed different patterns for race stages and differed more among women than among men, but ages of peak total performance were similar for men and women (28 ± 3 yr, mean ± SD). Correlations between observed and predicted placings at Olympics were slightly higher than those provided by placings in races before the Olympics. Athletes' trajectories will help identify talented athletes and their weakest and strongest stages. The wider range of trajectories among women should be taken into account when setting talent identification criteria. Trajectories offer a small advantage over usual race placings for predicting men's performance. Further refinements, such as accounting for individual responses to race conditions, may improve utility of performance trajectories.

Mining continuous activity patterns from animal trajectory data

Science.gov (United States)

Wang, Y.; Luo, Ze; Baoping, Yan; Takekawa, John Y.; Prosser, Diann J.; Newman, Scott H.

2014-01-01

The increasing availability of animal tracking data brings us opportunities and challenges to intuitively understand the mechanisms of animal activities. In this paper, we aim to discover animal movement patterns from animal trajectory data. In particular, we propose a notion of continuous activity pattern as the concise representation of underlying similar spatio-temporal movements, and develop an extension and refinement framework to discover the patterns. We first preprocess the trajectories into significant semantic locations with time property. Then, we apply a projection-based approach to generate candidate patterns and refine them to generate true patterns. A sequence graph structure and a simple and effective processing strategy is further developed to reduce the computational overhead. The proposed approaches are extensively validated on both real GPS datasets and large synthetic datasets.

Neural-Network-Based Robust Optimal Tracking Control for MIMO Discrete-Time Systems With Unknown Uncertainty Using Adaptive Critic Design.

Science.gov (United States)

Liu, Lei; Wang, Zhanshan; Zhang, Huaguang

2018-04-01

This paper is concerned with the robust optimal tracking control strategy for a class of nonlinear multi-input multi-output discrete-time systems with unknown uncertainty via adaptive critic design (ACD) scheme. The main purpose is to establish an adaptive actor-critic control method, so that the cost function in the procedure of dealing with uncertainty is minimum and the closed-loop system is stable. Based on the neural network approximator, an action network is applied to generate the optimal control signal and a critic network is used to approximate the cost function, respectively. In contrast to the previous methods, the main features of this paper are: 1) the ACD scheme is integrated into the controllers to cope with the uncertainty and 2) a novel cost function, which is not in quadric form, is proposed so that the total cost in the design procedure is reduced. It is proved that the optimal control signals and the tracking errors are uniformly ultimately bounded even when the uncertainty exists. Finally, a numerical simulation is developed to show the effectiveness of the present approach.

Adaptive control of a quadrotor aerial vehicle with input constraints and uncertain parameters

Science.gov (United States)

Tran, Trong-Toan; Ge, Shuzhi Sam; He, Wei

2018-05-01

In this paper, we address the problem of adaptive bounded control for the trajectory tracking of a Quadrotor Aerial Vehicle (QAV) while the input saturations and uncertain parameters with the known bounds are simultaneously taken into account. First, to deal with the underactuated property of the QAV model, we decouple and construct the QAV model as a cascaded structure which consists of two fully actuated subsystems. Second, to handle the input constraints and uncertain parameters, we use a combination of the smooth saturation function and smooth projection operator in the control design. Third, to ensure the stability of the overall system of the QAV, we develop the technique for the cascaded system in the presence of both the input constraints and uncertain parameters. Finally, the region of stability of the closed-loop system is constructed explicitly, and our design ensures the asymptotic convergence of the tracking errors to the origin. The simulation results are provided to illustrate the effectiveness of the proposed method.

Feasibility Study On Missile Launch Detection And Trajectory Tracking

Science.gov (United States)

2016-09-01

Feature (SURF) detection, and Kalman filtering are frequently used for object tracking. These methods have been applied frequently on video records...missile by processing the thermal imagery from the thermal-imaging sensor, which captures the temperature gradient of the surroundings within its field of...view. As the missile’s propulsion motor emits gases at high temperature to generate the thrust required for its flight, the heat 2 signature of

Distributed formation tracking using local coordinate systems

DEFF Research Database (Denmark)

Yang, Qingkai; Cao, Ming; Garcia de Marina, Hector

2018-01-01

This paper studies the formation tracking problem for multi-agent systems, for which a distributed estimator–controller scheme is designed relying only on the agents’ local coordinate systems such that the centroid of the controlled formation tracks a given trajectory. By introducing a gradient...... descent term into the estimator, the explicit knowledge of the bound of the agents’ speed is not necessary in contrast to existing works, and each agent is able to compute the centroid of the whole formation in finite time. Then, based on the centroid estimation, a distributed control algorithm...

Elastic tracking versus neural network tracking for very high multiplicity problems

International Nuclear Information System (INIS)

Harlander, M.; Gyulassy, M.

1991-04-01

A new Elastic Tracking (ET) algorithm is proposed for finding tracks in very high multiplicity and noisy environments. It is based on a dynamical reinterpretation and generalization of the Radon transform and is related to elastic net algorithms for geometrical optimization. ET performs an adaptive nonlinear fit to noisy data with a variable number of tracks. Its numerics is more efficient than that of the traditional Radon or Hough transform method because it avoids binning of phase space and the costly search for valid minima. Spurious local minima are avoided in ET by introducing a time-dependent effective potential. The method is shown to be very robust to noise and measurement error and extends tracking capabilities to much higher track densities than possible via local road finding or even the novel Denby-Peterson neural network tracking algorithms. 12 refs., 2 figs

Target Tracking of a Linear Time Invariant System under Irregular Sampling

Directory of Open Access Journals (Sweden)

Jin Xue-Bo

2012-11-01

Full Text Available Due to event-triggered sampling in a system, or maybe with the aim of reducing data storage, tracking many applications will encounter irregular sampling time. By calculating the matrix exponential using an inverse Laplace transform, this paper transforms the irregular sampling tracking problem to the problem of tracking with time-varying parameters of a system. Using the common Kalman filter, the developed method is used to track a target for the simulated trajectory and video tracking. The results of simulation experiments have shown that it can obtain good estimation performance even at a very high irregular rate of measurement sampling time.

Automated positioning dual-axis solar tracking system with precision elevation and azimuth angle control

International Nuclear Information System (INIS)

Sidek, M.H.M.; Azis, N.; Hasan, W.Z.W.; Ab Kadir, M.Z.A.; Shafie, S.; Radzi, M.A.M.

2017-01-01

This paper presents a study on an automated positioning open-loop dual-axis solar tracking system. The solar tracker was designed and fabricated using standard cylindrical aluminium hollow and Polyuthrene (PE). The control system of the solar tracker was governed by Micro Controller Unit (MCU) with auxiliary devices which includes encoder and Global Positioning System (GPS). The sun path trajectory algorithm utilizing the astronomical equation and GPS information was also embedded in the system. The power generation performance of the dual-axis solar tracking system was compared with the fixed-tilted Photovoltaic (PV) system. It is found that the solar tracker is able to position itself automatically based on sun path trajectory algorithm with an accuracy of ±0.5°. The embedded Proportional Integral Derivative (PID) positioning system improves the tracking of elevation and azimuth angles with minimum energy consumption. It is reveals that the proposed solar tracker is able generate 26.9% and 12.8% higher power than fixed-tilted PV system on a clear and heavy overcast conditions respectively. Overall, the open-loop dual-axis solar tracker can be deployed automatically at any location on the earth with minimal configurations and is suitable for mobile solar tracking system. - Highlights: • Self-positioning dual-axis solar tracking system. • Precise control of elevation and azimuth angle. • Sun path trajectory based on astronomical equation and GPS. • Can achieve up to 26.9% higher power than fixed-tilted PV system under clear weather condition.

Automated tracking of animal posture and movement during exploration and sensory orientation behaviors.

Directory of Open Access Journals (Sweden)

Alex Gomez-Marin

Full Text Available The nervous functions of an organism are primarily reflected in the behavior it is capable of. Measuring behavior quantitatively, at high-resolution and in an automated fashion provides valuable information about the underlying neural circuit computation. Accordingly, computer-vision applications for animal tracking are becoming a key complementary toolkit to genetic, molecular and electrophysiological characterization in systems neuroscience.We present Sensory Orientation Software (SOS to measure behavior and infer sensory experience correlates. SOS is a simple and versatile system to track body posture and motion of single animals in two-dimensional environments. In the presence of a sensory landscape, tracking the trajectory of the animal's sensors and its postural evolution provides a quantitative framework to study sensorimotor integration. To illustrate the utility of SOS, we examine the orientation behavior of fruit fly larvae in response to odor, temperature and light gradients. We show that SOS is suitable to carry out high-resolution behavioral tracking for a wide range of organisms including flatworms, fishes and mice.Our work contributes to the growing repertoire of behavioral analysis tools for collecting rich and fine-grained data to draw and test hypothesis about the functioning of the nervous system. By providing open-access to our code and documenting the software design, we aim to encourage the adaptation of SOS by a wide community of non-specialists to their particular model organism and questions of interest.

Adaptive multiparameter control: application to a Rapid Thermal Processing process; Commande Adaptative Multivariable: Application a un Procede de Traitement Thermique Rapide

Energy Technology Data Exchange (ETDEWEB)

Morales Mago, S J

1995-12-20

In this work the problem of temperature uniformity control in rapid thermal processing is addressed by means of multivariable adaptive control. Rapid Thermal Processing (RTP) is a set of techniques proposed for semiconductor fabrication processes such as annealing, oxidation, chemical vapour deposition and others. The product quality depends on two mains issues: precise trajectory following and spatial temperature uniformity. RTP is a fabrication technique that requires a sophisticated real-time multivariable control system to achieve acceptable results. Modelling of the thermal behaviour of the process leads to very complex mathematical models. These are the reasons why adaptive control techniques are chosen. A multivariable linear discrete time model of the highly non-linear process is identified on-line, using an identification scheme which includes supervisory actions. This identified model, combined with a multivariable predictive control law allows to prevent the controller from systems variations. The control laws are obtained by minimization of a quadratic cost function or by pole placement. In some of these control laws, a partial state reference model was included. This reference model allows to incorporate an appropriate tracking capability into the control law. Experimental results of the application of the involved multivariable adaptive control laws on a RTP system are presented. (author) refs

ALICE HLT high speed tracking on GPU

CERN Document Server

Gorbunov, Sergey; Aamodt, Kenneth; Alt, Torsten; Appelshauser, Harald; Arend, Andreas; Bach, Matthias; Becker, Bruce; Bottger, Stefan; Breitner, Timo; Busching, Henner; Chattopadhyay, Sukalyan; Cleymans, Jean; Cicalo, Corrado; Das, Indranil; Djuvsland, Oystein; Engel, Heiko; Erdal, Hege Austrheim; Fearick, Roger; Haaland, Oystein Senneset; Hille, Per Thomas; Kalcher, Sebastian; Kanaki, Kalliopi; Kebschull, Udo Wolfgang; Kisel, Ivan; Kretz, Matthias; Lara, Camillo; Lindal, Sven; Lindenstruth, Volker; Masoodi, Arshad Ahmad; Ovrebekk, Gaute; Panse, Ralf; Peschek, Jorg; Ploskon, Mateusz; Pocheptsov, Timur; Ram, Dinesh; Rascanu, Theodor; Richter, Matthias; Rohrich, Dieter; Ronchetti, Federico; Skaali, Bernhard; Smorholm, Olav; Stokkevag, Camilla; Steinbeck, Timm Morten; Szostak, Artur; Thader, Jochen; Tveter, Trine; Ullaland, Kjetil; Vilakazi, Zeblon; Weis, Robert; Yin, Zhong-Bao; Zelnicek, Pierre

2011-01-01

The on-line event reconstruction in ALICE is performed by the High Level Trigger, which should process up to 2000 events per second in proton-proton collisions and up to 300 central events per second in heavy-ion collisions, corresponding to an inp ut data stream of 30 GB/s. In order to fulfill the time requirements, a fast on-line tracker has been developed. The algorithm combines a Cellular Automaton method being used for a fast pattern recognition and the Kalman Filter method for fitting of found trajectories and for the final track selection. The tracker was adapted to run on Graphics Processing Units (GPU) using the NVIDIA Compute Unified Device Architecture (CUDA) framework. The implementation of the algorithm had to be adjusted at many points to allow for an efficient usage of the graphics cards. In particular, achieving a good overall workload for many processor cores, efficient transfer to and from the GPU, as well as optimized utilization of the different memories the GPU offers turned out to be cri...

Tracking Persons-of-Interest via Unsupervised Representation Adaptation

OpenAIRE

Zhang, Shun; Huang, Jia-Bin; Lim, Jongwoo; Gong, Yihong; Wang, Jinjun; Ahuja, Narendra; Yang, Ming-Hsuan

2017-01-01

Multi-face tracking in unconstrained videos is a challenging problem as faces of one person often appear drastically different in multiple shots due to significant variations in scale, pose, expression, illumination, and make-up. Existing multi-target tracking methods often use low-level features which are not sufficiently discriminative for identifying faces with such large appearance variations. In this paper, we tackle this problem by learning discriminative, video-specific face representa...

Wind Turbine Pitch Control and Load Mitigation Using an L1 Adaptive Approach

Directory of Open Access Journals (Sweden)

Danyong Li

2014-01-01

Full Text Available We present an application of L1 adaptive output feedback control design to wind turbine collective pitch control and load mitigation. Our main objective is the design of an L1 output feedback controller without wind speed estimation, ensuring that the generator speed tracks the reference trajectory with robustness to uncertain parameters and time-varying disturbances (mainly the uniform wind disturbance across the wind turbine rotor. The wind turbine model CART (controls advanced research turbine developed by the national renewable energy laboratory (NREL is used to validate the performance of the proposed L1 adaptive controller using the FAST (fatigue, aerodynamics, structures, and turbulence code. A comparative study is also conducted between the proposed controller and the most popular methods in practice: gain scheduling PI (GSPI controls and disturbance accommodating control (DAC methods. The results show better performance of L1 output feedback controller over the other two methods. Moreover, based on the FAST software and LQR analysis in the reference model selection of L1 adaptive controller, tradeoff can be achieved between control performance and loads mitigation.

A Dual Track Treadmill in a Virtual Reality Environment as a Countermeasure for Neurovestibular Adaptations in Microgravity

Science.gov (United States)

DAndrea, Susan E.; Kahelin, Michael W.; Horowitz, Jay G.; OConnor, Philip A.

2004-01-01

While the neurovestibular system is capable of adapting to altered environments such as microgravity, the adaptive state achieved in space in inadequate for 1G. This leads to gait and postural instabilities when returning to a gravity environment and may create serious problems in future missions to Mars. New methods are needed to improve the understanding of the adaptive capabilities of the human neurovestibular system and to develop more effective countermeasures. The concept behind the current study is that by challenging the neurovestibular system while walking or running, a treadmill can help to readjust the relationship between the visual, vestibular and proprioceptive signals that are altered in a microgravity environment. As a countermeasure, this device could also benefit the musculoskeletal and cardiovascular systems and at the same time decrease the overall time spent exercising. The overall goal of this research is to design, develop, build and test a dual track treadmill, which utilizes virtual reality,

Calculation of the electron trajectory for 200 kV self-shielded electron accelerator

International Nuclear Information System (INIS)

Wang Shuiqing

2000-01-01

In order to calculate the electron trajectory of 200 kV self-shielded electron accelerator, the electric field is calculated with a TRAJ program. In this program, following electron track mash points one by one, the electron beam trajectories are calculated. Knowing the effect of grid voltage on electron optics and gaining grid voltage focusing effect in the various energy grades, the authors have gained scientific basis for adjusting grid voltage, and also accumulated a wealth of experience for designing self-shielded electron accelerator or electron curtain in future

Advanced Alignment of the ATLAS Tracking System

CERN Document Server

Pedraza Lopez, S; The ATLAS collaboration

2012-01-01

In order to reconstruct trajectories of charged particles, ATLAS is equipped with a tracking system built using different technologies embedded in a 2T solenoidal magnetic field. ATLAS physics goals require high resolution, unbiased measurement of all charged particle kinematic parameters in order to assure accurate invariant mass reconstruction and interaction and decay vertex finding. These critically depend on the systematic effects related to the alignment of the tracking system. In order to eliminate malicious systematic deformations, various advanced tools and techniques have been put in place. These include information from known mass resonances, energy of electrons and positrons measured by the electromagnetic calorimeters, etc. Despite being stable under normal running conditions, ATLAS tracking system responses to sudden environ-mental changes (temperature, magnetic field) by small collective deformations. These have to be identified and corrected in order to assure uniform, highest quality tracking...

Fast Compressive Tracking.

Science.gov (United States)

Zhang, Kaihua; Zhang, Lei; Yang, Ming-Hsuan

2014-10-01

It is a challenging task to develop effective and efficient appearance models for robust object tracking due to factors such as pose variation, illumination change, occlusion, and motion blur. Existing online tracking algorithms often update models with samples from observations in recent frames. Despite much success has been demonstrated, numerous issues remain to be addressed. First, while these adaptive appearance models are data-dependent, there does not exist sufficient amount of data for online algorithms to learn at the outset. Second, online tracking algorithms often encounter the drift problems. As a result of self-taught learning, misaligned samples are likely to be added and degrade the appearance models. In this paper, we propose a simple yet effective and efficient tracking algorithm with an appearance model based on features extracted from a multiscale image feature space with data-independent basis. The proposed appearance model employs non-adaptive random projections that preserve the structure of the image feature space of objects. A very sparse measurement matrix is constructed to efficiently extract the features for the appearance model. We compress sample images of the foreground target and the background using the same sparse measurement matrix. The tracking task is formulated as a binary classification via a naive Bayes classifier with online update in the compressed domain. A coarse-to-fine search strategy is adopted to further reduce the computational complexity in the detection procedure. The proposed compressive tracking algorithm runs in real-time and performs favorably against state-of-the-art methods on challenging sequences in terms of efficiency, accuracy and robustness.

Hopfield neural network in HEP track reconstruction

International Nuclear Information System (INIS)

Muresan, R.; Pentia, M.

1997-01-01

In experimental particle physics, pattern recognition problems, specifically for neural network methods, occur frequently in track finding or feature extraction. Track finding is a combinatorial optimization problem. Given a set of points in Euclidean space, one tries the reconstruction of particle trajectories, subject to smoothness constraints.The basic ingredients in a neural network are the N binary neurons and the synaptic strengths connecting them. In our case the neurons are the segments connecting all possible point pairs.The dynamics of the neural network is given by a local updating rule wich evaluates for each neuron the sign of the 'upstream activity'. An updating rule in the form of sigmoid function is given. The synaptic strengths are defined in terms of angle between the segments and the lengths of the segments implied in the track reconstruction. An algorithm based on Hopfield neural network has been developed and tested on the track coordinates measured by silicon microstrip tracking system

Tracking down quirks at the Large Hadron Collider

Science.gov (United States)

Knapen, Simon; Lou, Hou Keong; Papucci, Michele; Setford, Jack

2017-12-01

Nonhelical tracks are the smoking gun signature of charged and/or colored quirks, which are pairs of particles bound by a new, long-range confining force. We propose a method to efficiently search for these nonhelical tracks at the LHC, without the need to fit their trajectories. We show that the hits corresponding to quirky trajectories can be selected efficiently by searching for coplanar hits in the inner layers of the ATLAS and CMS trackers, even in the presence of on average 50 pile-up vertices. We further argue that backgrounds from photon conversions and unassociated pile-up hits can be removed almost entirely, while maintaining a signal reconstruction efficiency as high as ˜70 % . With the 300 fb-1 dataset, this implies a discovery potential for string tension between 100 eV and 30 keV, and colored (electroweak charged) quirks as heavy as 1600 (650) GeV may be discovered.

Orion Exploration Flight Test 1 (EFT-1) Best Estimated Trajectory Development

Science.gov (United States)

Holt, Greg N.; Brown, Aaron

2016-01-01

The Orion Exploration Flight Test 1 (EFT-1) mission successfully flew on Dec 5, 2014 atop a Delta IV Heavy launch vehicle. The goal of Orions maiden flight was to stress the system by placing an uncrewed vehicle on a high-energy trajectory replicating conditions similar to those that would be experienced when returning from an asteroid or a lunar mission. The Orion navigation team combined all trajectory data from the mission into a Best Estimated Trajectory (BET) product. There were significant challenges in data reconstruction and many lessons were learned for future missions. The team used an estimation filter incorporating radar tracking, onboard sensors (Global Positioning System and Inertial Measurement Unit), and day-of-flight weather balloons to evaluate the true trajectory flown by Orion. Data was published for the entire Orion EFT-1 flight, plus objects jettisoned during entry such as the Forward Bay Cover. The BET customers include approximately 20 disciplines within Orion who will use the information for evaluating vehicle performance and influencing future design decisions.

Critical Neural Substrates for Correcting Unexpected Trajectory Errors and Learning from Them

Science.gov (United States)

Mutha, Pratik K.; Sainburg, Robert L.; Haaland, Kathleen Y.

2011-01-01

Our proficiency at any skill is critically dependent on the ability to monitor our performance, correct errors and adapt subsequent movements so that errors are avoided in the future. In this study, we aimed to dissociate the neural substrates critical for correcting unexpected trajectory errors and learning to adapt future movements based on…

Adaptive proportional–integral–derivative tuning sliding mode control for a shape memory alloy actuator

International Nuclear Information System (INIS)

Tai, Nguyen Trong; Ahn, Kyoung Kwan

2011-01-01

In this paper, a novel adaptive sliding mode control with a proportional–integral–derivative (PID) tuning method is proposed to control a shape memory alloy (SMA) actuator. The goal of the controller is to achieve system robustness against the SMA hysteresis phenomenon, system uncertainties and external disturbances. In the controller, the PID controller is employed to approximate the sliding mode equivalent control along the direction that makes the sliding mode asymptotically stable. Due to the system nonlinearity, the PID control gain parameters are systematically computed online according to the adaptive law. To improve the transient performance, the initial PID gain parameters are optimized by the particle swarm optimization (PSO) method. Simulation and experimental results demonstrate that the controller performs well for the desired trajectory tracking, and the hysteresis phenomenon is compensated for completely. The control results are also compared with the optimized PID controller

Task driven optimal leg trajectories in insect-scale legged microrobots

Science.gov (United States)

Doshi, Neel; Goldberg, Benjamin; Jayaram, Kaushik; Wood, Robert

Origami inspired layered manufacturing techniques and 3D-printing have enabled the development of highly articulated legged robots at the insect-scale, including the 1.43g Harvard Ambulatory MicroRobot (HAMR). Research on these platforms has expanded its focus from manufacturing aspects to include design optimization and control for application-driven tasks. Consequently, the choice of gait selection, body morphology, leg trajectory, foot design, etc. have become areas of active research. HAMR has two controlled degrees-of-freedom per leg, making it an ideal candidate for exploring leg trajectory. We will discuss our work towards optimizing HAMR's leg trajectories for two different tasks: climbing using electroadhesives and level ground running (5-10 BL/s). These tasks demonstrate the ability of single platform to adapt to vastly different locomotive scenarios: quasi-static climbing with controlled ground contact, and dynamic running with un-controlled ground contact. We will utilize trajectory optimization methods informed by existing models and experimental studies to determine leg trajectories for each task. We also plan to discuss how task specifications and choice of objective function have contributed to the shape of these optimal leg trajectories.

Adaptive nonlinear control for a research reactor

International Nuclear Information System (INIS)

Benitez R, J.S.

1994-01-01

Linearization by feedback of states is based on the idea of transform the nonlinear dynamic equation of a system in a linear form. This linear behavior can be achieve well in a complete way (input state) or in partial way (input output). This can be applied to systems of single or multiple inputs, and can be used to solve problems of stabilization and tracking of references trajectories. Comparing this method with conventional ones, linearization by feedback of states is exact in certain region of the space of state, instead of linear approximations of the equations in a certain point of the operation. In the presence of parametric uncertainties in the model of the system, the introduction of adaptive schemes provide a type toughness to the control system by nonlinear feedback, which gives as result the eventual cancellation of the nonlinear terms in the dynamic relationship between the output and the input of the auxiliary control. In the same way, it has been presented the design of a nonlinearizing control for the non lineal model of a TRIGA Mark III type reactor, with the aim of tracking a predetermined power profile. The asymptotic tracking of such profile is, at the present moment, in the stage of verification by computerized simulation the relative easiness in the design of auxiliary variable of control, as well as the decoupling action of the output variable, make very attractive the utilization of the method herein presented. (Author)

TPC track distortions III: fiat lux

CERN Document Server

Boyko, I; Dydak, F; Elagin, A; Gostkin, M; Guskov, A; Koreshev, V; Nefedov, Y; Nikolaev, K; Veenhof, R; Wotschack, J; Zhemchugov, A

2005-01-01

We present a comprehensive overview and final summary of all four types of static track distortions seen in the HARP TPC, in terms of physical origins, mathematical modelling, and correction algorithms. 'Static'™ distortions are defined as not depending on the event time within the 400 ms long accelerator spill. Calculated static distortions are compared with measurements from cosmic-muon tracks. We characterize track distortions by the r phi residuals of cluster positions with respect to the transverse projection of a helical trajectory constrained by hits in the RPC overlap regions. This method provides a fixed TPC-external reference system (by contrast to the co-moving coordinate system associated with a fit) which solely permits to identify individually, and measure quantitatively, the static TPC track distortions arising from (i) the inhomogeneity of the solenoidal magnetic field, (ii) the inhomogeneity of the electric field from the high-voltage mismatch between the inner and outer TPC field cages, (...

Artistic Visualization of Trajectory Data Using Cloud Model

Science.gov (United States)

Wu, T.; Zhou, Y.; Zhang, L.

2017-09-01

Rapid advance of location acquisition technologies boosts the generation of trajectory data, which track the traces of moving objects. A trajectory is typically represented by a sequence of timestamped geographical locations. Data visualization is an efficient means to represent distributions and structures of datasets and reveal hidden patterns in the data. In this paper, we explore a cloud model-based method for the generation of stylized renderings of trajectory data. The artistic visualizations of the proposed method do not have the goal to allow for data mining tasks or others but instead show the aesthetic effect of the traces of moving objects in a distorted manner. The techniques used to create the images of traces of moving objects include the uncertain line using extended cloud model, stroke-based rendering of geolocation in varying styles, and stylistic shading with aesthetic effects for print or electronic displays, as well as various parameters to be further personalized. The influence of different parameters on the aesthetic qualities of various painted images is investigated, including step size, types of strokes, colour modes, and quantitative comparisons using four aesthetic measures are also involved into the experiment. The experimental results suggest that the proposed method is with advantages of uncertainty, simplicity and effectiveness, and it would inspire professional graphic designers and amateur users who may be interested in playful and creative exploration of artistic visualization of trajectory data.

Video-based Chinese Input System via Fingertip Tracking

Directory of Open Access Journals (Sweden)

Chih-Chang Yu

2012-10-01

Full Text Available In this paper, we propose a system to detect and track fingertips online and recognize Mandarin Phonetic Symbol (MPS for user-friendly Chinese input purposes. Using fingertips and cameras to replace pens and touch panels as input devices could reduce the cost and improve the ease-of-use and comfort of computer-human interface. In the proposed framework, particle filters with enhanced appearance models are applied for robust fingertip tracking. Afterwards, MPS combination recognition is performed on the tracked fingertip trajectories using Hidden Markov Models. In the proposed system, the fingertips of the users could be robustly tracked. Also, the challenges of entering, leaving and virtual strokes caused by video-based fingertip input can be overcome. Experimental results have shown the feasibility and effectiveness of the proposed work.

Adaptive block online learning target tracking based on super pixel segmentation

Science.gov (United States)

Cheng, Yue; Li, Jianzeng

2018-04-01

Video target tracking technology under the unremitting exploration of predecessors has made big progress, but there are still lots of problems not solved. This paper proposed a new algorithm of target tracking based on image segmentation technology. Firstly we divide the selected region using simple linear iterative clustering (SLIC) algorithm, after that, we block the area with the improved density-based spatial clustering of applications with noise (DBSCAN) clustering algorithm. Each sub-block independently trained classifier and tracked, then the algorithm ignore the failed tracking sub-block while reintegrate the rest of the sub-blocks into tracking box to complete the target tracking. The experimental results show that our algorithm can work effectively under occlusion interference, rotation change, scale change and many other problems in target tracking compared with the current mainstream algorithms.

TrackML : The High Energy Physics Tracking Challenge

CERN Multimedia

CERN. Geneva

2018-01-01

We organize on the Kaggle platform a  data science competition to stimulate both the ML and HEP communities to renew core tracking algorithms in preparation of the next generation of particle detectors at the LHC.    In a nutshell : one event has 100.000 3D points  ; how to associate the points onto 10.000 unknown approximately helicoidal trajectories ? avoiding combinatorial explosion ? you have a few seconds. But we do give you 100.000 events to train on. We ran ttbar+200 minimum bias event into ACTS a simplified (yet accurate) simulation of a generic LHC silicon detectors, and wrote out ...

Sinusoidal visuomotor tracking: intermittent servo-control or coupled oscillations?

Science.gov (United States)

Russell, D M; Sternad, D

2001-12-01

In visuomotor tasks that involve accuracy demands, small directional changes in the trajectories have been taken as evidence of feedback-based error corrections. In the present study variability, or intermittency, in visuomanual tracking of sinusoidal targets was investigated. Two lines of analyses were pursued: First, the hypothesis that humans fundamentally act as intermittent servo-controllers was re-examined, probing the question of whether discontinuities in the movement trajectory directly imply intermittent control. Second, an alternative hypothesis was evaluated: that rhythmic tracking movements are generated by entrainment between the oscillations of the target and the actor, such that intermittency expresses the degree of stability. In 2 experiments, participants (N = 6 in each experiment) swung 1 of 2 different hand-held pendulums, tracking a rhythmic target that oscillated at different frequencies with a constant amplitude. In 1 line of analyses, the authors tested the intermittency hypothesis by using the typical kinematic error measures and spectral analysis. In a 2nd line, they examined relative phase and its variability, following analyses of rhythmic interlimb coordination. The results showed that visually guided corrective processes play a role, especially for slow movements. Intermittency, assessed as frequency and power components of the movement trajectory, was found to change as a function of both target frequency and the manipulandum's inertia. Support for entrainment was found in conditions in which task frequency was identical to or higher than the effector's eigenfrequency. The results suggest that it is the symmetry between task and effector that determines which behavioral regime is dominant.

Direct adaptive control of a PUMA 560 industrial robot

Science.gov (United States)

Seraji, Homayoun; Lee, Thomas; Delpech, Michel

1989-01-01

The implementation and experimental validation of a new direct adaptive control scheme on a PUMA 560 industrial robot is described. The testbed facility consists of a Unimation PUMA 560 six-jointed robot and controller, and a DEC MicroVAX II computer which hosts the Robot Control C Library software. The control algorithm is implemented on the MicroVAX which acts as a digital controller for the PUMA robot, and the Unimation controller is effectively bypassed and used merely as an I/O device to interface the MicroVAX to the joint motors. The control algorithm for each robot joint consists of an auxiliary signal generated by a constant-gain Proportional plus Integral plus Derivative (PID) controller, and an adaptive position-velocity (PD) feedback controller with adjustable gains. The adaptive independent joint controllers compensate for the inter-joint couplings and achieve accurate trajectory tracking without the need for the complex dynamic model and parameter values of the robot. Extensive experimental results on PUMA joint control are presented to confirm the feasibility of the proposed scheme, in spite of strong interactions between joint motions. Experimental results validate the capabilities of the proposed control scheme. The control scheme is extremely simple and computationally very fast for concurrent processing with high sampling rates.

Adaptive fuzzy control of a class of nonaffine nonlinear system with input saturation based on passivity theorem.

Science.gov (United States)

Molavi, Ali; Jalali, Aliakbar; Ghasemi Naraghi, Mahdi

2017-07-01

In this paper, based on the passivity theorem, an adaptive fuzzy controller is designed for a class of unknown nonaffine nonlinear systems with arbitrary relative degree and saturation input nonlinearity to track the desired trajectory. The system equations are in normal form and its unforced dynamic may be unstable. As relative degree one is a structural obstacle in system passivation approach, in this paper, backstepping method is used to circumvent this obstacle and passivate the system step by step. Because of the existence of uncertainty and disturbance in the system, exact passivation and reference tracking cannot be tackled, so the approximate passivation or passivation with respect to a set is obtained to hold the tracking error in a neighborhood around zero. Furthermore, in order to overcome the non-smoothness of the saturation input nonlinearity, a parametric smooth nonlinear function with arbitrary approximation error is used to approximate the input saturation. Finally, the simulation results for the theoretical and practical examples are given to validate the proposed controller. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Track-before-detect procedures for detection of extended object

Science.gov (United States)

Fan, Ling; Zhang, Xiaoling; Shi, Jun

2011-12-01

In this article, we present a particle filter (PF)-based track-before-detect (PF TBD) procedure for detection of extended objects whose shape is modeled by an ellipse. By incorporating of an existence variable and the target shape parameters into the state vector, the proposed algorithm performs joint estimation of the target presence/absence, trajectory and shape parameters under unknown nuisance parameters (target power and noise variance). Simulation results show that the proposed algorithm has good detection and tracking capabilities for extended objects.

Fast algorithm of track reconstruction for the Delphy TPC

International Nuclear Information System (INIS)

Maillard, J.

1984-01-01

We describe a simple geometrical method (polar inversion) to reconstruct tracks. When the magnetic field is constant in magnitude and direction. This method uses geometrical properties of the trajectories. In the case of the DELPHI apparatus, the track reconstruction is done using TPC informations. After explaining the algorithm, we give results on ''GEANT'' simulated events using the ''Lund'' generator. Today we get a computer time of the order of 1.2 milliseconds on a CDC 7600 and an efficiency of 98% [fr

Making Sense of Trajectory Data in Indoor Spaces

DEFF Research Database (Denmark)

Prentow, Thor Siiger; Thom, Andreas; Blunck, Henrik

2015-01-01

The increasing prevalence of positioning and tracking systems has helped simplify tracking large amounts of, e.g., people moving through buildings or cars traveling on roads, over long periods of time. However, technical limitations of positioning algorithms and traditional sensing infrastructures......-specific analysis tools. Additionally, it allows to predict the locally occurring expected positioning error biases. This in turn allows improved positioning, e.g., for real-time navigation assistance scenarios. We evaluate the proposed methods using trajectory data from employees at a large hospital complex...... which route was taken in a particular travel instance or whether two travel instances followed the same route. In this paper, we present a bootstrapping approach and several algorithms to mitigate error biases and related phenomena, focusing on indoor scenarios. In particular, we are able to estimate...

Approximate optimal tracking control for near-surface AUVs with wave disturbances

Science.gov (United States)

Yang, Qing; Su, Hao; Tang, Gongyou

2016-10-01

This paper considers the optimal trajectory tracking control problem for near-surface autonomous underwater vehicles (AUVs) in the presence of wave disturbances. An approximate optimal tracking control (AOTC) approach is proposed. Firstly, a six-degrees-of-freedom (six-DOF) AUV model with its body-fixed coordinate system is decoupled and simplified and then a nonlinear control model of AUVs in the vertical plane is given. Also, an exosystem model of wave disturbances is constructed based on Hirom approximation formula. Secondly, the time-parameterized desired trajectory which is tracked by the AUV's system is represented by the exosystem. Then, the coupled two-point boundary value (TPBV) problem of optimal tracking control for AUVs is derived from the theory of quadratic optimal control. By using a recently developed successive approximation approach to construct sequences, the coupled TPBV problem is transformed into a problem of solving two decoupled linear differential sequences of state vectors and adjoint vectors. By iteratively solving the two equation sequences, the AOTC law is obtained, which consists of a nonlinear optimal feedback item, an expected output tracking item, a feedforward disturbances rejection item, and a nonlinear compensatory term. Furthermore, a wave disturbances observer model is designed in order to solve the physically realizable problem. Simulation is carried out by using the Remote Environmental Unit (REMUS) AUV model to demonstrate the effectiveness of the proposed algorithm.

Positron Emission Tomography Particle tracking using cluster analysis

International Nuclear Information System (INIS)

Gundogdu, O.

2004-01-01

Positron Emission Particle Tracking was successfully used in a wide range of industrial applications. This technique primarily uses a single positron emitting tracer particle. However, using multiple particles would provide more comparative information about the physical processes taking place in a system such as mixing or fluidised beds. In this paper, a unique method that enables us to track more than one particle is presented. This method is based on the midpoint of the closest distance between two trajectories or coincidence vectors. The technique presented in this paper employs a clustering method

Positron Emission Tomography Particle tracking using cluster analysis

Energy Technology Data Exchange (ETDEWEB)

Gundogdu, O. [University of Birmingham, School of Physics and Astronomy, Birmingham, B15 2TT (United Kingdom)]. E-mail: o.gundogdu@surrey.ac.uk

2004-12-01

Positron Emission Particle Tracking was successfully used in a wide range of industrial applications. This technique primarily uses a single positron emitting tracer particle. However, using multiple particles would provide more comparative information about the physical processes taking place in a system such as mixing or fluidised beds. In this paper, a unique method that enables us to track more than one particle is presented. This method is based on the midpoint of the closest distance between two trajectories or coincidence vectors. The technique presented in this paper employs a clustering method.

Kinect-Based Moving Human Tracking System with Obstacle Avoidance

Directory of Open Access Journals (Sweden)

Abdel Mehsen Ahmad

2017-04-01

Full Text Available This paper is an extension of work originally presented and published in IEEE International Multidisciplinary Conference on Engineering Technology (IMCET. This work presents a design and implementation of a moving human tracking system with obstacle avoidance. The system scans the environment by using Kinect, a 3D sensor, and tracks the center of mass of a specific user by using Processing, an open source computer programming language. An Arduino microcontroller is used to drive motors enabling it to move towards the tracked user and avoid obstacles hampering the trajectory. The implemented system is tested under different lighting conditions and the performance is analyzed using several generated depth images.

Determination of extra trajectory parameters of projectile layout motion

Science.gov (United States)

Ishchenko, A.; Burkin, V.; Faraponov, V.; Korolkov, L.; Maslov, E.; Diachkovskiy, A.; Chupashev, A.; Zykova, A.

2017-11-01

The paper presents a brief description of the experimental track developed and implemented on the base of the RIAMM TSU for external trajectory investigations on determining the main aeroballistic parameters of various shapes projectiles, in the wide velocity range. There is comparison between the experimentally obtained dependence of the fin-stabilized projectile mock-up aerodynamic drag coefficient on the Mach number with the 1958 aerodynamic drag law and aerodynamic tests of the same mock-up

Adaptive terminal sliding mode control for hypersonic flight vehicles with strictly lower convex function based nonlinear disturbance observer.

Science.gov (United States)

Wu, Yun-Jie; Zuo, Jing-Xing; Sun, Liang-Hua

2017-11-01

In this paper, the altitude and velocity tracking control of a generic hypersonic flight vehicle (HFV) is considered. A novel adaptive terminal sliding mode controller (ATSMC) with strictly lower convex function based nonlinear disturbance observer (SDOB) is proposed for the longitudinal dynamics of HFV in presence of both parametric uncertainties and external disturbances. First, for the sake of enhancing the anti-interference capability, SDOB is presented to estimate and compensate the equivalent disturbances by introducing a strictly lower convex function. Next, the SDOB based ATSMC (SDOB-ATSMC) is proposed to guarantee the system outputs track the reference trajectory. Then, stability of the proposed control scheme is analyzed by the Lyapunov function method. Compared with other HFV control approaches, key novelties of SDOB-ATSMC are that a novel SDOB is proposed and drawn into the (virtual) control laws to compensate the disturbances and that several adaptive laws are used to deal with the differential explosion problem. Finally, it is illustrated by the simulation results that the new method exhibits an excellent robustness and a better disturbance rejection performance than the convention approach. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Application of vertex and mass constraints in track-based alignment

International Nuclear Information System (INIS)

Amoraal, J.; Blouw, J.; Blusk, S.; Borghi, S.; Cattaneo, M.; Chiapolini, N.; Conti, G.; Deissenroth, M.; Dupertuis, F.; Eijk, R. van der; Fave, V.; Gersabeck, M.; Hicheur, A.; Hulsbergen, W.; Hutchcroft, D.; Kozlinskiy, A.; Lambert, R.W.

2013-01-01

The software alignment of planar tracking detectors using samples of charged particle trajectories may lead to global detector distortions that affect vertex and momentum resolution. We present an alignment procedure that constrains such distortions by making use of samples of decay vertices reconstructed from two or more trajectories and putting constraints on their invariant mass. We illustrate the method by using a sample of invariant-mass constrained vertices from D 0 →K − π + decays to remove a curvature bias in the LHCb spectrometer

Using dual-energy x-ray imaging to enhance automated lung tumor tracking during real-time adaptive radiotherapy

Energy Technology Data Exchange (ETDEWEB)

Menten, Martin J., E-mail: martin.menten@icr.ac.uk; Fast, Martin F.; Nill, Simeon; Oelfke, Uwe, E-mail: uwe.oelfke@icr.ac.uk [Joint Department of Physics at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London SM2 5NG (United Kingdom)

2015-12-15

Purpose: Real-time, markerless localization of lung tumors with kV imaging is often inhibited by ribs obscuring the tumor and poor soft-tissue contrast. This study investigates the use of dual-energy imaging, which can generate radiographs with reduced bone visibility, to enhance automated lung tumor tracking for real-time adaptive radiotherapy. Methods: kV images of an anthropomorphic breathing chest phantom were experimentally acquired and radiographs of actual lung cancer patients were Monte-Carlo-simulated at three imaging settings: low-energy (70 kVp, 1.5 mAs), high-energy (140 kVp, 2.5 mAs, 1 mm additional tin filtration), and clinical (120 kVp, 0.25 mAs). Regular dual-energy images were calculated by weighted logarithmic subtraction of high- and low-energy images and filter-free dual-energy images were generated from clinical and low-energy radiographs. The weighting factor to calculate the dual-energy images was determined by means of a novel objective score. The usefulness of dual-energy imaging for real-time tracking with an automated template matching algorithm was investigated. Results: Regular dual-energy imaging was able to increase tracking accuracy in left–right images of the anthropomorphic phantom as well as in 7 out of 24 investigated patient cases. Tracking accuracy remained comparable in three cases and decreased in five cases. Filter-free dual-energy imaging was only able to increase accuracy in 2 out of 24 cases. In four cases no change in accuracy was observed and tracking accuracy worsened in nine cases. In 9 out of 24 cases, it was not possible to define a tracking template due to poor soft-tissue contrast regardless of input images. The mean localization errors using clinical, regular dual-energy, and filter-free dual-energy radiographs were 3.85, 3.32, and 5.24 mm, respectively. Tracking success was dependent on tumor position, tumor size, imaging beam angle, and patient size. Conclusions: This study has highlighted the influence of

Using dual-energy x-ray imaging to enhance automated lung tumor tracking during real-time adaptive radiotherapy

International Nuclear Information System (INIS)

Menten, Martin J.; Fast, Martin F.; Nill, Simeon; Oelfke, Uwe

2015-01-01

Purpose: Real-time, markerless localization of lung tumors with kV imaging is often inhibited by ribs obscuring the tumor and poor soft-tissue contrast. This study investigates the use of dual-energy imaging, which can generate radiographs with reduced bone visibility, to enhance automated lung tumor tracking for real-time adaptive radiotherapy. Methods: kV images of an anthropomorphic breathing chest phantom were experimentally acquired and radiographs of actual lung cancer patients were Monte-Carlo-simulated at three imaging settings: low-energy (70 kVp, 1.5 mAs), high-energy (140 kVp, 2.5 mAs, 1 mm additional tin filtration), and clinical (120 kVp, 0.25 mAs). Regular dual-energy images were calculated by weighted logarithmic subtraction of high- and low-energy images and filter-free dual-energy images were generated from clinical and low-energy radiographs. The weighting factor to calculate the dual-energy images was determined by means of a novel objective score. The usefulness of dual-energy imaging for real-time tracking with an automated template matching algorithm was investigated. Results: Regular dual-energy imaging was able to increase tracking accuracy in left–right images of the anthropomorphic phantom as well as in 7 out of 24 investigated patient cases. Tracking accuracy remained comparable in three cases and decreased in five cases. Filter-free dual-energy imaging was only able to increase accuracy in 2 out of 24 cases. In four cases no change in accuracy was observed and tracking accuracy worsened in nine cases. In 9 out of 24 cases, it was not possible to define a tracking template due to poor soft-tissue contrast regardless of input images. The mean localization errors using clinical, regular dual-energy, and filter-free dual-energy radiographs were 3.85, 3.32, and 5.24 mm, respectively. Tracking success was dependent on tumor position, tumor size, imaging beam angle, and patient size. Conclusions: This study has highlighted the influence of

Using dual-energy x-ray imaging to enhance automated lung tumor tracking during real-time adaptive radiotherapy.

Science.gov (United States)

Menten, Martin J; Fast, Martin F; Nill, Simeon; Oelfke, Uwe

2015-12-01

Real-time, markerless localization of lung tumors with kV imaging is often inhibited by ribs obscuring the tumor and poor soft-tissue contrast. This study investigates the use of dual-energy imaging, which can generate radiographs with reduced bone visibility, to enhance automated lung tumor tracking for real-time adaptive radiotherapy. kV images of an anthropomorphic breathing chest phantom were experimentally acquired and radiographs of actual lung cancer patients were Monte-Carlo-simulated at three imaging settings: low-energy (70 kVp, 1.5 mAs), high-energy (140 kVp, 2.5 mAs, 1 mm additional tin filtration), and clinical (120 kVp, 0.25 mAs). Regular dual-energy images were calculated by weighted logarithmic subtraction of high- and low-energy images and filter-free dual-energy images were generated from clinical and low-energy radiographs. The weighting factor to calculate the dual-energy images was determined by means of a novel objective score. The usefulness of dual-energy imaging for real-time tracking with an automated template matching algorithm was investigated. Regular dual-energy imaging was able to increase tracking accuracy in left-right images of the anthropomorphic phantom as well as in 7 out of 24 investigated patient cases. Tracking accuracy remained comparable in three cases and decreased in five cases. Filter-free dual-energy imaging was only able to increase accuracy in 2 out of 24 cases. In four cases no change in accuracy was observed and tracking accuracy worsened in nine cases. In 9 out of 24 cases, it was not possible to define a tracking template due to poor soft-tissue contrast regardless of input images. The mean localization errors using clinical, regular dual-energy, and filter-free dual-energy radiographs were 3.85, 3.32, and 5.24 mm, respectively. Tracking success was dependent on tumor position, tumor size, imaging beam angle, and patient size. This study has highlighted the influence of patient anatomy on the success rate of real

The method to increase an adequacy and exactitude of the tracking of controlled airplane flight

Directory of Open Access Journals (Sweden)

В. М. Васильєв

2003-03-01

Full Text Available The method to increase the adequacy and exactitude of trajectory estimates for tracking of controlled flight is proposed. The method of a solution of a non-linearity problem is also offered when imitate in trajectory estimation algorithm a control signal which includes nonlinear functions of restriction. The results of computer simulation are demonstrated

On-Line Path Generation and Tracking for High-Speed Wheeled Autonomous Vehicles

Science.gov (United States)

2006-02-17

On-Line Path Generation and Tracking for High-Speed Wheeled Autonomous Vehicles Report Title ABSTRACT In this work we proposed two semi-analytic...298-102 Enclosure 1 On-Line Path Generation and Tracking for High-Speed Wheeled Autonomous Vehicles by...Specifically, the following problems will be addressed during this project: 2.1 Challenges The problem of trajectory planning for high-speed autonomous vehicles is

Trajectory-tracking control of underwater inspection robot for nuclear reactor internals using Time Delay Control

International Nuclear Information System (INIS)

Park, Joon-Young; Cho, Byung-Hak; Lee, Jae-Kyung

2009-01-01

This paper addresses the trajectory control problem of an underwater inspection robot for nuclear reactor internals. From the viewpoint of control engineering, the trajectory control of the underwater robot is a difficult task due to its nonlinear dynamics, which includes various hydraulic forces such as buoyancy and hydrodynamic damping, the difference between the centres of gravity and buoyancy, and disturbances from a tether cable. To solve such problems, we applied Time Delay Control to the underwater robot. This control law has a very simple structure not requiring nonlinear plant dynamics, and was proven to be highly robust against nonlinearities, uncertainties and disturbances. We confirmed its effectiveness through experiments.

Quantifying the Adaptive Cycle.

Directory of Open Access Journals (Sweden)

David G Angeler

Full Text Available The adaptive cycle was proposed as a conceptual model to portray patterns of change in complex systems. Despite the model having potential for elucidating change across systems, it has been used mainly as a metaphor, describing system dynamics qualitatively. We use a quantitative approach for testing premises (reorganisation, conservatism, adaptation in the adaptive cycle, using Baltic Sea phytoplankton communities as an example of such complex system dynamics. Phytoplankton organizes in recurring spring and summer blooms, a well-established paradigm in planktology and succession theory, with characteristic temporal trajectories during blooms that may be consistent with adaptive cycle phases. We used long-term (1994-2011 data and multivariate analysis of community structure to assess key components of the adaptive cycle. Specifically, we tested predictions about: reorganisation: spring and summer blooms comprise distinct community states; conservatism: community trajectories during individual adaptive cycles are conservative; and adaptation: phytoplankton species during blooms change in the long term. All predictions were supported by our analyses. Results suggest that traditional ecological paradigms such as phytoplankton successional models have potential for moving the adaptive cycle from a metaphor to a framework that can improve our understanding how complex systems organize and reorganize following collapse. Quantifying reorganization, conservatism and adaptation provides opportunities to cope with the intricacies and uncertainties associated with fast ecological change, driven by shifting system controls. Ultimately, combining traditional ecological paradigms with heuristics of complex system dynamics using quantitative approaches may help refine ecological theory and improve our understanding of the resilience of ecosystems.

A new paradigm for particle tracking velocimetry, based on graph-theory and pulsed neural network

International Nuclear Information System (INIS)

Derou, D.; Herault, L.

1994-01-01

The Particle Tracking Velocimetry (PTV) technique works by recording, at different instances in time, positions of small tracers particles following a flow and illuminated by a sheet, or pseudo sheet, of light. It aims to recognize each particle trajectory, constituted of n different spots and determine thus each particle velocity vector. In this paper, we devise a new method, taking into account a global consistency of the trajectories to be extracted, in terms of visual perception and physical properties. It is based on a graph-theoretic formulation of the particle tracking problem and the use of an original neural network, called pulsed neural network. (authors). 4 figs

Track-before-detect procedures for detection of extended object

Directory of Open Access Journals (Sweden)

Fan Ling

2011-01-01

Full Text Available Abstract In this article, we present a particle filter (PF-based track-before-detect (PF TBD procedure for detection of extended objects whose shape is modeled by an ellipse. By incorporating of an existence variable and the target shape parameters into the state vector, the proposed algorithm performs joint estimation of the target presence/absence, trajectory and shape parameters under unknown nuisance parameters (target power and noise variance. Simulation results show that the proposed algorithm has good detection and tracking capabilities for extended objects.

A New Computational Technique for the Generation of Optimised Aircraft Trajectories

Science.gov (United States)

Chircop, Kenneth; Gardi, Alessandro; Zammit-Mangion, David; Sabatini, Roberto

2017-12-01

A new computational technique based on Pseudospectral Discretisation (PSD) and adaptive bisection ɛ-constraint methods is proposed to solve multi-objective aircraft trajectory optimisation problems formulated as nonlinear optimal control problems. This technique is applicable to a variety of next-generation avionics and Air Traffic Management (ATM) Decision Support Systems (DSS) for strategic and tactical replanning operations. These include the future Flight Management Systems (FMS) and the 4-Dimensional Trajectory (4DT) planning and intent negotiation/validation tools envisaged by SESAR and NextGen for a global implementation. In particular, after describing the PSD method, the adaptive bisection ɛ-constraint method is presented to allow an efficient solution of problems in which two or multiple performance indices are to be minimized simultaneously. Initial simulation case studies were performed adopting suitable aircraft dynamics models and addressing a classical vertical trajectory optimisation problem with two objectives simultaneously. Subsequently, a more advanced 4DT simulation case study is presented with a focus on representative ATM optimisation objectives in the Terminal Manoeuvring Area (TMA). The simulation results are analysed in-depth and corroborated by flight performance analysis, supporting the validity of the proposed computational techniques.

ARTISTIC VISUALIZATION OF TRAJECTORY DATA USING CLOUD MODEL

Directory of Open Access Journals (Sweden)

T. Wu

2017-09-01

Full Text Available Rapid advance of location acquisition technologies boosts the generation of trajectory data, which track the traces of moving objects. A trajectory is typically represented by a sequence of timestamped geographical locations. Data visualization is an efficient means to represent distributions and structures of datasets and reveal hidden patterns in the data. In this paper, we explore a cloud model-based method for the generation of stylized renderings of trajectory data. The artistic visualizations of the proposed method do not have the goal to allow for data mining tasks or others but instead show the aesthetic effect of the traces of moving objects in a distorted manner. The techniques used to create the images of traces of moving objects include the uncertain line using extended cloud model, stroke-based rendering of geolocation in varying styles, and stylistic shading with aesthetic effects for print or electronic displays, as well as various parameters to be further personalized. The influence of different parameters on the aesthetic qualities of various painted images is investigated, including step size, types of strokes, colour modes, and quantitative comparisons using four aesthetic measures are also involved into the experiment. The experimental results suggest that the proposed method is with advantages of uncertainty, simplicity and effectiveness, and it would inspire professional graphic designers and amateur users who may be interested in playful and creative exploration of artistic visualization of trajectory data.

Real-time detecting and tracking ball with OpenCV and Kinect

Science.gov (United States)

Osiecki, Tomasz; Jankowski, Stanislaw

2016-09-01

This paper presents a way to detect and track ball with using the OpenCV and Kinect. Object and people recognition, tracking are more and more popular topics nowadays. Described solution makes it possible to detect ball based on the range, which is set by the user and capture information about ball position in three dimensions. It can be store in the computer and use for example to display trajectory of the ball.

A silicon track trigger for the DOe experiment

International Nuclear Information System (INIS)

Narain, Meenakshi

2000-01-01

The design of a processor to trigger on long-lived particles (e.g. b-quarks) for the DOe experiment at the Fermilab Tevatron is presented. This device reconstructs the trajectory of the charged particles in the DOe tracking system, which consists of a central fiber tracker and a silicon microstrip tracker. The r-phi impact parameter resolution of the fitted tracks is about 40 μm. This enables the identification of the long-lived b-quarks produced in the decays of various particles, e.g. the top quarks, Higgs Boson, techni-particles and other exotic particles produced in pp-bar collisions at the Tevatron. In this report we describe the design of the architecture and algorithms for the Silicon Track Trigger

A silicon track trigger for the DOe experiment

CERN Document Server

Narain, M

2000-01-01

The design of a processor to trigger on long-lived particles (e.g. b-quarks) for the DOe experiment at the Fermilab Tevatron is presented. This device reconstructs the trajectory of the charged particles in the DOe tracking system, which consists of a central fiber tracker and a silicon microstrip tracker. The r-phi impact parameter resolution of the fitted tracks is about 40 mu m. This enables the identification of the long-lived b-quarks produced in the decays of various particles, e.g. the top quarks, Higgs Boson, techni-particles and other exotic particles produced in pp-bar collisions at the Tevatron. In this report we describe the design of the architecture and algorithms for the Silicon Track Trigger.

ACTS: from ATLAS software towards a common track reconstruction software

CERN Document Server

AUTHOR|(INSPIRE)INSPIRE-00349786; The ATLAS collaboration; Salzburger, Andreas; Kiehn, Moritz; Hrdinka, Julia; Calace, Noemi

2017-01-01

Reconstruction of charged particles' trajectories is a crucial task for most particle physics experiments. The high instantaneous luminosity achieved at the LHC leads to a high number of proton-proton collisions per bunch crossing, which has put the track reconstruction software of the LHC experiments through a thorough test. Preserving track reconstruction performance under increasingly difficult experimental conditions, while keeping the usage of computational resources at a reasonable level, is an inherent problem for many HEP experiments. Exploiting concurrent algorithms and using multivariate techniques for track identification are the primary strategies to achieve that goal. Starting from current ATLAS software, the ACTS project aims to encapsulate track reconstruction software into a generic, framework- and experiment-independent software package. It provides a set of high-level algorithms and data structures for performing track reconstruction tasks as well as fast track simulation. The software is de...

Research on target tracking in coal mine based on optical flow method

Science.gov (United States)

Xue, Hongye; Xiao, Qingwei

2015-03-01

To recognize, track and count the bolting machine in coal mine video images, a real-time target tracking method based on the Lucas-Kanade sparse optical flow is proposed in this paper. In the method, we judge whether the moving target deviate from its trajectory, predicate and correct the position of the moving target. The method solves the problem of failure to track the target or lose the target because of the weak light, uneven illumination and blocking. Using the VC++ platform and Opencv lib we complete the recognition and tracking. The validity of the method is verified by the result of the experiment.

Adaptation of multidimensional group particle tracking and particle wall-boundary condition model to the FDNS code

Science.gov (United States)

Chen, Y. S.; Farmer, R. C.

1992-01-01

A particulate two-phase flow CFD model was developed based on the FDNS code which is a pressure based predictor plus multi-corrector Navier-Stokes flow solver. Turbulence models with compressibility correction and the wall function models were employed as submodels. A finite-rate chemistry model was used for reacting flow simulation. For particulate two-phase flow simulations, a Eulerian-Lagrangian solution method using an efficient implicit particle trajectory integration scheme was developed in this study. Effects of particle-gas reaction and particle size change to agglomeration or fragmentation were not considered in this investigation. At the onset of the present study, a two-dimensional version of FDNS which had been modified to treat Lagrangian tracking of particles (FDNS-2DEL) had already been written and was operational. The FDNS-2DEL code was too slow for practical use, mainly because it had not been written in a form amenable to vectorization on the Cray, nor was the full three-dimensional form of FDNS utilized. The specific objective of this study was to reorder to calculations into long single arrays for automatic vectorization on the Cray and to implement the full three-dimensional version of FDNS to produce the FDNS-3DEL code. Since the FDNS-2DEL code was slow, a very limited number of test cases had been run with it. This study was also intended to increase the number of cases simulated to verify and improve, as necessary, the particle tracking methodology coded in FDNS.

SU-G-JeP1-12: Head-To-Head Performance Characterization of Two Multileaf Collimator Tracking Algorithms for Radiotherapy

International Nuclear Information System (INIS)

Caillet, V; Colvill, E; O’Brien, R; Keall, P; Poulsen, P; Moore, D; Booth, J; Sawant, A

2016-01-01

Purpose: Multi-leaf collimator (MLC) tracking is being clinically pioneered to continuously compensate for thoracic and abdominal motion during radiotherapy. The purpose of this work is to characterize the performance of two MLC tracking algorithms for cancer radiotherapy, based on a direct optimization and a piecewise leaf fitting approach respectively. Methods: To test the algorithms, both physical and in silico experiments were performed. Previously published high and low modulation VMAT plans for lung and prostate cancer cases were used along with eight patient-measured organ-specific trajectories. For both MLC tracking algorithm, the plans were run with their corresponding patient trajectories. The physical experiments were performed on a Trilogy Varian linac and a programmable phantom (HexaMotion platform). For each MLC tracking algorithm, plan and patient trajectory, the tracking accuracy was quantified as the difference in aperture area between ideal and fitted MLC. To compare algorithms, the average cumulative tracking error area for each experiment was calculated. The two-sample Kolmogorov-Smirnov (KS) test was used to evaluate the cumulative tracking errors between algorithms. Results: Comparison of tracking errors for the physical and in silico experiments showed minor differences between the two algorithms. The KS D-statistics for the physical experiments were below 0.05 denoting no significant differences between the two distributions pattern and the average error area (direct optimization/piecewise leaf-fitting) were comparable (66.64 cm2/65.65 cm2). For the in silico experiments, the KS D-statistics were below 0.05 and the average errors area were also equivalent (49.38 cm2/48.98 cm2). Conclusion: The comparison between the two leaf fittings algorithms demonstrated no significant differences in tracking errors, neither in a clinically realistic environment nor in silico. The similarities in the two independent algorithms give confidence in the use

WE-G-BRF-06: Positron Emission Tomography (PET)-Guided Dynamic Lung Tumor Tracking for Cancer Radiotherapy: First Patient Simulations

International Nuclear Information System (INIS)

Yang, J; Loo, B; Graves, E; Yamamoto, T; Keall, P

2014-01-01

Purpose: PET-guided dynamic tumor tracking is a novel concept of biologically targeted image guidance for radiotherapy. A dynamic tumor tracking algorithm based on list-mode PET data has been developed and previously tested on dynamic phantom data. In this study, we investigate if dynamic tumor tracking is clinically feasible by applying the method to lung cancer patient PET data. Methods: PET-guided tumor tracking estimates the target position of a segmented volume in PET images reconstructed continuously from accumulated coincidence events correlated with external respiratory motion, simulating real-time applications, i.e., only data up to the current time point is used to estimate the target position. A target volume is segmented with a 50% threshold, consistently, of the maximum intensity in the predetermined volume of interest. Through this algorithm, the PET-estimated trajectories are quantified from four lung cancer patients who have distinct tumor location and size. The accuracy of the PET-estimated trajectories is evaluated by comparing to external respiratory motion because the ground-truth of tumor motion is not known in patients; however, previous phantom studies demonstrated sub-2mm accuracy using clinically derived 3D tumor motion. Results: The overall similarity of motion patterns between the PET-estimated trajectories and the external respiratory traces implies that the PET-guided tracking algorithm can provide an acceptable level of targeting accuracy. However, there are variations in the tracking accuracy between tumors due to the quality of the segmentation which depends on target-to-background ratio, tumor location and size. Conclusion: For the first time, a dynamic tumor tracking algorithm has been applied to lung cancer patient PET data, demonstrating clinical feasibility of real-time tumor tracking for integrated PET-linacs. The target-to-background ratio is a significant factor determining accuracy: screening during treatment planning would

SU-G-JeP1-12: Head-To-Head Performance Characterization of Two Multileaf Collimator Tracking Algorithms for Radiotherapy

Energy Technology Data Exchange (ETDEWEB)

Caillet, V; Colvill, E [School of Medecine, The University of Sydney, Sydney, NSW (Australia); Royal North Shore Hospital, St Leonards, Sydney (Australia); O’Brien, R; Keall, P [School of Medecine, The University of Sydney, Sydney, NSW (Australia); Poulsen, P [Aarhus University Hospital, Aarhus (Denmark); Moore, D [UT Southwestern Medical Center, Dallas, TX (United States); University of Maryland School of Medicine, Baltimore, MD (United States); Booth, J [Royal North Shore Hospital, St Leonards, Sydney (Australia); Sawant, A [University of Maryland School of Medicine, Baltimore, MD (United States)

2016-06-15

Purpose: Multi-leaf collimator (MLC) tracking is being clinically pioneered to continuously compensate for thoracic and abdominal motion during radiotherapy. The purpose of this work is to characterize the performance of two MLC tracking algorithms for cancer radiotherapy, based on a direct optimization and a piecewise leaf fitting approach respectively. Methods: To test the algorithms, both physical and in silico experiments were performed. Previously published high and low modulation VMAT plans for lung and prostate cancer cases were used along with eight patient-measured organ-specific trajectories. For both MLC tracking algorithm, the plans were run with their corresponding patient trajectories. The physical experiments were performed on a Trilogy Varian linac and a programmable phantom (HexaMotion platform). For each MLC tracking algorithm, plan and patient trajectory, the tracking accuracy was quantified as the difference in aperture area between ideal and fitted MLC. To compare algorithms, the average cumulative tracking error area for each experiment was calculated. The two-sample Kolmogorov-Smirnov (KS) test was used to evaluate the cumulative tracking errors between algorithms. Results: Comparison of tracking errors for the physical and in silico experiments showed minor differences between the two algorithms. The KS D-statistics for the physical experiments were below 0.05 denoting no significant differences between the two distributions pattern and the average error area (direct optimization/piecewise leaf-fitting) were comparable (66.64 cm2/65.65 cm2). For the in silico experiments, the KS D-statistics were below 0.05 and the average errors area were also equivalent (49.38 cm2/48.98 cm2). Conclusion: The comparison between the two leaf fittings algorithms demonstrated no significant differences in tracking errors, neither in a clinically realistic environment nor in silico. The similarities in the two independent algorithms give confidence in the use

The ATLAS FTK Auxiliary Card: A Highly Functional VME Rear Transition Module for a Hardware Track Finding Processing Unit

CERN Document Server

Alison, John; The ATLAS collaboration; Bogdan, Mircea; Bryant, Patrick; Cheng, Yangyang; Krizka, Karol; Shochet, Mel; Tompkins, Lauren; Webster, Jordan S

2014-01-01

The ATLAS Fast TracKer is a hardware-based charged particle track finder for the High Level Trigger system of the ATLAS Experiment at the LHC. Using a multi-component system, it finds charged particle trajectories of 1 GeV/c and greater using data from the full ATLAS silicon tracking detectors at a rate of 100 kHz. Pattern recognition and preliminary track fitting are performed by VME Processing Units consisting of an Associative Memory Board containing custom associative memory chips for pattern recognition, and the Auxiliary Card (AUX), a powerful rear transition module which formats the data for pattern recognition and performs linearized fits on track candidates. We report on the design and testing of the AUX, which utilizes six FPGAs to process up to 32 Gbps of hit data, as well as fit the helical trajectory of one track candidate per nanosecond through a highly parallel track fitting architecture. Both the board and firmware design will be discussed, as well as the performance observed in tests at CERN ...

Track Simulation and Reconstruction in the ATLAS experiment

CERN Document Server

Salzburger, Andreas; Elsing, Markus

The reconstruction and simulation of particle trajectories is an inevitable part of the analysis strate- gies for data taken with the ATLAS detector. Many aspects and necessary parts of a high-quality track reconstruction will be presented and discussed in this work. At first, the technical realisation of the data model and the reconstruction geometry will be given; the reconstruction geometry is charac- terised by a newly developed navigation model and an automated procedure for the synchronisation of the detailed simulation geometry description with the simplified reconstruction geometry model, which allows a precise description of the tracker material in track reconstruction. Both components help the coherent and fast integration of material effects in a newly established track extrapolation package, that is discussed in the following. The extrapolation engine enables a highly precise trans- port of the track parameterisation and the associated covariances through the complex magnetic field and the detec...

Maintaining Unity - relatives in older patients' fast-track treatment programmes. A grounded theory study.

Science.gov (United States)

Berthelsen, Connie Bøttcher; Lindhardt, Tove; Frederiksen, Kirsten

2014-12-01

To generate a substantive grounded theory of relatives' pattern of behaviour in older patients' fast-track treatment programmes during total hip or knee replacement. Fast-track treatment programmes are designed to make total hip and knee replacements more efficient through recovery improvements. The support of relatives during older patients' trajectory is important. However, knowledge is needed on the relatives' pattern of behaviour to strengthen their involvement in fast-track treatment programmes. We used a Glaserian grounded theory approach based on a systematic generation of theory from data to explain the latent pattern of behaviour of relatives. Data were collected from 2010-2011 in orthopaedic wards at two Danish university hospitals and consisted of 14 non-participant observations, 14 postobservational interviews and five interviews. Seven relatives of patients over 70 years of age participated. The constant comparative method was the guiding principle for simultaneous data collection, data analysis and coding, while theoretically sampling and writing memos. Maintaining Unity emerged as the relatives' pattern of behaviour through which they resolved their main concern: preventing the patients from feeling alone. The relatives resolved their main concern through three interchangeable behavioural modes: Protecting Mode, by providing loving and respectful support; Substituting Mode, with practical and cognitive support; and an Adapting Mode, by trying to fit in with the patients' and health professionals' requirements. The substantive theory of Maintaining Unity offers knowledge of relatives' strong desire to provide compassionate and loving support for the older patients during fast-track treatment programmes. © 2014 John Wiley & Sons Ltd.

Parameter Identification of Static Friction Based on An Optimal Exciting Trajectory

Science.gov (United States)

Tu, X.; Zhao, P.; Zhou, Y. F.

2017-12-01

In this paper, we focus on how to improve the identification efficiency of friction parameters in a robot joint. First, the static friction model that has only linear dependencies with respect to their parameters is adopted so that the servomotor dynamics can be linearized. In this case, the traditional exciting trajectory based on Fourier series is modified by replacing the constant term with quintic polynomial to ensure the boundary continuity of speed and acceleration. Then, the Fourier-related parameters are optimized by genetic algorithm(GA) in which the condition number of regression matrix is set as the fitness function. At last, compared with the constant-velocity tracking experiment, the friction parameters from the exciting trajectory experiment has the similar result with the advantage of time reduction.

On the integration scheme along a trajectory for the characteristics method

International Nuclear Information System (INIS)

Le Tellier, Romain; Hebert, Alain

2006-01-01

The issue of the integration scheme along a trajectory which appears for all tracking-based transport methods is discussed from the point of view of the method of characteristics. The analogy with the discrete ordinates method in slab geometry is highlighted along with the practical limitation in transposing high-order S N schemes to a trajectory-based method. We derived an example of such a transposition starting from the linear characteristic scheme. This new scheme is compared with the standard flat-source approximation of the step characteristic scheme and with the diamond differencing scheme. The numerical study covers a 1D analytical case, 2D one-group critical and fixed-source benchmarks and finally a realistic multigroup calculation on a BWR-MOX assembly

A Trajectory Generation Approach for Payload Directed Flight

Science.gov (United States)

Ippolito, Corey A.; Yeh, Yoo-Hsiu

2009-01-01

Presently, flight systems designed to perform payload-centric maneuvers require preconstructed procedures and special hand-tuned guidance modes. To enable intelligent maneuvering via strong coupling between the goals of payload-directed flight and the autopilot functions, there exists a need to rethink traditional autopilot design and function. Research into payload directed flight examines sensor and payload-centric autopilot modes, architectures, and algorithms that provide layers of intelligent guidance, navigation and control for flight vehicles to achieve mission goals related to the payload sensors, taking into account various constraints such as the performance limitations of the aircraft, target tracking and estimation, obstacle avoidance, and constraint satisfaction. Payload directed flight requires a methodology for accurate trajectory planning that lets the system anticipate expected return from a suite of onboard sensors. This paper presents an extension to the existing techniques used in the literature to quickly and accurately plan flight trajectories that predict and optimize the expected return of onboard payload sensors.

Three-dimensional tracking of cardiac catheters using an inverse geometry x-ray fluoroscopy system

International Nuclear Information System (INIS)

Speidel, Michael A.; Tomkowiak, Michael T.; Raval, Amish N.; Van Lysel, Michael S.

2010-01-01

Purpose: Scanning beam digital x-ray (SBDX) is an inverse geometry fluoroscopic system with high dose efficiency and the ability to perform continuous real-time tomosynthesis at multiple planes. This study describes a tomosynthesis-based method for 3D tracking of high-contrast objects and present the first experimental investigation of cardiac catheter tracking using a prototype SBDX system. Methods: The 3D tracking algorithm utilizes the stack of regularly spaced tomosynthetic planes that are generated by SBDX after each frame period (15 frames/s). Gradient-filtered versions of the image planes are generated, the filtered images are segmented into object regions, and then a 3D coordinate is calculated for each object region. Two phantom studies of tracking performance were conducted. In the first study, an ablation catheter in a chest phantom was imaged as it was pulled along a 3D trajectory defined by a catheter sheath (10, 25, and 50 mm/s pullback speeds). SBDX tip tracking coordinates were compared to the 3D trajectory of the sheath as determined from a CT scan of the phantom after the registration of the SBDX and CT coordinate systems. In the second study, frame-to-frame tracking precision was measured for six different catheter configurations as a function of image noise level (662-7625 photons/mm 2 mean detected x-ray fluence at isocenter). Results: During catheter pullbacks, the 3D distance between the tracked catheter tip and the sheath centerline was 1.0±0.8 mm (mean ±one standard deviation). The electrode to centerline distances were comparable to the diameter of the catheter tip (2.3 mm), the confining sheath (4 mm outside diameter), and the estimated SBDX-to-CT registration error (±0.7 mm). The tip position was localized for all 332 image frames analyzed and 83% of tracked positions were inside the 3D sheath volume derived from CT. The pullback speeds derived from the catheter trajectories were within 5% of the programed pullback speeds. The

Approximate Learning and Inference for Tracking with Non-overlapping Cameras

NARCIS (Netherlands)

Zajdel, W.; Kröse, B.; Hamza, M.H.

2003-01-01

Tracking with multiple cameras requires partitioning of ob servations from various sensors into trajectories. In this paper we assume that the observations are generated by a hidden, stochastic 'partition' process and propose a hidden Markov model (HMM) as a generative model for the data. The state

Observations on the geometries of etched fission and alpha-recoil tracks with reference to models of track revelation in minerals

International Nuclear Information System (INIS)

Jonckheere, R.; Enkelmann, E.; Stuebner, K.

2005-01-01

The kinetic and atomistic theories of crystal growth and dissolution are used to interpret the shapes and orientations of fission-track, recoil-track and dislocation etch pits in tri-octahedral phlogopite and di-octahedral muscovite. An atomistic approach combined with symmetry considerations lead to the identification of the periodic bond chains that determine the etch pit morphologies and relative etch rates at a chemical level: O-Mg-O in phlogopite, O-Mg-O-Fe in biotite and O-Al-O in muscovite. Using first-order estimates of the bond strengths, it is possible to account for the relative track etch rates in these minerals. The reported, sometimes simultaneous, occurrence of triangular, polygonal and hexagonal etch pit contours in phlogopite, some of which violate the crystal symmetry, suggests that the cohesion of the phlogopite lattice is lost over a much larger radius than that of the track core around the trajectories of particles for which the energy loss exceeds a threshold value. This is interpreted as an indication of pronounced sublattice and anisotropic effects during track registration

First industrial application of the auto-adaptative MAG STT welding technique with laser joint tracking

International Nuclear Information System (INIS)

Tran Tien, Th.

2007-01-01

The Welding Institute has participated to the plan of construction of the Large Hadron Collider. The hoops of the dipolar magnets are composed of two half cylinders 15 m in length in 10 mm 316LN austenitic stainless steel and are assembled around the magnet in a horizontal-vertical position. The Welding Institute has developed a software for carrying out the auto-adaptative welding technique with laser joint tracking, in using the MAG STT (Surface Tension Transfer) process. The modelling of the welding laws and the strategy of filling the joints in multi-paths absorb the physical tolerances of the preparation (clearance, poor alignment, root..) in dynamic welding condition too. (O.M.)

Speed tracking control of pneumatic motor servo systems using observation-based adaptive dynamic sliding-mode control

Science.gov (United States)

Chen, Syuan-Yi; Gong, Sheng-Sian

2017-09-01

This study aims to develop an adaptive high-precision control system for controlling the speed of a vane-type air motor (VAM) pneumatic servo system. In practice, the rotor speed of a VAM depends on the input mass air flow, which can be controlled by the effective orifice area (EOA) of an electronic throttle valve (ETV). As the control variable of a second-order pneumatic system is the integral of the EOA, an observation-based adaptive dynamic sliding-mode control (ADSMC) system is proposed to derive the differential of the control variable, namely, the EOA control signal. In the ADSMC system, a proportional-integral-derivative fuzzy neural network (PIDFNN) observer is used to achieve an ideal dynamic sliding-mode control (DSMC), and a supervisor compensator is designed to eliminate the approximation error. As a result, the ADSMC incorporates the robustness of a DSMC and the online learning ability of a PIDFNN. To ensure the convergence of the tracking error, a Lyapunov-based analytical method is employed to obtain the adaptive algorithms required to tune the control parameters of the online ADSMC system. Finally, our experimental results demonstrate the precision and robustness of the ADSMC system for highly nonlinear and time-varying VAM pneumatic servo systems.

Knee medial and lateral contact forces in a musculoskeletal model with subject-specific contact point trajectories.

Science.gov (United States)

Zeighami, A; Aissaoui, R; Dumas, R

2018-03-01

Contact point (CP) trajectory is a crucial parameter in estimating medial/lateral tibio-femoral contact forces from the musculoskeletal (MSK) models. The objective of the present study was to develop a method to incorporate the subject-specific CP trajectories into the MSK model. Ten healthy subjects performed 45 s treadmill gait trials. The subject-specific CP trajectories were constructed on the tibia and femur as a function of extension-flexion using low-dose bi-plane X-ray images during a quasi-static squat. At each extension-flexion position, the tibia and femur CPs were superimposed in the three directions on the medial side, and in the anterior-posterior and proximal-distal directions on the lateral side to form the five kinematic constraints of the knee joint. The Lagrange multipliers associated to these constraints directly yielded the medial/lateral contact forces. The results from the personalized CP trajectory model were compared against the linear CP trajectory and sphere-on-plane CP trajectory models which were adapted from the commonly used MSK models. Changing the CP trajectory had a remarkable impact on the knee kinematics and changed the medial and lateral contact forces by 1.03 BW and 0.65 BW respectively, in certain subjects. The direction and magnitude of the medial/lateral contact force were highly variable among the subjects and the medial-lateral shift of the CPs alone could not determine the increase/decrease pattern of the contact forces. The suggested kinematic constraints are adaptable to the CP trajectories derived from a variety of joint models and those experimentally measured from the 3D imaging techniques. Copyright © 2018 Elsevier Ltd. All rights reserved.

PageRank tracker: from ranking to tracking.

Science.gov (United States)

Gong, Chen; Fu, Keren; Loza, Artur; Wu, Qiang; Liu, Jia; Yang, Jie

2014-06-01

Video object tracking is widely used in many real-world applications, and it has been extensively studied for over two decades. However, tracking robustness is still an issue in most existing methods, due to the difficulties with adaptation to environmental or target changes. In order to improve adaptability, this paper formulates the tracking process as a ranking problem, and the PageRank algorithm, which is a well-known webpage ranking algorithm used by Google, is applied. Labeled and unlabeled samples in tracking application are analogous to query webpages and the webpages to be ranked, respectively. Therefore, determining the target is equivalent to finding the unlabeled sample that is the most associated with existing labeled set. We modify the conventional PageRank algorithm in three aspects for tracking application, including graph construction, PageRank vector acquisition and target filtering. Our simulations with the use of various challenging public-domain video sequences reveal that the proposed PageRank tracker outperforms mean-shift tracker, co-tracker, semiboosting and beyond semiboosting trackers in terms of accuracy, robustness and stability.

Robust Adaptive Neurocontrol of SISO Nonlinear Systems Preceded by Unknown Deadzone

Directory of Open Access Journals (Sweden)

J. Humberto Pérez-Cruz

2012-01-01

Full Text Available In this study, the problem of controlling an unknown SISO nonlinear system in Brunovsky canonical form with unknown deadzone input in such a way that the system output follows a specified bounded reference trajectory is considered. Based on universal approximation property of the neural networks, two schemes are proposed to handle this problem. The first scheme utilizes a smooth adaptive inverse of the deadzone. By means of Lyapunov analyses, the exponential convergence of the tracking error to a bounded zone is proven. The second scheme considers the deadzone as a combination of a linear term and a disturbance-like term. Thus, the estimation of the deadzone inverse is not required. By using a Lyapunov-like analyses, the asymptotic converge of the tracking error to a bounded zone is demonstrated. Since this control strategy requires the knowledge of a bound for an uncertainty/disturbance term, a procedure to find such bound is provided. In both schemes, the boundedness of all closed-loop signals is guaranteed. A numerical experiment shows that a satisfactory performance can be obtained by using any of the two proposed controllers.

Location-allocation algorithm for multiple particle tracking using Birmingham MWPC positron camera

International Nuclear Information System (INIS)

Gundogdu, O.; Tarcan, E.

2004-01-01

Positron Emission Particle Tracking is a powerful, non-invasive technique that employs a single radioactive particle. It has been applied to a wide range of industrial systems. This paper presents an original application of a technique, which was mainly developed in economics or resource management. It allows the tracking of multiple particles using small number of trajectories with correct tagging. This technique originally used in economics or resource management provides very encouraging results

Location-allocation algorithm for multiple particle tracking using Birmingham MWPC positron camera

Energy Technology Data Exchange (ETDEWEB)

Gundogdu, O. E-mail: o.gundogdu@surrey.ac.uko_gundo@yahoo.co.uko.gundogdu@kingston.ac.uk; Tarcan, E

2004-05-01

Positron Emission Particle Tracking is a powerful, non-invasive technique that employs a single radioactive particle. It has been applied to a wide range of industrial systems. This paper presents an original application of a technique, which was mainly developed in economics or resource management. It allows the tracking of multiple particles using small number of trajectories with correct tagging. This technique originally used in economics or resource management provides very encouraging results.

Coordinated trajectory planning of dual-arm space robot using constrained particle swarm optimization

Science.gov (United States)

Wang, Mingming; Luo, Jianjun; Yuan, Jianping; Walter, Ulrich

2018-05-01

Application of the multi-arm space robot will be more effective than single arm especially when the target is tumbling. This paper investigates the application of particle swarm optimization (PSO) strategy to coordinated trajectory planning of the dual-arm space robot in free-floating mode. In order to overcome the dynamics singularities issue, the direct kinematics equations in conjunction with constrained PSO are employed for coordinated trajectory planning of dual-arm space robot. The joint trajectories are parametrized with Bézier curve to simplify the calculation. Constrained PSO scheme with adaptive inertia weight is implemented to find the optimal solution of joint trajectories while specific objectives and imposed constraints are satisfied. The proposed method is not sensitive to the singularity issue due to the application of forward kinematic equations. Simulation results are presented for coordinated trajectory planning of two kinematically redundant manipulators mounted on a free-floating spacecraft and demonstrate the effectiveness of the proposed method.

3D scanning particle tracking velocimetry

Energy Technology Data Exchange (ETDEWEB)

Hoyer, Klaus; Holzner, Markus; Guala, Michele; Liberzon, Alexander; Kinzelbach, Wolfgang [Swiss Federal Institut of Technology Zurich, Institut fuer Hydromechanik und Wasserwirtschaft, Zuerich (Switzerland); Luethi, Beat [Risoe National Laboratory, Roskilde (Denmark)

2005-11-01

In this article, we present an experimental setup and data processing schemes for 3D scanning particle tracking velocimetry (SPTV), which expands on the classical 3D particle tracking velocimetry (PTV) through changes in the illumination, image acquisition and analysis. 3D PTV is a flexible flow measurement technique based on the processing of stereoscopic images of flow tracer particles. The technique allows obtaining Lagrangian flow information directly from measured 3D trajectories of individual particles. While for a classical PTV the entire region of interest is simultaneously illuminated and recorded, in SPTV the flow field is recorded by sequential tomographic high-speed imaging of the region of interest. The advantage of the presented method is a considerable increase in maximum feasible seeding density. Results are shown for an experiment in homogenous turbulence and compared with PTV. SPTV yielded an average 3,500 tracked particles per time step, which implies a significant enhancement of the spatial resolution for Lagrangian flow measurements. (orig.)

Root locus analysis and design of the adaptation process in active noise control.

Science.gov (United States)

Tabatabaei Ardekani, Iman; Abdulla, Waleed H

2012-10-01

This paper applies root locus theory to develop a graphical tool for the analysis and design of adaptive active noise control systems. It is shown that the poles of the adaptation process performed in these systems move on typical trajectories in the z-plane as the adaptation step-size varies. Based on this finding, the dominant root of the adaptation process and its trajectory can be determined. The first contribution of this paper is formulating parameters of the adaptation process root locus. The next contribution is introducing a mechanism for modifying the trajectory of the dominant root in the root locus. This mechanism creates a single open loop zero in the original root locus. It is shown that appropriate localization of this zero can cause the dominant root of the locus to be pushed toward the origin, and thereby the adaptation process becomes faster. The validity of the theoretical findings is confirmed in an experimental setup which is implemented using real-time multi-threading and multi-core processing techniques.

Adaptive Monocular Visual-Inertial SLAM for Real-Time Augmented Reality Applications in Mobile Devices.

Science.gov (United States)

Piao, Jin-Chun; Kim, Shin-Dug

2017-11-07

Simultaneous localization and mapping (SLAM) is emerging as a prominent issue in computer vision and next-generation core technology for robots, autonomous navigation and augmented reality. In augmented reality applications, fast camera pose estimation and true scale are important. In this paper, we present an adaptive monocular visual-inertial SLAM method for real-time augmented reality applications in mobile devices. First, the SLAM system is implemented based on the visual-inertial odometry method that combines data from a mobile device camera and inertial measurement unit sensor. Second, we present an optical-flow-based fast visual odometry method for real-time camera pose estimation. Finally, an adaptive monocular visual-inertial SLAM is implemented by presenting an adaptive execution module that dynamically selects visual-inertial odometry or optical-flow-based fast visual odometry. Experimental results show that the average translation root-mean-square error of keyframe trajectory is approximately 0.0617 m with the EuRoC dataset. The average tracking time is reduced by 7.8%, 12.9%, and 18.8% when different level-set adaptive policies are applied. Moreover, we conducted experiments with real mobile device sensors, and the results demonstrate the effectiveness of performance improvement using the proposed method.

Adaptive Monocular Visual–Inertial SLAM for Real-Time Augmented Reality Applications in Mobile Devices