Parallel frequency filtering

The frequency filtering method is a robust and efficient ILU-like solver for large sparse systems (cf. [9,10]). Combining this method with the so-called Schur-complement DD method, we obtain a fast parallel solver. In this context, frequency filtering can be applied as solver inside the subdomains as well as for the treatment of the arising Schur complements. Especially for those, the method is well suited since it is highly parallelizable by recursively applying the same decomposition as to the original system. In this paper, an implementation of the frequency filtering domain decomposition (FFDD) method on a multiprocessor system will be presented and the numerical results of some variants thereof be discussed. The scaling behaviour of the algorithm for an increasing number of processors is almost optimal.     

Realtime tracking and performance analysers for use in drug evaluation

Psychoactive drugs, while influencing the mood and personality of an individual, can exert quite serious and incapacitating side effects with regard to complex tasks such as the operation of complex machinery or car driving. The paper concerns the design of a microprocessor-based method of assessing the extent of these side effects. The dual-task system described allows experimenters in pharmacology and psychology to study the redistribution of a patient's attention after medication. A car driving analogy is used: tracking represents the steering task, and at the same time the patient's awareness of peripheral activity (eg on the ‘pavement’) is monitored. Initial results obtained with the proposed method are summarized.     

On interval tracking performance evaluation and practical varying sampling ILC

This paperconsiders the evaluation of interval tracking error for sampled control performance and an associated sampling technique to enhance the tracking performance. The upper bounds of the tracking error profile of arbitrary sample interval for both the linear system and nonlinear system are first given. A practical sampled-data iterative learning control with varying sampling rates is proposed to ensure a prior given tolerant tracking error. In this control strategy, the inter-sample behaviour is checked to determine which intervals are not satisfactory when the given tracking performance at-sample time instants is satisfied, and then the sampling frequency for such intervals is increased. Both at-sample and inter-sample tracking performance are satisfied after enough learning iterations. Two examples are simulated to demonstrate the effectiveness of the proposed sampling strategy.     

Adaptive control with optimal tracking performance

This paper provides a way to optimise the steady-state tracking performance of the adaptive control system in the presence of unknown external disturbances. A-priori knowledge of the dynamic model of the reference signal to be tracked is not completely known. Especially, the updatable non-empty admissible model set, which is consistent to the a-priori knowledge of the plant parameter and the online measurements, is computed. Treating the overall system performance as the criteria, the nominal model is optimally chosen within the admissible model set. The optimal nominal model is subsequently used to synthesise the optimal closed-loop controller that minimises the steady-state absolute value of the tracking error. Combining the above two aspects, an optimal adaptive control scheme is proposed. Because of the consistency of the identification criteria and control object, the adaptive control scheme proposed in this paper can achieve the overall optimal steady-state tracking performance, and the effect of the interplay between the identification and control of the adaptive system can be handled effectively. In addition, the computable optimal performance is also provided.     

A single performance characteristic for the evaluation of seeker tracking algorithms

This paper presents a single numerical performance characteristic for the evaluation of seeker tracking algorithms. It concentrates on ship IR seeker tracking algorithms. Assessing the threat from guided missiles needs a sound evaluation of their performance. The main goal is to introduce a characteristic which is able to assess the threat for ships depending on various scenario parameters. It is shown that for these applications such a single characteristic is sufficient. In order to achieve this five popular tracking algorithms are used. Synthetic IR image sequences are generated to simulate a large set of attack approaches and assemble sufficient statistics on the behavior of the algorithms. The introduced characteristic can also be used for investigations on algorithms themselves, e.g. for sensitivity analyses and parameter optimization of a single algorithm, and for comparison of different algorithms.     

目标跟踪算法的并行优化

目标跟踪是计算机视觉领域一个重要的研究方向,近年来学者提出了众多优秀的目标跟踪算法,但许多算法的低实时性制约了其在应用场景中的有效性。针对这些算法,提出了一个通用的跟踪模型,并针对此模型提出了一个可行的并行优化方案。之后使用SCM算法验证了所提出的并行优化方案。在四核CPU的环境下,并行后的SCM算法相比于未并行的算法取得了3.48倍的并行加速比,并且比原算法Matlab+C程序的运行速度快了约30倍,这说明了所提出的并行优化方案的有效性。     

MPC for tracking with optimal closed-loop performance

In the recent paper [Limon, D., Alvarado, I., Alamo, T., & Camacho, E.F. (2008). MPC for tracking of piece-wise constant references for constrained linear systems. Automatica, 44, 2382-2387], a novel predictive control technique for tracking changing target operating points has been proposed. Asymptotic stability of any admissible equilibrium point is achieved by adding an artificial steady state and input as decision variables, specializing the terminal conditions and adding an offset cost function to the functional.In this paper, the closed-loop performance of this controller is studied and it is demonstrated that the offset cost function plays an important role in the performance of the model predictive control (MPC) for tracking. Firstly, the controller formulation has been enhanced by considering a convex, positive definite and subdifferential function as the offset cost function. Then it is demonstrated that this formulation ensures convergence to an equilibrium point which minimizes the offset cost function. Thus, in case of target operation points which are not reachable steady states or inputs for the constrained system, the proposed control law steers the system to an admissible steady state (different to the target) which is optimal with relation to the offset cost function. Therefore, the offset cost function plays the role of a steady-state target optimizer which is built into the controller. On the other hand, optimal performance of the MPC for tracking is studied and it is demonstrated that under some conditions on both the offset and the terminal cost functions optimal closed-loop performance is locally achieved.     

Parallel implementation of multiple model tracking algorithms

The implementations of the Viterbi algorithm (VA) and the interacting multiple model (IMM) algorithm on a shared-bus and shared-memory multiple-input multiple-data (MIMD) multiprocessor are discussed. The computational complexity as well as the speedup and efficiency are examined in detail. It is shown that the computational complexity of the parallel implementation of these algorithms is about the same in both memory space and processing time categories. Efficiency with P processors is about 1-1/P for small P and is expected to be relatively high for large P, especially when many filters and large state and measurement vectors are considered     

Neural net robot controller with guaranteed tracking performance

A neural net (NN) controller for a general serial-link robot arm is developed. The NN has two layers so that linearity in the parameters holds, but the "net functional reconstruction error" and robot disturbance input are taken as nonzero. The structure of the NN controller is derived using a filtered error/passivity approach, leading to new NN passivity properties. Online weight tuning algorithms including a correction term to backpropagation, plus an added robustifying signal, guarantee tracking as well as bounded NN weights. The NN controller structure has an outer tracking loop so that the NN weights are conveniently initialized at zero, with learning occurring online in real-time. It is shown that standard backpropagation, when used for real-time closed-loop control, can yield unbounded NN weights if (1) the net cannot exactly reconstruct a certain required control function or (2) there are bounded unknown disturbances in the robot dynamics. The role of persistency of excitation is explored.     

基于嵌入式WEB的视频服务器的设计

本文介绍了一个基于嵌入式WEB技术的网络视频监控系统的设计与实现,重点阐述其嵌入式服务器软硬件部分的设计思想和体系架构,并对其中涉及的若干关键技术进行了较为详细的介绍.     

Comparative performance evaluation of CAR systems based on mobile phones and feature tracking

Collaborative Augmented Reality (CAR) systems based on mobile phones have experienced a huge expansion last years, since the hardware features of most mobile phones provide excellent multimedia services and wireless network capabilities. In previous works, we improved the performance of large-scale CAR systems based on mobile phones that use fiducial marker tracking. However, CAR systems based on natural feature tracking have just emerged, changing the way in which Augmented Reality applications work. In this paper, we propose the performance evaluation of CAR systems based on feature tracking when using mobile phones, and their comparison with CAR systems based on fiducial marker tracking. The evaluation of the whole CAR system includes the rendering of the virtual environment with Unity3D. The purpose is to provide the reader with a reference about the performance that can be achieved with each kind of CAR system. The evaluation results of client devices show that they work faster with natural feature (commonly denoted as markerless) tracking than with fiducial marker tracking, regardless of the phone model and the operating system considered. The evaluation results of the whole CAR system show that natural feature tracking provides similar performance than fiducial marker tracking when the system reaches saturation. However, the use of natural feature tracking allows better performance for low workloads or when the system approaches saturation, since, it provides similar response times at the cost of increasing the percentage of CPU utilization in the server, instead of dropping messages. These results validate natural feature tracking as the best option for CAR systems based on mobile phones.     

Boundary scan with built-in self-test

The authors propose a way to merge boundary scan with the built-in self-test (BIST) of printed circuit boards. Their boundary-scan structure is based on Version 2.0 of the Joint Task Action Group's recommendations for boundary scan and incorporates BIST using a register based on cellular automata (CA) techniques. They examine test patterns generated from this register and the more conventional linear-feedback shift register. The advantages of the CA register, or CAR, are its modularity, which allows modification without major redesign, its higher stuck-at fault coverage, and its higher transition fault coverage     

Parallel border tracking in binary images using GPUs

The Journal of Supercomputing - Border tracking in binary images is an important kernel for many applications. There are very efficient sequential algorithms, most notably, the algorithm proposed...     

Parallel accelerated computing architecture for dim target tracking on-board

The real-time tracking process of dim targets in space is mainly achieved through the correlation and prediction of dots after the detection and calculation process. The on-board calculation of the tracking needs to be completed in milliseconds, and it needs to reach the microsecond level at high frame rates. For real-time tracking of dim targets in space, it is necessary to achieve universal tracking calculation acceleration in response to different space regions and complex backgrounds, which poses high requirements for engineering implementation architecture. This paper designs a Kalman filter calculation based on digital logic parallel acceleration architecture for real-time solution of dim target tracking on-board. A unified architecture of Vector Processing Element (VPE) was established for the calculation of Kalman filtering matrix, and an array computing structure based on VPE was designed to decompose the entire filtering process and form a parallel pipelined data stream. The prediction errors under different fixed point bit widths were analyzed and deduced, and the guidance methods for selecting the optimal bit width based on the statistical results were provided. The entire design was engineered based on Xilinx's XC7K325T, resulting in an energy efficiency improvement compared to previous designs. The single iteration calculation time does not exceed 0.7 microseconds, which can meet the current high frame rate target tracking requirements. The effectiveness of this design has been verified through simulation of random trajectory data, which is consistent with the theoretical calculation error.     

A double-filter-structure based COMPASS/INS deep integrated navigation system implementation and tracking performance evaluation

Beidou or COMPASS is a Chinese GNSS(global navigation satellite system).Like the GPS receiver,the COMPASS receiver also faces the challenge of choosing an optimal bandwidth to satisfy both anti-jamming capability and dynamics adaptation simultaneously.GPS/INS(inertial navigation system)deep integrated navigation system has solved this problem by fusing GPS baseband signal and INS information in a deeply coupled mode.In this study,a COMPASS B3 frequency is considered and a traditional federated GPS/INS deep integration model is used to derive a single-filter-structure based COMPASS/INS deep integration model.Besides,a double-filter-structure based COMPASS/INS deep integration model is proposed.The simulation results show a better carrier tracking performance,especially a better dynamics adaptation.The impact of IMU errors and vehicle’s dynamics on carrier tracking performance of the double-filter-structure based COMPASS/INS deep integrated navigation system are evaluated in simulated and field environments.Simulation and field test results are in accordance with the theory analysis.     

具有未知输入增益的非线性系统的跟踪控制

针对具有未知输入增益的非线性系统, 提出了一种可实现系统输出跟踪控制的自适应控制方法. 通过在backstepping设计中引入一种新的Nausbaum增益, 按该方法设计的控制器可以在系统输入增益未知的情况下实现系统输出的渐近跟踪.     

Adaptive tracking control of an MEMS gyroscope with H-infinity performance

Microelectromechanical systems (MEMSs) pose unique measurement and control problems compared with conventional ones because of their small size,low cost,and low power consumption.The vibrating gyroscope is one of those MEMS devices that have significant potential in many industry applications.When the MEMS gyroscope system is considered simultaneously with the coupling terms,the exogenous disturbances and the parameter variations,the controller design of this system becomes very challenging.This paper investigates the primary control problem of a perturbed vibrating MEMS gyroscope.A nonlinear robust adaptive control scheme is proposed for the drive axis of a vibrating MEMS gyroscope.By combining the dynamic surface control (DSC) method with the H-infinity disturbance attenuation technique,a simpler systematic design procedure is developed.The derived H-infinity controller has a simplified structure,and it can drive the drive axis to resonance,regulate the output amplitude of the drive axis to a desired value,and attenuate the generalized disturbances.The features of the derived controller are discussed and illustrated by the simulation of a closed-loop system.The analysis and simulation show that the obtained controller possesses good adaptability and robustness to system uncertainties.     

Optimal tracking performance of network time-delay systems with multiple constraints

This paper investigates the optimal tracking performance based on the codec, colored noise, and bandwidth constraints in the network time-delay systems. Choosing the optimal two-degree-of-freedom compensator and the dominant expression of the system optimal tracking performance is obtained after Youla parameterization by using the coprime factorizations method and spectral decomposition technology. The result shows that the tracking performance of the system is determined by the nonminimum phase zero and unstable pole of the controlled plant. Moreover, codec, colored noise, and bandwidth constraints can also significantly impact the performance. Finally, two simulation examples prove the accuracy of the theory.     

Robust attitude tracking for rigid spacecraft with prescribed transient performance

This paper investigates the prescribed performance attitude tracking control problem of a rigid spacecraft with uncertain dynamics and bounded disturbances. By suitable selection of the configuration error function, the trajectory tracking problem on SO(3) is transformed into a point stabilisation problem of an error dynamic system in the associated Lie algebra. The predefined transient performance indexes, which include the maximum steady-state error and overshoot, and the minimum convergence rate of the attitude error vector, are characterised as the inequality constraints. For the tracking controller design, the error transformation technique is utilised to transform the attitude error dynamics with inequality constraints to an equivalent ‘unconstrained’ error one. Then, a coordinate-free robust tracking controller is designed for the ‘unconstrained’ error dynamics to solve the prescribed performance attitude tracking control problem. A rigorous mathematical stability proof is given. Finally, numerical simulations are presented to demonstrate the effectiveness and robustness of the proposed controller.