基于相机的多投影光度补偿系统

现有关于光度补偿的研究主要基于单投影,可在带有纹理和颜色的表面上进行投影显示。而在多投影系统中,由于多投影带来了重叠区域的光度不一致性,相机的每个像素覆盖的区域增大等问题,容易致使光度补偿失败。介绍一种基于相机的多投影光度补偿系统,虽然也是通过获取环境参数的手段,但提出一种方便快捷的迭代方式来提高投影表面反射率参数的获取精度,可以达到更好的效果,并仅需对投影区域捕捉两幅以上图像。同时,对多投影仪重叠区域的融合效果也做了改进,统一解决了光度补偿和投影拼接问题。最后,提供的实验结果表明有较好的改进效果。     

Real-time adaptive resource management

Distributed mission-critical environments employ a mixture of hard and soft real-time applications that usually expect a guaranteed range of quality of service (QoS). These applications have different levels of criticality and varied structures ranging from periodic independent tasks to distributed pipelines or event-driven modules. The underlying distributed system must evolve and adapt to the high variability in resource demands that competing applications impose. The current industry trend is to use commercial off-the-shelf (COTS) hardware and software components to build distributed environments for mission-critical applications. The paper considers how adding a middleware layer above the COTS components facilitates consistent management of system resources, decreases system complexity, and reduces development costs     

Real-time adaptive contrast enhancement

A recursive filter approach is introduced to simplify real-time implementation of an adaptive contrast enhancement scheme for imaging sensors. With this scheme, even scenes possessing large global dynamic ranges (>40 dB) can be accommodated by the limited dynamic range (20 dB) of a display without losing the local contrast essential for image interpretation. This paper describes the recursive filter implementation of the local area contrast enhancement scheme using charge-coupled devices and the resultant real-time hardware capable of processing standard 525 and 875 line TV compatible video (from vidicons, videotape recorders, etc). Several examples from video imagery are included to demonstrate its effectiveness.     

视频实时自适应去雾算法

在雾天环境下,户外视频的可视性将受到极大损害,需要通过视频实时去雾来恢复视频的可视性。视频实时去雾对于单帧图像处理的速度有很高的要求,现有的图像去雾算法或是速度上达不到要求,或是速度虽快但去雾效果不理想。另外,视频还会面临拍摄场景中雾气浓度不断变化的问题,现有图像去雾算法中需要手动设置参数且参数固定,无法在雾气浓度变化的条件下始终达到理想的去雾效果。提出了一种实时的视频自适应去雾算法,该算法对视频中单帧图像进行去雾时,会基于暗原色值来区分图像区域,并对不同区域进行不同程度的去雾,在满足实时性的同时得到了很好的去雾效果。此外,该算法还基于暗通道先验设计了评价去雾结果的方法,并使用迭代的方式根据雾气浓度自动调整去雾参数,从而在视频中雾气浓度变化的情况下,始终能达到理想的去雾效果。     

运动控制中的鲁棒自适应死区补偿

在高精度PD控制器中,死区可能会产生极限环,而且,死区参数往往未知.本文针对有非对称死区的直流伺服系统,设计了一种鲁棒自适应预补偿控制器,这种控制器不仅对死区的不确定性具有鲁棒性,而且对惯性及粘性摩擦等参数的不确定性,及外部扰动都有较强的鲁棒性.采用Lyapunov理论证明了这种控制器能够保证跟踪误差一致最终有界.并且调整调节控制器的参数可以改变跟踪误差.仿真结果表明了这种方法的有效性.     

Real-time range acquisition by adaptive structured light

The goal of this paper is to provide a "self-adaptive" system for real-time range acquisition. Reconstructions are based on a single frame structured light illumination. Instead of using generic, static coding that is supposed to work under all circumstances, system adaptation is proposed. This occurs on-the-fly and renders the system more robust against instant scene variability and creates suitable patterns at startup. A continuous trade-off between speed and quality is made. A weighted combination of different coding cues - based upon pattern color, geometry, and tracking - yields a robust way to solve the correspondence problem. The individual coding cues are automatically adapted within a considered family of patterns. The weights to combine them are based on the average consistency with the result within a small time-window. The integration itself is done by reformulating the problem as a graph cut. Also, the camera-projector configuration is taken into account for generating the projection patterns. The correctness of the range maps is not guaranteed, but an estimation of the uncertainty is provided for each part of the reconstruction. Our prototype is implemented using unmodified consumer hardware only and, therefore, is cheap. Frame rates vary between 10 and 25 fps, dependent on scene complexity.     

Real-time structured light coding for adaptive patterns

Coded structured light is a technique that allows the 3D reconstruction of poorly or non-textured scene areas. With the codes uniquely associated with visual primitives of the projected pattern, the correspondence problem is quickly solved by means of local information only, with robustness against disturbances like high surface curvatures, partial occlusions, out-of-field of view or out-of-focus. Real-time 3D reconstruction with one shot is possible with pseudo-random arrays, where the encoding is done in a single pattern using spatial neighbourhood. To correct more mismatched visual primitives and to get patterns globally more robust, a higher Hamming distance between all the used codewords should be suited. Recent works in the structured light field have shown a growing interest for adaptive patterns. These can account for geometrical or spectral specificities of the scene to provide better features matching and reconstructions. Up till today, such patterns cannot benefit from the robustness offered by spatial neighbourhood coding with a minimal Hamming distance constraint, because the existing algorithms for such a class of coding are designed with an offline coding only. In this article, we show that due to two new contributions, a mixed exploration/exploitation search behaviour and a O(n ²) to ～O(n) complexity reduction using the epipolar constraint, the real-time coding of patterns having similar properties than those coded offline can be achieved. This allows to design a complete closed-loop processing pipeline for adaptive patterns.     

Real-time adaptive fluid simulation with complex boundaries

In this paper, we present a new adaptive model for real-time fluid simulation with complex boundaries based on Smoothed Particle Hydrodynamics (SPH) framework. Firstly, we introduce an adaptive SPH framework that is based on our character field function composed of four factors: geometrical complexity, boundary condition, physical complexity, and complementary condition in terms of the neighboring particle number. Meanwhile, the rule for particle adaptation is presented. We also present a two-step method to fast detect collision with complex boundary. The first step is voxelization on the complex scene. In the second step, based on the result of voxelization, we propose a three-phase method to fast detect collisions between complex boundaries and particles. By using this method, we avoid most of the useless intersection detection computation and greatly enhance the computation efficiency. In addition, a subdivision of boundary is precomputed before the collision interaction method so that fluid in a scene with complex boundary can still be simulated at relatively high speed and system stability risk is reduced greatly. To further accelerate the simulation, a highly parallel fluid algorithm is presented and implemented using GPU so that we can simulate dynamic fluid with mutual interaction between fluid and complex boundary at a considerably fast speed without compromising realism.     

传感器网络中一种实时的自适应时隙调度算法

无线传感器网络节点数目众多,MAC协议为节点分配工作时隙面临能量利用不高、节点延时较长等方面的难题。目前基于时隙调度的MAC协议一般采用等长的时隙大小,不能适应数据流量变化大的网络且忽略与网络层的融合,没有利用路由层信息来减低时隙分配算法性能代价。提出一种基于路由转发树的时隙调度算法（ATSA）,网络采用簇结构,在簇内构造一棵路由转发树,根据路由转发树形成的路径信息对节点实时获取节点每轮需要发送的数据量大小,根据节点的数据量大小来分配节点每轮需要的时隙,然后由簇头据此动态地为成员节点分配时隙,降低时隙划分的能量和时间代价,减少空闲侦听时间,避免串音。仿真表明,该算法有效地提高了网络能量利用效率,延长了网络生存周期,降低数据包的延时。     

基于自适应背景的实时运动物体检测

为了能够在监控系统中实时的检测出运动物体,提出了一种能够自适应获取并更新背景的运动检测方法。它是利用连续帧差分,当前帧与背景图像差分来获取运动信息,同时选择性的更新背景。实验证明该算法运算量小,鲁棒性好,算法中通过直方图分析来获取合适的阈值,提高了系统的自动化程度。     

PD manipulator controller with fuzzy adaptive gravity compensation

This paper presents a PD manipulator controller with fuzzy adaptive gravity compensation. The main idea is to use a fuzzy adaptive controller to compensate for the gravity term of the robotic manipulator. This controller is designed by using Lyapunov's stability theorem, which guarantees system stability. Simulation is implemented on a two‐link manipulator by using MATALAB and SIMULINK. The results show that this fuzzy adaptive controller makes the manipulator trajectory converge to a desired position. Compared with other proposed fuzzy adaptive manipulator controllers, the PD manipulator controller with fuzzy adaptive gravity compensation is conceptually and structurally simpler and guarantees zero position error. ©2000 John Wiley & Sons, Inc.     

Support vector networks in adaptive friction compensation.

This paper presents our research on how support vector regression (SVR) and parametric adaptive learning, which are normally used independently, can be exploited together to benefit adaptive neural control. In the context of friction compensation for servo-motion control systems, we present the notion of support vector networks which play an essential role in combining SVR and adaptive neural network (NN) in cooperation for friction estimation. The analysis shows that the proposed support vector network contributes not only to the performance improvement but also to the practical usefulness in adaptive friction compensation. Experimental results are reported to demonstrate the effectiveness of the proposed approach.     

An adaptive actuator failure compensation controller using outputfeedback

An adaptive control scheme using output feedback for output tracking is developed for systems with unknown actuator failures. Such actuator failures are characterized by some unknown inputs stuck at some unknown fixed values at unknown time instants. An effective output feedback controller structure is proposed for actuator failure compensation. When implemented with true matching parameters, the controller achieves desired plant-model output matching. When implemented with adaptive parameter estimates, the controller achieves asymptotic output tracking. A stable adaptive law is derived for parameter adaptation in the presence of parameter uncertainties. Closed-loop signal boundedness and asymptotic output tracking, despite the uncertainties in actuator failures and plant parameters, are ensured analytically and verified by simulation results     

传感器实时动态补偿方法与误差分析

为了改善传感器动态特性,用零极点相消的补偿原理拓宽传感器系统的工作频带.研究了极点建模误差对传感器补偿效果的影响.分析一阶系统、二阶系统的极点建模误差与工作频带拓宽之间的关系,给出相应的关系图.得出结论:一阶系统,补偿效果只与建模误差有关,补偿效果较明显;二阶系统,补偿效果由误差与阻尼比决定,阻尼比越大,要求其极点实部精度越高,而其虚部精度要求越小,且阻尼比小于0.1时,其实部误差可以忽略不计,仿真结果与理论一致.定量分析补偿后噪声的放大程度与工作频带拓宽之间的关系,为实时补偿提供依据.并在数字信号处理器(DSP)中实现实时补偿系统,实时观察输出结果,验证了该系统的稳定性和可行性.     

Real-time design of an adaptive nonlinear predictive controller

Based on real-time identification and using the concept of NARX (Nonlinear AutoRegressive with exogenous inputs) models, a new adaptive nonlinear predictive controller (ANPC) design is proposed. NARX models represent a natural way to describe the input-output relationship of severely nonlinear systems. From an initial batch of input-output data, a parsimonious NARX model is obtained using the Modified Gram-Schmidt (MGS) orthogonalization algorithm. Following this initial off-line identification and model reduction procedure, the control loop is closed. The ANPC directly uses the obtained structure and initial parameter estimates, which are updated each time step using recursive identification. The controller is designed similar to a typical linear predictive controller based on solving a nonlinear programming (NLP) problem. This paper shows how to solve this NLP problem on-line without the knowledge of the NARX model structure. The design is given for the multi-input multi-output (MIMO) case.     

Feedback based adaptive compensation of control system sensor uncertainties

In this paper, the problem of adaptively compensating sensor uncertainties is addressed in a feedback based framework. In this study, sensor characteristics are modeled as parametrizable uncertain functions and a compensator is constructed to adaptively cancel the effects of sensor uncertainties, to generate an adaptive estimate of the plant output. Such an estimated output is used for the feedback control law. Adaptive control schemes using a model reference approach with sensor uncertainty compensation are developed for LTI plants with either known or unknown plant dynamics. A new feedback controller structure is developed for the case when the plant dynamics is unknown, to handle the plant and sensor uncertainties. Simulation results are presented to show that the proposed adaptive sensor uncertainty compensation designs significantly improve system tracking performance.     

飞翼飞行器的操纵面故障自适应补偿控制

本文针对具有操纵面卡死、失效故障以及执行器饱和的飞翼飞行器纵向运动,考虑系统的预定动态性能,提出了一种自适应反步补偿跟踪控制方案.设计预定动态性能(prescribed performance bound,PPB)边界以保证系统的跟踪误差,采用二阶指令滤波器限制执行器的饱和,通过控制分配避免执行器故障后对横侧向运动的影响.所设计的自适应反步补偿跟踪控制律能够保证系统对参考信号的渐近跟踪.仿真结果表明了本文方法的有效性.     

Thermally adaptive response‐time compensation for LCDs

Abstract— This paper presents thermally adaptive driving (TAD) technology for response‐time compensation (RTC) of an LCD with an integrated sensor. The TAD system is comprised of an analog sensor, an analog sensor signal conditioning, and a digital feedback algorithm. The integrated thermal sensor provides accurate temperature measurement of the liquid‐crystal layer. The TAD controller has an eight‐step look‐up‐table (LUT) and compensates response time based on the panel temperature. The TAD system reduces response time by nearly 34% over the temperature range 0–60°C. This paper also presents a thermal sensor which has been integrated onto an LCD. The sensor uses metal (Mo/Al) film as a temperature detection layer, and its fabrication requires no manufacturing process changes. The sensor shows very good linearity, sensitivity, and reliability.     

利用免疫克隆粒子群混合算法实现自适应PMD补偿

提出了一种免疫克隆算法与粒子群优化（PSO）算法相结合的混和算法来进行函数优化,克服了PSO算法容易陷入局部极值的不足,通过免疫克隆算法的应用,提高了种群的多样性,增强了算法全局搜索的能力,提高了收敛速度和精度。仿真结果表明,该算法在搜索多维函数最优解中具有优良的性能。将该混和算法应用到光纤偏振模色散（PMD）补偿系统中,补偿后,眼图恢复效果很好,补偿系统的搜索时间最短可达71 ms,响应恢复小于20 ms,实现了对光纤通信系统的实时自适应PMD补偿。     

基于反步自适应控制的伺服系统齿隙补偿

齿隙是影响机电伺服系统动/静态性能的一个重要因素. 为了减小其不利影响, 该文以存在不确定参数的机电位置伺服系统为研究对象, 针对系统中存在的齿隙非线性, 应用反步积分方法, 通过逐步递推选择Lyapunov函数,设计了基于状态反馈的自适应控制器. 通过理论分析以及与传统PID控制的仿真结果比较表明, 该方案显著地降低了齿隙对伺服性能的影响, 提高了系统的跟踪精度和鲁棒性.