Development of active matrix LCD for use in high‐resolution adaptive headlights

Conventional adaptive driving beam headlamps are limited in achieving still higher quantities of switchable pixels by the number of LEDs and movable elements needed. In this paper, it is shown that by integrating an active matrix liquid crystal display module, it is possible to realize fully adaptive high‐resolution headlights without mechanical elements and a finite number of LED with 30 k switchable pixels.     

Tri‐band composite cylindrical dielectric resonator antenna with hybrid mode excitation and cross‐polarization suppression

This communication investigates composite cylindrical dielectric resonator antenna (CDRA) for various wireless applications. Three important features of proposed antenna design are (i) realization of two different hybrid modes, that is, HEM_11δ and HEM_12δ mode in CDRA with the help of modified annular ring printed line (work as both magnetic dipole and electric dipole), both the hybrid modes support broadside radiation characteristics (ii) suppression of HEM_21δ mode, in order to reduce the cross‐polarization level in H‐plane of other hybrid modes (HEM_11δ and HEM_12δ mode) by an amount of 8‐10 dB (iii) creation of triple‐band attribute using the concept of composite antenna. The proposed antenna design has been fabricated and practically tested. Simulated outcomes show good agreement with measured outcomes. It works in three frequency bands, that is, 2.25‐2.79 GHz, 3.1‐4.0 GHz, and 5.05‐5.6 GHz. The designed antenna structure is appropriate for WLAN and WiMAX applications.     

Robust Output Feedback Controller Design for Time‐Delayed Teleoperation: Experimental Results

In this paper, a robust output feedback control strategy is proposed for a nonlinear teleoperation system which can deal with stability as well as transparency despite the variable time‐delay and uncertain dynamics. The proposed approach is composed of two steps. First, local Lyapunov based adaptive controllers are applied to both master and slave sides in order to suppress the nonlinearities in the system dynamics. Afterwards, a new observer‐based controller scheme is proposed to achieve stability and performance (transparency) of the teleoperation system. Using the Lyapunov techniques, stability and performance objectives are cast as some linear matrix inequality (LMI) feasibility conditions. To evaluate the performance of the proposed controller, a set of simulations and experiments are performed. Through simulation results, it is demonstrated that the proposed approach significantly outperforms the existing methodologies reported in the literature.     

End‐Point Regulation and Vibration Suppression of a Flexible Robotic Manipulator

In this paper, end‐point regulation and vibration suppression are investigated for a flexible robotic manipulator subject to the external disturbances. The dynamics of the flexible robotic manipulator is represented by one partial differential equation (PDE) and five ordinary differential equations (ODEs). Based on the Lyapunov's direct method, boundary control is developed to drive the manipulator to the desired set‐point and simultaneously suppress the vibrations of the flexible manipulator. Considering the unknown spatiotemporally varying disturbance, uniform boundedness of the closed‐loop system is achieved. The control performance of the closed‐loop system is guaranteed by suitably choosing the design parameters. Simulations are provided to illustrate the effectiveness of the proposed control.     

Stable indirect adaptive interval type-2 fuzzy sliding-based control and synchronization of two different chaotic systems

An indirect approach to adaptive interval type-2 fuzzy sliding mode control is proposed for the stable synchronization of two different chaotic nonlinear systems with different initial conditions under the presence of uncertainties involving process noises and external disturbances. The indirect model-based approach to adaptation is promoted here as a more suitable strategy for the fast changes that occurs in chaotic systems. In other words, the usual direct adaptive strategies may be too slow to respond to the inherently fast changing dynamics of chaotic systems. Using Lyapunov analysis, the sliding mode approach illustrates the asymptotic convergence of synchronization error to zero as well as good robustness against external disturbances. The interval type-2 structure aims to remedy the undesirable chattering phenomenon that is common in most conventional sliding mode control applications. It also provides a more effective equivalent model in the indirect approach, which leads to improved handling of the chaotic variations and uncertainties. Two numerical pairs of chaotic systems, i.e. the Lorenz and Chen’s systems and the Rössler system and modified Chua’s circuit are considered. In particular, in comparison with its type-1 fuzzy counterpart, the control effort is reduced by an average of 26.25% and 17.4% for the synchronization of the two corresponding systems, respectively. Furthermore, the integral of squared error is also improved by an average of 27.2% and 25.33%. This is while convergence time is reduced to less than 0.5 s and 1.5 s.     

Prediction of landslide displacement with controlling factors using extreme learning adaptive neuro-fuzzy inference system (ELANFIS)

Landslide is a major geo-environmental hazard which imparts serious threat to lives and properties. The slope failures are due to adverse inherent geological conditions triggered by an external factor. This paper proposes a new method for the prediction of displacement of step-like landslides, by accounting the controlling factors, using recently proposed extreme learning adaptive neuro-fuzzy inference system (ELANFIS) with empirical mode decomposition (EMD) technique. ELANFIS reduces the computational complexity of conventional ANFIS by incorporating the theoretical idea of extreme learning machines (ELM). The rainfall data and reservoir level elevation data are also integrated into the study. The nonlinear original landslide displacement series, rainfall data, and reservoir level elevation data are first converted into a limited number of intrinsic mode functions (IMF) and one residue. Then decomposed displacement data are predicted by using appropriate ELANFIS model. Final prediction is obtained by the summation of outputs of all ELANFIS sub models. The performance of proposed the technique is tested for the prediction Baishuihe and Shiliushubao landslides. The results show that ELANFIS with EMD model outperforms other methods in terms of generalization performance.     

基于Arduino控制板的数据采集智能小车的控制系统设计与实现

为实现具有环境数据采集功能的智能小车控制,设计并实现了基于Ardu-no控制板的控制系统。选用Arduino Mega 2560控制板为控制核心,搭配DS1-B20温度传感器、DHT11湿度传感器、MQ-2烟雾传感器、超声波测距传感器、E-P8266Wifi通讯模块组成硬件系统;采用PWM脉宽调制技术调节小车行进速度,PID算法调节小车的行进方向。调试结果表明,小车具有基于Wifi的无线遥控操作功能,能够对起所处环境中的温度、湿度、烟雾数据进行实时测量、采集和传输,并能自动检测前方障碍物。证明了基于Arduino控制板的控制系统在环境数据采集智能小车中应用的可行性。     

基于矩阵分解的个性化推荐系统研究

随着社交网络的快速发展,用户在使用社交应用时会产生大量有价值的数据。通过对社交网络进行数据挖掘,发现隐藏在数据中关联用户与物品之间的偏好关系。然后对用户建模分析,选择合适的推荐引擎进行个性化物品推荐,这是一个非常有价值的研究方向。该文重点研究矩阵分解算法对处理大规模用户与物品评分矩阵的推荐效果,为了提高推荐的准确度展开了对用户社交关系和隐性反馈的研究,在组合预测模型中加入社交关系、人口统计学信息配置项、用户的消费记录等隐因子项,通过实验验证了扩展之后的混合预测模型在RMSE值上比SVD算法降低了0.259 475,在推荐性能有较大幅度的提高。     

基于行人运动模态辨识的室内外无缝导航航向算法研究

目前行人导航航向解算算法均基于导航传感器在行人身体上的固定安装模式,或者依赖其他射频信息辅助修正陀螺航向,这极大约束了导航传感器的适用条件.为此,利用陀螺对低频噪声的敏感性及加速度计低频的稳定性,提出了解决行人手持手机稳态查看与非稳态摇摆的运动模态辨识算法和基于时域互补滤波器实现姿态的最优融合方法;研究了改进型互补滤波以消除行人的运动加速度对姿态解算的干扰误差,提高了载体姿态的测量精度;此外,利用磁传感器标定后的数据设计了自适应卡尔曼滤波算法,抑制了航向角的误差发散.经实际数据测试验证,室内外行人手持稳态与非稳态下的航向角测量精度提高了80%,同时大大提高了导航传感器的适用性与便携性,满足实际工程的使用需求.     

基于无线传感器网络的坡面异常信号检测方法研究

提出了一种适用于硬件资源受限的传感器节点的坡面异常信号检测方法,数据的采集和异常检测在节点前端完成,能提高监测实时性,降低数据传输的通信能耗.传感器节点采集坡面加速度数据,通过对训练数据进行经验模态分解得到本征模函数的上包络,并对该包络数据进行高斯建模自适应学习确定检测阈值.对监测数据经验模态分解得到上包络数据,运用3α原则与检测阈值进行比较实现异常信号判别.通过算法仿真和实际部署测试得到该方法检测精度为98%,具有一定的实用价值.