Modelling and Fast Terminal Sliding Mode Control for Mirror-based Pointing Systems

In this paper, we present a new discrete-time Fast Terminal Sliding Mode (FTSM) controller for mirror-based pointing systems. We first derive the decoupled model of those systems and then estimate the parameters using a nonlinear least-square identification method. Based on the derived model, we design a FTSM sliding manifold in the continuous domain. We then exploit the Euler discretization on the designed FTSM sliding surfaces to synthesize a discrete-time controller. Furthermore, we improve the transient dynamics of the sliding surface by adding a linear term. Finally, we prove the stability of the proposed controller based on the Sarpturk reaching condition. Extensive simulations, followed by comparisons with the Terminal Sliding Mode (TSM) and Model Predictive Control (MPC) have been carried out to evaluate the effectiveness of the proposed approach. A comparative study with data obtained from a real-time experiment was also conducted. The results indicate the advantage of the proposed method over the other techniques.Comment: In Proceedings of the 15th International Conference on Control, Automation, Robotics and Vision (ICARCV 2018

Comments on "Frequency Response of the Noise Conversion from Relative Intensity Noise to Phase Noise in the Photodetection of an Optical Pulse Train"

International audienceIt is shown that the results presented in the above letter, and attributed by the authors to amplitude-to-phase conversion in the photodetector, do not originate in the photodetector under test, due to the power dependence observed. More recent results show that conversion effects with the same size and frequency dependence are observed in passively mode-locked nonlinear polarization rotation mode-locked lasers

Effectiveness of Teaching About Preventing and Detecting Complications of Hand, Foot, and Mouth Disease at My Phuoc Hospital

Hand, foot, and mouth disease (HFMD) is an infectious illness that affects millions of people, especially children under five years of age. The social impact of severe HFMD to the health community, family members, and children is also of big concern. In the south of Vietnam, Binh Duong province is located in the area affected by HFMD. Unfortunately, caregivers have little knowledge to prevent and detect HFMD severity in children. The research question asked how effective teaching about HFMD was to improve knowledge of caregivers for detecting HFMD severity in children under five years of age at My Phuoc Hospital in Binh Duong Province, Vietnam. Therefore, the purpose of this quasi-experimental study was to determine the effectiveness of HFMD teaching to improve knowledge for preventing and detecting severe HFMD in children less than five years of age. In the analysis section, data were extracted from 52 caregivers caring for children under five years of age before and after a health education session. The results showed the intervention measures improved knowledge about HFMD in participants after the intervention. In the pretest, 34.6% caregiver had levels of poor and very poor understanding, 38.5% had moderate levels, and 26.9% had good and very good knowledge levels. This finding compared with 86.5% caregivers who achieved very good knowledge levels after intervention

Topological Lifshitz phase transition in effective model of QCD with chiral symmetry non-restoration

The topological Lifshitz phase transition is studied systematically within an effective model of QCD, in which the chiral symmetry, broken at zero temperature, is not restored at high temperature and/or baryon chemical potential. It is found that during phase transition the quark system undergoes a first-order transition from low density fully-gapped state to high density state with Fermi sphere which is protected by momentum-space topology. The Lifshitz phase diagram in the plane of temperature and baryon chemical potential is established. The critical behaviors of various equations of state are determined.Comment: 8 pages, 10 figure

Automatic Crack Detection in Built Infrastructure Using Unmanned Aerial Vehicles

This paper addresses the problem of crack detection which is essential for health monitoring of built infrastructure. Our approach includes two stages, data collection using unmanned aerial vehicles (UAVs) and crack detection using histogram analysis. For the data collection, a 3D model of the structure is first created by using laser scanners. Based on the model, geometric properties are extracted to generate way points necessary for navigating the UAV to take images of the structure. Then, our next step is to stick together those obtained images from the overlapped field of view. The resulting image is then clustered by histogram analysis and peak detection. Potential cracks are finally identified by using locally adaptive thresholds. The whole process is automatically carried out so that the inspection time is significantly improved while safety hazards can be minimised. A prototypical system has been developed for evaluation and experimental results are included.Comment: In proceeding of The 34th International Symposium on Automation and Robotics in Construction (ISARC), pp. 823-829, Taipei, Taiwan, 201

The influence of knowledge sharing behavior and transactive memory systems on innovative work behavior: A conceptual model

© 2017 IEEE. Although knowledge sharing (KS), the key to creativity and innovation, are increasingly common in organisations, research on the relationship between knowledge sharing behaviour (KSB) and transactive memory system (TMS) and its effect on innovative work behaviour (IWB) is relatively rare. Prior studies have reported that KS influences IWB in organisations. However, the effect of KSB on IWB and the join influence between TMS on KS and IWB have not been adequately investigated in past research. Therefore, the goal of this research-in-progress is to propose a conceptual model comprising three construct domains including KSB, TMS quality and IWB to examine the impact of the KS practices of employees on their IWB in organisations. We advance to conduct a survey to examine our discussion of the proposed conceptual model. It is expected that this research will contribute to the deeper understanding of the effects of KSB and TMS on IBW within organisation. Implications and future research are also proposed

Adaptive twisting sliding mode control for quadrotor unmanned aerial vehicles

© 2017 IEEE. This work addresses the problem of robust attitude control of quadcopters. First, the mathematical model of the quadcopter is derived considering factors such as nonlinearity, external disturbances, uncertain dynamics and strong coupling. An adaptive twisting sliding mode control algorithm is then developed with the objective of controlling the quadcopter to track desired attitudes under various conditions. For this, the twisting sliding mode control law is modified with a proposed gain adaptation scheme to improve the control transient and tracking performance. Extensive simulation studies and comparisons with experimental data have been carried out for a Solo quadcopter. The results show that the proposed control scheme can achieve strong robustness against disturbances while is adaptable to parametric variations

Sensing Data Fusion for Enhanced Indoor Air Quality Monitoring

Multisensor fusion of air pollutant data in smart buildings remains an important input to address the well-being and comfort perceived by their inhabitants. An integrated sensing system is part of a smart building where real-time indoor air quality data are monitored round the clock using sensors and operating in the Internet-of-Things (IoT) environment. In this work, we propose an air quality management system merging indoor air quality index (IAQI) and humidex into an enhanced indoor air quality index (EIAQI) by using sensor data on a real-time basis. Here, indoor air pollutant levels are measured by a network of waspmote sensors while IAQI and humidex data are fused together using an extended fractional-order Kalman filter (EFKF). According to the obtained EIAQI, overall air quality alerts are provided in a timely fashion for accurate prediction with enhanced performance against measurement noise and nonlinearity. The estimation scheme is implemented by using the fractional-order modeling and control (FOMCON) toolbox. A case study is analysed to prove the effectiveness and validity of the proposed approach.Comment: Published in IEEE Sensors Journal (Early Access