Adaptive Super-twisting Second-order Sliding Mode for Attitude Control of Quadcopter UAVs

This work addresses the modelling and control aspects for quadcopter or drone unmanned aerial vehicles (UAVs). First, the mathematical model of the drone is derived by identifying significant parameters and the negligible ones are treated as disturbances. The control design begins with the switching surface selection, then, an Adaptive Super Twisting Sliding Mode (ASTSM) Control algorithm is applied to adjust attitudes of the quadcopter under harsh conditions such as nonlinear, strong coupling, high uncertainties and disturbances. Simulation results show that the proposed controller can achieve robust operation with disturbance rejection, parametric variation adaptation as well as chattering attenuation. Comparisons with some commonly used and advanced controllers in a quadcopter model show advantages of the proposed control scheme

Fast terminal sliding mode control for gantry cranes

Cranes remain a vital tool for the construction of infrastructure such as buildings, bridges, etc. Recently, there has been renewed interest in crane automation in dealing with concerns on safety and possible performance degradation due to system uncertainties and disturbances. One potential solution to the problem is the use of robust techniques based on the Sliding Mode Control (SMC) methodology. Much research has been conducted to design controllers based on linear sliding surfaces, aiming at achieving the desired control performance in finite time. In this context, this paper proposes a control method, based on the Fast Terminal Sliding Mode (FTSM), to guarantee finite-time stability of the crane. To do that, we have derived a mathematical model of the crane using Lagrangian formulation with uncertainties as bounding functions. Then, sliding surfaces based on the hierarchical sliding mode are defined, and a control law is derived using the Lyapunov stability theory. The hierarchical sliding surfaces consist of two layers. The first layer include sliding functions based on FTSM to enable faster convergence of the system to equilibrium. This can have advantages in high precision tracking applications. In the second-layer, the sliding surface is designed from the linear combination of the first layer sliding functions. Also, we have given a proof of the stability of the system in finite time. Extensive simulation results show the proposed controller based on FTSM can achieve higher performance in stabilizing the swinging load of a gantry crane. Laboratorial experiments have been conducted to verify the obtained results in terms of the superior convergence time and improved performance over conventional SMC

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

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

Adaptive second-order sliding mode control of UAVs for civil applications

Quadcopters, as unmanned aerial vehicles (UAVs), have great potential in civil applications such as surveying, building monitoring, and infrastructure condition assessment. Quadcopters, however, are relatively sensitive to noises and disturbances so that their performance may be quickly downgraded in the case of inadequate control, system uncertainties and/or external disturbances. In this study, we deal with the quadrotor low-level control by proposing a robust scheme named the adaptive second-order quasi-continuous sliding mode control (adaptive 2-QCSM). The ultimate objective is for robust attitude control of the UAV in monitoring and inspection of built infrastructure. First, the mathematical model of the quadcopter is derived considering nonlinearity, strong coupling, uncertain dynamics and external disturbances. The control design includes the selection of the sliding manifold and the development of quasi-continuous second-order sliding mode controller with an adaptive gain. Stability of the overall control system is analysed by using a global Lyapunov function for convergence of both the sliding dynamics and adaptation scheme. Extensive simulations have been carried out for evaluation. Results show that the proposed controller can achieve robustness against disturbances or parameter variations and has better tracking performance in comparison with experimental responses of a UAV in a real-time monitoring task

Angle-Encoded Swarm Optimization for UAV Formation Path Planning

© 2018 IEEE. This paper presents a novel and feasible path planning technique for a group of unmanned aerial vehicles (DAVs) conducting surface inspection of infrastructure. The ultimate goal is to minimise the travel distance of DAVs while simultaneously avoid obstacles, and maintain altitude constraints as well as the shape of the UAV formation. A multiple-objective optimisation algorithm, called the Angle-encoded Particle Swarm Optimization (θ- PSO) algorithm, is proposed to accelerate the swarm convergence with angular velocity and position being used for the location of particles. The whole formation is modelled as a virtual rigid body and controlled to maintain a desired geometric shape among the paths created while the centroid of the group follows a pre-determined trajectory. Based on the testbed of 3DR Solo drones equipped with a proprietary Mission Planner, and the Internet-of- Things (loT) for multi-directional transmission and reception of data between the DAV s, extensive experiments have been conducted for triangular formation maintenance along a monorail bridge. The results obtained confirm the feasibility and effectiveness of the proposed approach

Detection and monitoring of cancers with biosensors in Vietnam

Biosensors are able to provide fast, accurate and reliable detec-tions and monitoring of cancer cells, as well as to determine the effectiveness of anticancer chemotherapy agents in cancer treatments. These have attracted a great attention of research communities, especially in the capabilities of detecting the path-ogens, viruses and cancer cells in narrow scale that the conven-tional apparatus and techniques do not have. This paper pre-sents technologies and applications of biosensors for detections of cancer cells and related diseases, with the focus on the cur-rent research and technology development about biosensors in Vietnam, a typical developing country with a very high number of patients diagnosed with cancers in recent years, but having a very low cancer survival rate. The role of biosensors in early detections of diseases, cancer screening, diagnosis and treat-ment, is more and more important; especially it is estimated that by 2020, 60-70% new cases of cancers and nearly 70% of cancer deaths will be in economically disadvantaged countries. The paper is also aimed to open channels for the potential R&D collaborations with partners in Vietnam in the areas of innovative design and development of biosensors in particular and medical technology devices in general

‘Blue boats’ and ‘reef robbers’: A new maritime security threat for the Asia Pacific?

© 2019 The Authors. Asia Pacific Viewpoint published by Victoria University of Wellington and John Wiley & Sons Australia, Ltd Vietnamese ‘blue boats’ – small wooden-hulled fishing boats – are now entering the territorial waters of Pacific Island countries and illegally catching high-value species found on remote coastal reefs. Crossing several international boundaries and traversing a distance of over 5000 km, these intrusions have alarmed Oceanic countries, including Australia. Lacking administrative capacity as well as jurisdictional authority to effectively control the vast stretches of island coastlines individually, governments and intergovernmental bodies in the region have called for strengthened coordination of surveillance efforts while also pressuring Vietnam diplomatically. This paper reviews these latest developments and is the first to provide a focused assessment of the issue. Through the lens of Copenhagen School of securitisation theory, we analyse responses of national and regional actors and their portrayal in online media to understand how blue boats are constructed as a security threat within a narrative of maritime, food and human security. Arguably, Australia together with the Forum Fisheries Agency, who advise on the governance of offshore tuna resources, have so far acted most decisively – in a way that might see them extend their strategic role in the region. We propose a comprehensive empirical research agenda to better understand and manage this nascent, flammable and largely unpredictable inter-regional phenomenon

Crack detection using enhanced thresholding on UAV based collected images

© 2018 Australasian Robotics and Automation Association. All rights reserved. This paper proposes a thresholding approach for crack detection in an unmanned aerial vehicle (UAV) based infrastructure inspection system. The proposed algorithm performs recursively on the intensity histogram of UAV-taken images to exploit their crack-pixels appearing at the low intensity interval. A quantified criterion of interclass contrast is proposed and employed as an object cost and stop condition for the recursive process. Experiments on different datasets show that our algorithm outperforms different segmentation approaches to accurately extract crack features of some commercial buildings

Monitoring System-Based Flying IoT in Public Health and Sports Using Ant-Enabled Energy-Aware Routing.

In recent decades, the Internet of flying networks has made significant progress. Several aerial vehicles communicate with one another to form flying ad hoc networks. Unmanned aerial vehicles perform a wide range of tasks that make life easier for humans. However, due to the high frequency of mobile flying vehicles, network problems such as packet loss, latency, and perhaps disrupted channel links arise, affecting data delivery. The use of UAV-enabled IoT in sports has changed the dynamics of tracking and working on player safety. WBAN can be merged with aerial vehicles to collect data regarding health and transfer it to a base station. Furthermore, the unbalanced energy usage of flying things will result in earlier mission failure and a rapid decline in network lifespan. This study describes the use of each UAV's residual energy level to ensure a high level of safety using an ant-based routing technique called AntHocNet. In health care, the use of IoT-assisted aerial vehicles would increase operational performance, surveillance, and automation optimization to provide a smart application of flying IoT. Apart from that, aerial vehicles can be used in remote communication for treatment, medical equipment distribution, and telementoring. While comparing routing algorithms, simulation findings indicate that the proposed ant-based routing protocol is optimal