In this paper, we propose a robust and finite-time control method, based on the terminal sliding mode (TSM), for a class of two-degree-of-freedom (2-DOF) underactuated electromechanical systems subject to bounded uncertainties and disturbances. First, the proposed Fast Terminal Sliding Mode (FTSM) method is presented. Then for the underactuated system control, hierarchical sliding surfaces are defined, consisting of two layers. In the first layer, separate FTSM sliding functions are selected for each state of the system. In the second layer, the system sliding manifold is a linear combination of the first layer sliding surfaces. A control law is derived and stability conditions of the nonlinear system are obtained by using the Lyapunov theory. To verify the effectiveness of our proposed method, the developed control technique is applied to control both the swinging load and the cart position of an underactuated gantry crane. Extensive simulation and real-time experiments demonstrate enhanced performance of the system and robustness against parametric variations in comparison to conventional TSM and sliding mode control.

-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.

This paper propose a novel objective function for the Dynamic Window Approach (DWA). We prove the convergence property of the objective function using Lyapunov stability criteria. Unlike previous studies which concentrate on implementing the DWA in nonholonomic vehicles, in this paper we have considered a quadrotor whose motion is limited to a fixed X-Y plane just like a holonomic vehicle. Simulation result shows our method guides the vehicle in avoiding obstacles and converge to the goal even in situations where conventional method failed.

This paper presents a system for tracking thermal targets using the RobotEye technology. The system comprises of a thermal came ra, a vision camera, a RobotEye, and a fiducial detection system. A marker is attached to a thermal target in order to estimate its position and orientation using the marker detection system. Then, an estimator predicts the future position of the target. A predictive control based on the Model Predictive Control (MPC) approach is then applied to generate commands for the eye to follow the target. Results of the tracking by MPC are also presented in this paper along with the performance evaluation of the whole system. The evaluation clearly shows the improve ment in the tracking performance by the proposed system.

Real-time vision systems are widely-used in construction and manufacturing industries. A significant proportion of computational resources of such systems is used in fiducial identification and localisation for motion tracking of moving targets. The requirement is to localise a pattern in an image captured by the vision system precisely, accurately, and with a minimum available computation time. As such, this paper presents a class of patterns and, accordingly, proposes an algorithm to fulfil the requirement. Here, the patterns are designed using circular patches of concentric circles to increase the probability of detection and reduce cases of false detection. In the detection algorithm, the image captured by the vision system is first scaled down for computationally-effective processing. The scaled image is then separated by filtering only the colour components, which are made up of outer circular patches in the proposed pattern. A blob detection algorithm is then implemented for identifying inner circular patches. The inner circles are then localised in the image by using the colour information obtained. Finally, the localised pattern, along with the camera and distortion matrix of the vision system, is applied in a perspective-n-point solving algorithm to estimate the marker orientation and position in the global coordinate system. Our system shows significant enhancement in performance of fiducial detection and identification and achieves the required latency of less than ten milliseconds. Thus, it can be used for infrastructure monitoring in many applications that involve high-speed real-time vision systems.

In this paper, a new systematic approach for designing a self-tuning controller for an autonomous quadrotor robot is introduced.In order to design the self-tuning controller, first, a linearized dynamic model of a quadrotor about hovering positions is derived, and thenthe successive loop closure approach is applied to design the self-tuning PID controller of the attitude, altitude and velocity for the autonomous flying capability of the flying robot. In addition, nonlinearities of the design model are also imposed in the control loop by takinginto account the saturation of actuators. For the verification of the effectiveness of the proposed controller, various simulation studiesare carried out in terms of the accuracy and robustness.

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.

In this paper, we present a new discrete-time Fast Terminal Sliding Mode (FTSM) controller for mirrorbased 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.