1.Introduction 2.Fundamental Modeling and Control of Unmanned Small-Scale and Mi-niature Helicopters 3.Autonomous Control of a Mini Quadrotor Vehicle Using LQG Controllers 4.Modeling and Control of an Autonomous Quad-Tilt-Wing (QTW) UAV 5.Linearlization and Identification of Helicopter Model for Hierarchical Control Design 6.Analysis of the Autorotation Maneuver in Small-Scale Helicopters and Application for Emergency Landing 7.Autonomous Acrobatic Flight based on Feedforward Sequence Control for Small Unmanned Helicopter 8.Mathematical Modeling and Nonlinear Control of VTOL Aerial Vehicles 9.Formation Flight Control of Multiple Autonomous Helicopters Using Predictive Control 10.Guidance and Navigation Systems for Small Aerial Robots 11.Design and Implementation of a Low-Cost Attitude Quaternion Sensor 12.Vision-Based Navigation and Visual Servoing of Mini Flying Machines 13.Autonomous Indoor Flight and Precise Auto-Landing Using Infrared and Ultrasonic Sensors

Autonomous flying robots : unmanned aerial vehicles and micro aerial vehicles

Observer-based fixed-time continuous nonsingular terminal sliding mode control of quadrotor aircraft under uncertainties and disturbances for robust trajectory tracking: theory and experiment

A mathematical model of a class of underactuated mechanical systems is analyzed and a nonlinear control scheme based on partial feedback linearization is presented.In the underactuated mechanical system,the dynamics corresponding to the active degrees of freedom are linearized based on the exact linearization design technique,while the dynamics corresponding to the passive degrees are taken as the internal dynamics of the system.The trajectory tracking control of the linearized system is studied by choosing the active degrees as the system outputs.The analysis of the system internal dynamics shows that the stability of the zero dynamics guarantees the stability of the control system.Finally,simulation is done for the anti-swing control of an overhead crane system.

Nonlinear Control for a Class of Underactuated Mechanical Systems

Quadcopter unmanned aerial vehicles (UAVs) systems are receiving remarkable attention from researchers due to their daily use in numerous applications, particularly at the current time where UAVs are playing a significant role in combating the COVID-19 pandemic. This paper is concerned with the problem of UAV navigation and control in the presence of uncertainty and external disturbances. It addresses this issue by proposing an improved adaptive sliding mode control (IASMC). Improved control law generates an adaptive switching gain achieving fast adaptation and robustness against both parameter uncertainties and external disturbances. Simultaneously, the control law allows for maintaining robust trajectory tracking with chattering attenuation. The performance of the proposed IASMC controller has been evaluated using a Matlab/Simulink platform. The obtained simulation results showed that the proposed IASMC control scheme as an inner loop controller is robust when dealing with uncertainties and can effectively track the desired trajectories while significantly attenuating the well-known chattering introduced by the SMC controller.

An Improved Design of an Adaptive Sliding Mode Controller for Chattering Attenuation and Trajectory Tracking of the Quadcopter UAV

This paper investigates an Adaptive Fuzzy Gains-Scheduling Integral Sliding Mode Controller (AFGS-ISMC) design approach to deal with the attitude and altitude stabilization problem of an Unmanned Aerial Vehicles (UAV) precisely of a quadrotor. The Integral Sliding Mode Control (ISMC) seems to be an adequate control tool to remedy this problem. The selection of the controller parameters is done most of the time using repetitive trials-errors based methods. This method is not completely reliable and becomes a time-consuming and difficult task. Here we propose the tuning and selection of all ISMC gains adaptively according to a fuzzy supervisor. The sliding surface and its differential are declared as Fuzzy Logic Supervisor (FLS) inputs and the integral sliding mode control gains as the FLS outputs. The proposed fuzzy-based supervision mechanisms modify all ISMC gains to be time-varying and further enhance the performance and robustness of the obtained adaptive nonlinear controllers against uncertainties and external disturbances. The proposed adaptive fuzzy technique increases the effectiveness of the ISMC structure compared to the classical SMC strategy and excludes the dull and repetitive trials-errors process for its design and tuning. Various simulations have been carried out and followed by comparison and discussion of the results in order to prove the superiority of the suggested fuzzy gains-scheduled ISMC approach for the quadrotor attitude and altitude flight stabilization.

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Fuzzy Gains-Scheduling of an Integral Sliding Mode Controller for a Quadrotor Unmanned Aerial Vehicle

In this paper, a nonlinear model for a Quadrotor Vertical Take-Off and Landing (VTOL) type of Unmanned Aerial Vehicles (UAVs) is firstly established for the attitude and position control. All aerodynamic forces and moments of the studied Quadrotor UAV are described within an inertial frame. Such a dynamical model is obtained using the Newton-Euler formalism. Secondly, an improved nonlinear Sliding Mode Control (SMC) approach is designed for this aircraft in order to stabilize its vertical flight dynamics, while avoiding the classical chattering problem. Since chattering phenomena is the most problematic issue in the sliding mode control applications, a Quasi Sliding Mode Control (QSMC) technique is used as a solution for the chattering avoidance in Quadrotor dynamics control. Demonstrative simulations are carried out in order to show the effectiveness of the proposed QSMC approach for the stabilization and tracking of various desired trajectories.

Chattering Free Sliding Mode Controller Design for a Quadrotor Unmanned Aerial Vehicle

Vision-based autonomous robot field is becoming rapidly popular, according to the Artificial Intelligence revolution. The proposed system is a composition of Unmanned Ground Vehicle vision-based target tracking robot. Target tracking is useful in multiple real-life issues such as the assistance and security fields. Acquitted visual input processing is applied through using OpenCV library. The object detection process is done based on a pre-built deep learning object detection model. YOLOv3-tiny is used to detect objects, which is a light computation-cost version comparing to the original YOLOv3 model and the other complex deep-learning networks. Object to track is specified to be a human only. The target tracking algorithm is based on a sequence of mathematical equations with Region of Interest and stream’s frame coefficients. coefficients refer to the values of locations according to x-axis and y-axis of the frame. A simple mathematical technique is used for the delayed feedback issue. Ultra-sound technique is used for collision avoidance. The locomotion of UGV is based on transmitted commands from algorithm to the motors through local network connection. The results show an autonomous behavior, streamlined and accurate locomotion of tracking.

Nour Ben Ammar

Papers

Fuzzy Gains-Scheduling of an Integral Sliding Mode Controller for a Quadrotor Unmanned Aerial Vehicle

Chattering Free Sliding Mode Controller Design for a Quadrotor Unmanned Aerial Vehicle

Real-Time Visual Target Detection and Tracking Via Unmanned Ground Vehicle