Quadrotor UAV Control: Online Learning Approach

2011 ◽  
Author(s):  
Pong-in Pipatpaibul ◽  
P. R. Ouyang
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Iterative Learning Control ◽  
Iterative Learning ◽  
Search And Rescue ◽  
Learning Approach ◽  
Circular Trajectory ◽  
Quadrotor Uav ◽  
Aerial Vehicles ◽  
Simulation Results ◽  
Quadrotor Unmanned Aerial Vehicles

Quadrotor unmanned aerial vehicles (UAVs) are recognized to be capable of various tasks including search and rescue and surveillance for their agilities and small sizes. This paper proposes a simple and robust quadrotor controller utilizing online Iterative Learning Control (ILC) that is known to be useful for tasks performed repeatedly. The controller is used for trajectory tracking to perform a variety of manoeuvring such as take-off, landing, smooth translation, and circular trajectory motion. Different online ILCs are studied and simulation results prove the ability to gain full autonomy and perform successfully certain missions in the presence of considerably large disturbances.

scholarly journals Quadrotor UAV control : online learning approach

2021 ◽  
Author(s):  
Pong-In Pipatpaibul
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Iterative Learning Control ◽  
Convergence Rates ◽  
Learning Approach ◽  
Circular Trajectory ◽  
Quadrotor Uav ◽  
Simulation Results ◽  
Trajectory Tracking Controller ◽  
Gyroscopic Effects ◽  
Quadrotor Unmanned Aerial Vehicles

Quadrotor unmanned aerial vehicles (UAVs) are recognized to be capable of various tasks including search and surveillance for their agilities and small sizes. This thesis proposes a simple and robust trajectory tracking controller for a quadrotor UAV utilizing online Iterative Learning Control (ILC) that is known to be effective for tasks performed repeatedly. Based on a nonlinear model which considers basic aerogynamic and gyroscopic effects, the quadrotor UAV model is simulated to perform a variety of maneuvering such as take-off, landing, smooth translation and horizontal and spatial circular trajectory motions, PD online ILCs wirh switching gain (SPD ILCs) are studies, tested and compared. Simulation results prove the ability of the online ILCs to successfully perform certain missions in the presence of considerably large disturbances and SPD ILCs can obtain faster convergence rates.

scholarly journals Quadrotor UAV control : online learning approach

2021 ◽  
Author(s):  
Pong-In Pipatpaibul
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Iterative Learning Control ◽  
Convergence Rates ◽  
Learning Approach ◽  
Circular Trajectory ◽  
Quadrotor Uav ◽  
Simulation Results ◽  
Trajectory Tracking Controller ◽  
Gyroscopic Effects ◽  
Quadrotor Unmanned Aerial Vehicles

Quadrotor unmanned aerial vehicles (UAVs) are recognized to be capable of various tasks including search and surveillance for their agilities and small sizes. This thesis proposes a simple and robust trajectory tracking controller for a quadrotor UAV utilizing online Iterative Learning Control (ILC) that is known to be effective for tasks performed repeatedly. Based on a nonlinear model which considers basic aerogynamic and gyroscopic effects, the quadrotor UAV model is simulated to perform a variety of maneuvering such as take-off, landing, smooth translation and horizontal and spatial circular trajectory motions, PD online ILCs wirh switching gain (SPD ILCs) are studies, tested and compared. Simulation results prove the ability of the online ILCs to successfully perform certain missions in the presence of considerably large disturbances and SPD ILCs can obtain faster convergence rates.

A Two-Step Optimization-Based Iterative Learning Control for Quadrotor Unmanned Aerial Vehicles

2021 ◽  
Vol 143 (7) ◽  
Author(s):  
Revant Adlakha ◽  
Minghui Zheng
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Design Problem ◽  
Iterative Learning Control ◽  
Design Method ◽  
Learning Control ◽  
Iterative Learning ◽  
Learning Performance ◽  
Aerial Vehicles ◽  
Quadrotor Unmanned Aerial Vehicles ◽  
Optimization Based Design

Abstract This paper presents a two-step optimization-based design method for iterative learning control and applies it onto the quadrotor unmanned aerial vehicles (UAVs) trajectory tracking problem. Iterative learning control aims to improve the tracking performance through learning from errors over iterations in repetitively operated systems. The tracking errors from previous iterations are injected into a learning filter and a robust filter to generate the learning signal. The design of the two filters usually involves nontrivial tuning work. This paper presents a new two-optimization design method for the iterative learning control, which is easy to obtain and implement. In particular, the learning filter design problem is transferred into a feedback controller design problem for a purposely constructed system, which is solved based on H-infinity optimal control theory thereafter. The robust filter is then obtained by solving an additional optimization to guarantee the learning convergence. Through the proposed design method, the learning performance is optimized and the system's stability is guaranteed. The proposed two-step optimization-based design method and the regarding iterative learning control algorithm are validated by both numerical and experimental studies.

scholarly journals Application of Online Iterative Learning Tracking Control for Quadrotor UAVs

ISRN Robotics ◽  
2013 ◽  
Vol 2013 ◽  
pp. 1-20 ◽  
Author(s):  
Pong-in Pipatpaibul ◽  
P. R. Ouyang
Keyword(s):  
Tracking Control ◽  
Iterative Learning Control ◽  
Convergence Rates ◽  
Iterative Learning ◽  
Three Dimensions ◽  
Circular Trajectory ◽  
Tracking Errors ◽  
Trajectory Tracking Control ◽  
Monitoring And Surveillance ◽  
Quadrotor Unmanned Aerial Vehicles

Quadrotor unmanned aerial vehicles (UAVs) have attracted considerable interest for various applications including search and rescue, environmental monitoring, and surveillance because of their agilities and small sizes. This paper proposes trajectory tracking control of UAVs utilizing online iterative learning control (ILC) methods that are known to be powerful for tasks performed repeatedly. PD online ILC and switching gain PD online ILC are used to perform a variety of manoeuvring such as take-off, smooth translation, and various circular trajectory motions in two and three dimensions. Simulation results prove the ability and effectiveness of the online ILCs to perform successfully certain missions in the presence of disturbances and uncertainties. It also demonstrates that the switching gain PD ILC is much effective than the PD online ILC in terms of fast convergence rates and smaller tracking errors.

scholarly journals Simulation and Analysis of a Quadrotor UAV while Landing.

2020 ◽  
Vol 8 (6) ◽  
pp. 672-680
Keyword(s):  
Unmanned Aerial Vehicles ◽  
High Stress ◽  
Simulation Method ◽  
Flight Period ◽  
High Stress Concentration ◽  
Quadrotor Uav ◽  
Unmanned Air Vehicle ◽  
Aerial Vehicles ◽  
Air Vehicle ◽  
Quadrotor Unmanned Aerial Vehicles

Unmanned aerial vehicles are widely used in military and civilian fields in recent years. Quadrotor Unmanned Aerial Vehicles (UAV) have high advantage among other UAV’s, in different categories, due to their ability to hover, and Vertical Take-Off and Landing (VTOL) capability. The mathematical simulation method can be adopted for analysis of UAV. The simulation method can reduce the flight period, cost and risk and improve its performance while Vertical take-off and landing (VTOL). While landing of UAV, the kinetic energy of vehicle is absorbed by UAV frame resulting in high stress concentration. The stresses are also produced in other parts of the UAV. The effect of the landing loads and stresses on the airframe of the quadrotor unmanned air vehicle must be completely understood and the UAV must be designed accordingly in order not to damage during landing.These stresses can be analyzed by simulation method to ensure the sustainability of UAV structure. This work includes structural and frequency analysis for Quadrotor UAV chassis.

A method for autonomous collision-free navigation of a quadrotor UAV in unknown tunnel-like environments

Robotica ◽  
2021 ◽  
pp. 1-27
Author(s):  
Taha Elmokadem ◽  
Andrey V. Savkin
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Autonomous Underwater Vehicles ◽  
Three Dimensional ◽  
Underwater Vehicles ◽  
Practical Implementation ◽  
Challenging Problem ◽  
Quadrotor Uav ◽  
Navigation Algorithm ◽  
Aerial Vehicles ◽  
Quadrotor Uavs

Abstract Unmanned aerial vehicles (UAVs) have become essential tools for exploring, mapping and inspection of unknown three-dimensional (3D) tunnel-like environments which is a very challenging problem. A computationally light navigation algorithm is developed in this paper for quadrotor UAVs to autonomously guide the vehicle through such environments. It uses sensors observations to safely guide the UAV along the tunnel axis while avoiding collisions with its walls. The approach is evaluated using several computer simulations with realistic sensing models and practical implementation with a quadrotor UAV. The proposed method is also applicable to other UAV types and autonomous underwater vehicles.

Intelligent cooperative collision avoidance via fuzzy potential fields

Robotica ◽  
2021 ◽  
pp. 1-20
Author(s):  
Daegyun Choi ◽  
Anirudh Chhabra ◽  
Donghoon Kim
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Collision Avoidance ◽  
Fuzzy Inference ◽  
Potential Fields ◽  
Rule Base ◽  
Local Minima ◽  
Inference System ◽  
Aerial Vehicles ◽  
Different Shapes ◽  
Simulation Results

Summary This paper proposes an intelligent cooperative collision avoidance approach combining the enhanced potential field (EPF) with a fuzzy inference system (FIS) to resolve local minima and goal non-reachable with obstacles nearby issues and provide a near-optimal collision-free trajectory. A genetic algorithm is utilized to optimize parameters of membership function and rule base of the FISs. This work uses a single scenario containing all issues and interactions among unmanned aerial vehicles (UAVs) for training. For validating the performance, two scenarios containing obstacles with different shapes and several UAVs in small airspace are considered. Multiple simulation results show that the proposed approach outperforms the conventional EPF approach statistically.

scholarly journals Design and Fabrication of Voice Controlled Unmanned Aerial Vehicle

2016 ◽  
Vol 5 (3) ◽  
pp. 205
Author(s):  
S. Sakthi Anand ◽  
R. Mathiyazaghan
Keyword(s):  
Control System ◽  
Unmanned Aerial Vehicles ◽  
Unmanned Aerial Vehicle ◽  
Voice Recognition ◽  
Search And Rescue ◽  
Voice Input ◽  
Recognition Process ◽  
Aerial Vehicles ◽  
Aerial Vehicle ◽  
The Voice

<p class="Default">Unmanned Aerial Vehicles have gained well known attention in recent years for a numerous applications such as military, civilian surveillance operations as well as search and rescue missions. The UAVs are not controlled by professional pilots and users have less aviation experience. Therefore it seems to be purposeful to simplify the process of aircraft controlling. The objective is to design, fabricate and implement an unmanned aerial vehicle which is controlled by means of voice recognition. In the proposed system, voice commands are given to the quadcopter to control it autonomously. This system is navigated by the voice input. The control system responds to the voice input by voice recognition process and corresponding algorithms make the motors to run at specified speeds which controls the direction of the quadcopter.</p>

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