Evolutionary Controller Design for Area Search using Multiple UAVs with Minimum Altitude Maneuver

2011 ◽  
Author(s):  
Soohun Oh ◽  
Jinyoung Suk
Keyword(s):  
Controller Design ◽  
Multiple Uavs

scholarly journals Adaptive Robust Trajectory Tracking Control of Multiple Quad-Rotor UAVs with Parametric Uncertainties and Disturbances

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2401
Author(s):  
Yasir Mehmood ◽  
Jawad Aslam ◽  
Nasim Ullah ◽  
Md. Shahariar Chowdhury ◽  
Kuaanan Techato ◽  
...  
Keyword(s):  
Trajectory Tracking ◽  
Control Method ◽  
Controller Design ◽  
Sliding Mode ◽  
Parametric Uncertainties ◽  
Trajectory Tracking Control ◽  
Multiple Uavs ◽  
Control Schemes ◽  
Robust Adaptive ◽  
The Stability

Recently, formation flying of multiple unmanned aerial vehicles (UAVs) found numerous applications in various areas such as surveillance, industrial automation and disaster management. The accuracy and reliability for performing group tasks by multiple UAVs is highly dependent on the applied control strategy. The formation and trajectories of multiple UAVs are governed by two separate controllers, namely formation and trajectory tracking controllers respectively. In presence of environmental effects, disturbances due to wind and parametric uncertainties, the controller design process is a challenging task. This article proposes a robust adaptive formation and trajectory tacking control of multiple quad-rotor UAVs using super twisting sliding mode control method. In the proposed design, Lyapunov function-based adaptive disturbance estimators are used to compensate for the effects of external disturbances and parametric uncertainties. The stability of the proposed controllers is guaranteed using Lyapunov theorems. Two variants of the control schemes, namely fixed gain super twisting SMC (STSMC) and adaptive super twisting SMC (ASTSMC) are tested using numerical simulations performed in MATLAB/Simulink. From the results presented, it is verified that in presence of disturbances, the proposed ASTSMC controller exhibits enhanced robustness as compared to the fixed gain STSMC.

Continuous Time Controller Design

IEE Review ◽  
1991 ◽  
Vol 37 (6) ◽  
pp. 228
Author(s):  
Stephen Barnett
Keyword(s):  
Continuous Time ◽  
Controller Design

Path Tracking Controller Design of Automatic Guided Vehicle Based on Four-Wheeled Omnidirectional Motion Model

2020 ◽  
Vol 17 (2) ◽  
pp. 7996-8010
Author(s):  
X. Wu ◽  
Y. Yang
Keyword(s):  
Control System ◽  
Fuzzy Controller ◽  
Controller Design ◽  
Threshold Value ◽  
Position Angle ◽  
Path Tracking ◽  
Global Coordinate System ◽  
Automatic Guided Vehicle ◽  
Input Variables ◽  
Industrial Pc

This paper presents a new design of omnidirectional automatic guided vehicle based on a hub motor, and proposes a joint controller for path tracking. The proposed controller includes two parts: a fuzzy controller and a multi-step predictive optimal controller. Firstly, based on various steering conditions, the kinematics model of the whole vehicle and the pose (position, angle) model in the global coordinate system are introduced. Secondly, based on the modeling, the joint controller is designed. Lateral deviation and course deviation are used as the input variables of the control system, and the threshold value is switched according to the value of the input variable to realise the correction of the large range of posture deviation. Finally, the joint controller is implemented by using the industrial PC and the self-developed control system based on the Freescale minimum system. Path tracking experiments were made under the straight and circular paths to test the ability of the joint controller for reducing the pose deviation. The experimental results show that the designed guided vehicle has excellent ability to path tracking, which meets the design goals.

Mode-Based Controller Design for Hammerstein Models Using Closed-Loop Tranjent Response Data

2016 ◽  
Vol 136 (5) ◽  
pp. 625-632
Author(s):  
Yoshihiro Matsui ◽  
Hideki Ayano ◽  
Shiro Masuda ◽  
Kazushi Nakano
Keyword(s):  
Closed Loop ◽  
Controller Design ◽  
Response Data ◽  
Hammerstein Models
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