scholarly journals Adaptive Visual Servoing for Obstacle Avoidance of Micro Unmanned Aerial Vehicle with Optical Flow and Switched System Model

Processes ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 2126
Author(s):  
Ming-Li Chiang ◽  
Shun-Hung Tsai ◽  
Cheng-Ming Huang ◽  
Kuang-Tin Tao
Keyword(s):  
Adaptive Control ◽  
Optical Flow ◽  
Obstacle Avoidance ◽  
Visual Servoing ◽  
Switching System ◽  
Flight Direction ◽  
Control Scheme ◽  
Flow Information ◽  
Aerial Vehicle ◽  
Switching Controller

A vision-based adaptive switching controller that uses optical flow information to avoid obstacles for micro unmanned aerial vehicles (MUAV) is proposed in this paper. To use the optical flow to indicate the distance between the MUAV and the environment, we propose an algorithm with multi-thread processing such that the optical flow information is obtained reliably and continuously in the entire camera field of view. The flying behavior of considered MUAV is regarded as a switching system when considering different flying modes during the mission of obstacle avoidance. By the required flight direction for obstacle avoidance specified by the detected optical flow, an adaptive control scheme is designed to track the required trajectory in switching modes. The simulation result shows the tracking performances of the adaptive control with the switching system. The experiment of the whole system is completed to verify the obstacle avoidance capability of our system.

scholarly journals Unmanned Aerial Vehicle Navigation Using Wide-Field Optical Flow and Inertial Sensors

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Matthew B. Rhudy ◽  
Yu Gu ◽  
Haiyang Chao ◽  
Jason N. Gross
Keyword(s):  
Optical Flow ◽  
Unmanned Aerial Vehicle ◽  
Inertial Sensors ◽  
Wide Field ◽  
Flight Data ◽  
Information Filter ◽  
Full State ◽  
Flow Information ◽  
Aerial Vehicle ◽  
Image Distance

This paper offers a set of novel navigation techniques that rely on the use of inertial sensors and wide-field optical flow information. The aircraft ground velocity and attitude states are estimated with an Unscented Information Filter (UIF) and are evaluated with respect to two sets of experimental flight data collected from an Unmanned Aerial Vehicle (UAV). Two different formulations are proposed, a full state formulation including velocity and attitude and a simplified formulation which assumes that the lateral and vertical velocity of the aircraft are negligible. An additional state is also considered within each formulation to recover the image distance which can be measured using a laser rangefinder. The results demonstrate that the full state formulation is able to estimate the aircraft ground velocity to within 1.3 m/s of a GPS receiver solution used as reference “truth” and regulate attitude angles within 1.4 degrees standard deviation of error for both sets of flight data.

Adaptive Control Scheme for Coupled Tank Process

2018 ◽  
pp. 89-95
Author(s):  
Vinodhini M.
Keyword(s):  
Adaptive Control ◽  
Nonlinear Behaviour ◽  
Simulation Studies ◽  
Input Output ◽  
Control Scheme ◽  
Direct Model ◽  
Multivariable Process ◽  
Model Reference Adaptive ◽  
Siso System ◽  
Adaptive Control Scheme

The objective of this paper is to develop a Direct Model Reference Adaptive Control (DMRAC) algorithm for a MIMO process by extending the MIT rule adopted for a SISO system. The controller thus developed is implemented on Laboratory interacting coupled tank process through simulation. This can be regarded as the relevant process control in petrol and chemical industries. These industries involve controlling the liquid level and the flow rate in the presence of nonlinearity and disturbance which justifies the use of adaptive techniques such as DMRAC control scheme. For this purpose, mathematical models are obtained for each of the input-output combinations using white box approach and the respective controllers are developed. A detailed analysis on the performance of the chosen process with these controllers is carried out. Simulation studies reveal the effectiveness of proposed controller for multivariable process that exhibits nonlinear behaviour.

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