Intelligent Steering Control of an Autonomous Underwater Vehicle

2000 ◽  
Vol 53 (3) ◽  
pp. 511-525 ◽  
Author(s):  
R. Sutton ◽  
R. S. Burns ◽  
P. J. Craven
Keyword(s):  
Control Algorithm ◽  
Autonomous Underwater Vehicle ◽  
Fuzzy Inference ◽  
Underwater Vehicle ◽  
Guidance System ◽  
Line Of Sight ◽  
Steering Control ◽  
Inference System ◽  
Sea Current ◽  
Proportional Derivative Controller

This paper considers the development of three autopilots for controlling the yaw responses of an autonomous underwater vehicle model. The autopilot designs are based on the adaptive network-based fuzzy inference system (ANFIS), a simulated, annealing-tuned control algorithm and a traditional proportional-derivative controller. In addition, each autopilot is integrated with a line-of-sight (LOS) guidance system to test its effectiveness in steering round a series of waypoints with and without the presence of sea current disturbance. Simulation results are presented that show the overall superiority of the ANFIS approach.

Terminal Underwater Docking of an Autonomous Underwater Vehicle Using One Camera and One Light

2016 ◽  
Vol 50 (6) ◽  
pp. 58-68 ◽  
Author(s):  
Dejun Li ◽  
Tao Zhang ◽  
Canjun Yang
Keyword(s):  
Image Processing ◽  
Tracking Control ◽  
Control Algorithm ◽  
Autonomous Underwater Vehicle ◽  
Underwater Vehicle ◽  
Guidance System ◽  
Lateral Deviation ◽  
Distance Information ◽  
Underwater Docking ◽  
Vision Guidance

AbstractThis study introduces a vision guidance system for the terminal underwater docking of an autonomous underwater vehicle (AUV) using one camera and one light. The configuration of this docking system, including an overview of the AUV and the docking station, is proposed. A detailed description of the vision guidance system is then provided. Four stages, namely, image acquisition, binarization of the captured images, elimination of noisy luminaries, and estimation of the relative position, constitute the image processing procedure. A tracking control algorithm based on the position of the dock center in the image coordinate obtained through image processing has been proposed. This algorithm can guide the AUV to the docking station without requiring distance information. A pool trial has been conducted at night to validate the proposed algorithm. Experimental results demonstrate the effectiveness of the vision guidance system despite the initial lateral deviation of up to 8 m. This paper ends with an analysis of the advantages and defects of this vision guidance system and proposes future works.

scholarly journals An Adaptive Neuro-Fuzzy Control of Pneumatic Mechanical Ventilator

Actuators ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 51
Author(s):  
Jozef Živčák ◽  
Michal Kelemen ◽  
Ivan Virgala ◽  
Peter Marcinko ◽  
Peter Tuleja ◽  
...  
Keyword(s):  
Control System ◽  
Control Algorithm ◽  
Fuzzy Inference ◽  
Fuzzy Controller ◽  
Mechanical Design ◽  
Mechanical Ventilator ◽  
Mechanical Ventilators ◽  
Inference System ◽  
Control Approach ◽  
Neuro Fuzzy

COVID-19 was first identified in December 2019 in Wuhan, China. It mainly affects the respiratory system and can lead to the death of the patient. The motivation for this study was the current pandemic situation and general deficiency of emergency mechanical ventilators. The paper presents the development of a mechanical ventilator and its control algorithm. The main feature of the developed mechanical ventilator is AmbuBag compressed by a pneumatic actuator. The control algorithm is based on an adaptive neuro-fuzzy inference system (ANFIS), which integrates both neural networks and fuzzy logic principles. Mechanical design and hardware design are presented in the paper. Subsequently, there is a description of the process of data collecting and training of the fuzzy controller. The paper also presents a simulation model for verification of the designed control approach. The experimental results provide the verification of the designed control system. The novelty of the paper is, on the one hand, an implementation of the ANFIS controller for AmbuBag pressure control, with a description of training process. On other hand, the paper presents a novel design of a mechanical ventilator, with a detailed description of the hardware and control system. The last contribution of the paper lies in the mathematical and experimental description of AmbuBag for ventilation purposes.

Control Algorithm of a Multilevel Converter based on a Fuzzy Inference System using MATLAB

2007 ◽  
Author(s):  
Salvador Revelo-Andrade ◽  
Mariano Fernandez-Nava ◽  
Pedro Banuelos-Sanchez ◽  
Felix E. Guerrero-Castro
Keyword(s):  
Fuzzy Inference System ◽  
Control Algorithm ◽  
Fuzzy Inference ◽  
Multilevel Converter ◽  
Inference System

Robust Adaptive Tracking Control of Autonomous Underwater Vehicle-Manipulator Systems

2014 ◽  
Vol 136 (5) ◽  
Author(s):  
Mohan Santhakumar ◽  
Jinwhan Kim
Keyword(s):  
Adaptive Control ◽  
Control Algorithm ◽  
Autonomous Underwater Vehicle ◽  
Underwater Vehicle ◽  
Dynamic Coupling ◽  
Unknown Parameters ◽  
Adaptive Tracking Control ◽  
Control Scheme ◽  
Robust Adaptive ◽  
Model Reference Adaptive

This paper proposes a new tracking controller for autonomous underwater vehicle-manipulator systems (UVMSs) using the concept of model reference adaptive control. It also addresses the detailed modeling and simulation of the dynamic coupling between an autonomous underwater vehicle and manipulator system based on Newton–Euler formulation scheme. The proposed adaptation control algorithm is used to estimate the unknown parameters online and compensate for the rest of the system dynamics. Specifically, the influence of the unknown manipulator mass on the control performance is indirectly captured by means of the adaptive control scheme. The effectiveness and robustness of the proposed control scheme are demonstrated using numerical simulations.

The Study of Fuzzy/PID Compound Control Algorithms in Rubber Sulfuration Process Based on Sugeno Rules

2011 ◽  
Vol 221 ◽  
pp. 571-576
Author(s):  
Chun Tang Zhang ◽  
Zhen Zhu Yu
Keyword(s):  
Mathematical Model ◽  
Control Algorithm ◽  
Fuzzy Inference ◽  
Control Algorithms ◽  
Fuzzy Pid ◽  
Inference System ◽  
Pid Algorithm ◽  
Compound Control ◽  
Simulation Results ◽  
Nonlinear Delay

Aiming at rubber sulfuration of nonlinear, delay and complexity, a Fuzzy/PID compound control algorithm is proposed. The algorithm combined fuzzy inference system and PID algorithm, it has solved well the problem which is difficult to establish a precise mathematical model because of the uncertainties and complexities of rubber sulfuration. The simulation results indicate that the control algorithm is viable and effective.

Sign in / Sign up

Export Citation Format

Share Document