Analysis and development of a buoyancy-pitch based depth control algorithm for a hybrid underwater glider

2012 ◽  
Author(s):  
Brian Claus ◽  
Ralf Bachmayer ◽  
Lauren Cooney
Keyword(s):  
Control Algorithm ◽  
Underwater Glider ◽  
Depth Control

Adaptive depth control algorithm for sound tracing

2018 ◽  
Vol 24 (5) ◽  
pp. 21-30
Author(s):  
Eun Jae Kim ◽  
Woonam Chung ◽  
Woochan Park ◽  
Yun Juwon ◽  
Youngsik Kim
Keyword(s):  
Control Algorithm ◽  
Depth Control

U-model based depth control of underwater glider

2015 ◽  
Author(s):  
Isra Abbasi ◽  
S. Saad Azhar Ali ◽  
Rosdiazli Ibrahim ◽  
Syed Hasan Adil ◽  
Mark Ovinis
Keyword(s):  
Underwater Glider ◽  
Model Based ◽  
Depth Control

Depth Control Method of AFM-Based Nanomachining with Diamond Tip in Deflection Mode

2007 ◽  
Vol 10-12 ◽  
pp. 578-582 ◽  
Author(s):  
Zhen Jiang Hu ◽  
Yong Da Yan ◽  
Tao Sun ◽  
Shen Dong ◽  
Z.Z. Zhao
Keyword(s):  
Theoretical Analysis ◽  
Penetration Depth ◽  
Theoretical Basis ◽  
Control Algorithm ◽  
Control Method ◽  
Normal Load ◽  
Penetration Process ◽  
Depth Control ◽  
Machining System

The equations correlated the normal load and the tip penetration depth were derived through the theoretical analysis of the penetration process of the diamond tip. Verified by experiments, the equations can reflect the penetration process of the scratching machining system and provide theoretical basis for the optimization of depth control algorithm. The control of scratching depth realized in AFM deflection mode can effectively restrain the system drift during scratching process.

ENHANCING THE YIELD OF HIGH-DENSITY ELECTRODE ARRAYS THROUGH AUTOMATED ELECTRODE SELECTION

2012 ◽  
Vol 22 (01) ◽  
pp. 1-19 ◽  
Author(s):  
GERT VAN DIJCK ◽  
KARSTEN SEIDL ◽  
OLIVER PAUL ◽  
PATRICK RUTHER ◽  
MARC M. VAN HULLE ◽  
...  
Keyword(s):  
Control Algorithm ◽  
Signal To Noise Ratio ◽  
Pyramidal Cells ◽  
Inhibitory Interneurons ◽  
Electrode Arrays ◽  
Signal To Noise ◽  
Detection Algorithms ◽  
Benchmark Data ◽  
Depth Control ◽  
Electrode Selection

Recently developed CMOS-based microprobes contain hundreds of electrodes on a single shaft with inter-electrode distances as small as 30 μm. So far, neuroscientists needed to select electrodes manually from hundreds of electrodes. Here we present an electronic depth control algorithm that allows to select electrodes automatically, hereby allowing to reduce the amount of data and locating those electrodes that are close to neurons. The electrodes are selected according to a new penalized signal-to-noise ratio (PSNR) criterion that demotes electrodes from becoming selected if their signals are redundant with previously selected electrodes. It is shown that, using the PSNR, interneurons generating smaller spikes are also selected. We developed a model that aims to evaluate algorithms for electronic depth control, but also generates benchmark data for testing spike sorting and spike detection algorithms. The model comprises a realistic tufted pyramidal cell, non-tufted pyramidal cells and inhibitory interneurons. All neurons are synaptically activated by hundreds of fibers. This arrangement allows the algorithms to be tested in more realistic conditions, including backgrounds of synaptic potentials, varying spike rates with bursting and spike amplitude attenuation.

Pitch and Depth Control of Underwater Glider using LQG and LQR via Kalman Filter

2018 ◽  
Vol 10 (2) ◽  
Author(s):  
B. Ullah ◽  
M. Ovinis ◽  
M.B. Baharom ◽  
S.S.A Ali ◽  
M.Y. Javaid
Keyword(s):  
Kalman Filter ◽  
Linear Quadratic Regulator ◽  
Good Control ◽  
External Noise ◽  
Control Surface ◽  
Underwater Glider ◽  
Linear Quadratic ◽  
Control Effort ◽  
Underwater Gliders ◽  
Depth Control

Underwater gliders are adversely affected by ocean currents because of their low speed, which is compounded by an inability to make quick corrective manoeuvres due to limited control surface and weak buoyancy driven propulsion system. In this paper, Linear Quadratic Regulator (LQR) and Linear Quadratic Gaussian (LQG) robust controllers are presented for pitch and depth control of an underwater glider. The LQR and LQG robust control schemes are implemented using MATLAB/Simulink. A Kalman filter was designed to estimate the pitch of the glider. Based on the simulation results, both controllers are compared to show the robustness in the presence of noise. The LQG controller results shows good control effort in presence of external noise and the stability of the controller performance is guaranteed.

scholarly journals Coordinated Depth Control of Multiple Autonomous Underwater Vehicles by Using Theory of Adaptive Sliding Mode

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Yintao Wang ◽  
Yani Zhang
Keyword(s):  
Control Algorithm ◽  
Sliding Mode ◽  
Autonomous Underwater Vehicles ◽  
Underwater Vehicles ◽  
Loop Control ◽  
Depth Control ◽  
The Common ◽  
Extended Graph ◽  
Rudder Angle ◽  
Theoretical Results

This paper addresses the coordinated depth control problem of multiple autonomous underwater vehicles, which means to maneuver a group of underwater vehicles which move at the same depth synchronously. Firstly, a coordinated error of depth between vehicles and the common desired depth is defined by using extended graph theory in a distributed manner; then a deep-pitch double loop control algorithm based on sliding mode is designed for each vehicle, by which each vehicle is driven to and move at the common depth coordinately. In particular, a pitch reference command is firstly calculated by the predefined coordinated depth error, which can be regarded as the outer loop control, and then, the input rudder angle for each vehicle is derived according to the pitch reference command being as the inner loop control. Considering the uncertainties of the model hydrodynamic parameters, an online parameter adaptive algorithm is introduced to improve the performance of the sliding mode control algorithm proposed. Simulations were performed to verify the theoretical results proposed.

scholarly journals Depth control design and simulation of hybrid underwater glider

2019 ◽  
Vol 1402 ◽  
pp. 044018
Author(s):  
A Latifah ◽  
D D S Fatimah ◽  
B L Hakim ◽  
D Chandrahadinata
Keyword(s):  
Control Design ◽  
Underwater Glider ◽  
Depth Control
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