LHC Collimators Low Level Control System

2007 ◽  
Author(s):  
Alessandro Masi ◽  
Roberto Losito
Keyword(s):  
Control System ◽  
Level Control ◽  
Low Level ◽  
Level Control System

LOW-LEVEL CONTROL SYSTEM OF A NEW BIPED ROBOT "ROTTO"

2009 ◽  
Author(s):  
M. KONYEV ◽  
F. PALIS ◽  
Y. ZAVGORODNIY ◽  
A. MELNYKOV ◽  
A. RUDSKYY ◽  
...  
Keyword(s):  
Control System ◽  
Biped Robot ◽  
Level Control ◽  
Low Level ◽  
Level Control System

Reliability review of the LHC Collimators Low Level Control System

2010 ◽  
Vol 43 (8) ◽  
pp. 200-205
Author(s):  
A. Masi ◽  
M. Donze ◽  
R. Losito
Keyword(s):  
Control System ◽  
Level Control ◽  
Low Level ◽  
Level Control System

scholarly journals LHC Collimators Low Level Control System

2008 ◽  
Vol 55 (1) ◽  
pp. 333-340 ◽  
Author(s):  
Alessandro Masi ◽  
Roberto Losito
Keyword(s):  
Control System ◽  
Level Control ◽  
Low Level ◽  
Level Control System

scholarly journals Development of a Low-Level Control System for the ROV Visor3

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Santiago Rúa ◽  
Rafael E. Vásquez
Keyword(s):  
Mathematical Model ◽  
Control System ◽  
Nonlinear Observer ◽  
Navigation Systems ◽  
Level Control ◽  
Remotely Operated Vehicle ◽  
Low Level ◽  
Level Control System ◽  
High Level ◽  
And Control

This paper addresses the development of the simulation of the low-level control system for the underwater remotely operated vehicle Visor3. The 6-DOF mathematical model of Visor3 is presented using two coordinated systems: Earth-fixed and body-fixed frames. The navigation, guidance, and control (NGC) structure is divided into three layers: the high level or the mission planner; the mid-level or the path planner; and the low level formed by the navigation and control systems. The nonlinear model-based observer is developed using the extended Kalman filter (EKF) which uses the linearization of the model to estimate the current state. The behavior of the observer is verified through simulations using Simulink®. An experiment was conducted with a trajectory that describes changes in the x and y and yaw components. To accomplish this task, two algorithms are compared: a multiloop PID and PID with gravity compensation. These controllers and the nonlinear observer are tested using the 6-DOF mathematical model of Visor3. The control and navigation systems are a fundamental part of the low-level control system that will allow Visor3’s operators to take advantage of more advanced vehicle’s capabilities during inspection tasks of port facilities, hydroelectric dams, and oceanographic research.

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