Enabling full field physics based OPC via dynamic model generation

2017 ◽  
Author(s):  
Michael Lam ◽  
Chris Clifford ◽  
Ananthan Raghunathan ◽  
Germain Fenger ◽  
Kostas Adam
Keyword(s):  
Dynamic Model ◽  
Model Generation ◽  
Full Field

Enabling full-field physics-based optical proximity correction via dynamic model generation

2017 ◽  
Vol 16 (3) ◽  
pp. 033502 ◽  
Author(s):  
Michael Lam ◽  
Chris Clifford ◽  
Ananthan Raghunathan ◽  
Germain Fenger ◽  
Kostas Adam
Keyword(s):  
Dynamic Model ◽  
Model Generation ◽  
Full Field ◽  
Optical Proximity Correction

LQR Feedback Control Development for Wind Turbines Featuring a Digital Fluid Power Transmission System

2016 ◽  
Author(s):  
Niels H. Pedersen ◽  
Per Johansen ◽  
Torben O. Andersen
Keyword(s):  
Wind Turbine ◽  
Dynamic Model ◽  
Control Strategy ◽  
Linear Time ◽  
Control Design ◽  
Design Approach ◽  
Fluid Power ◽  
Full Field ◽  
Delta Sigma ◽  
Pulse Density

Research within digital fluid power (DFP) transmissions is receiving an increased attention as an alternative to conventional transmission technologies. The use of DFP displacement machines entails a need for applicable control algorithms. However, the design and analysis of controllers for such digital systems are complicated by its non-smooth behavior. In this paper a control design approach for a digital displacement machine® is proposed and a performance analysis of a wind turbine using a DFP transmission is presented. The performance evaluation is based on a dynamic model of the transmission with a DFP motor, which has been combined with the NREL 5-MW reference wind turbine model. A classical variable speed control strategy for wind speeds below rated is proposed for the turbine, where the pump displacement is fixed and the digital motor displacement is varied for pressure control. The digital motor control strategy consists of a full stroke operation strategy, where a Delta-Sigma pulse density modulator is used to determine the chamber activation sequence. In the LQR-control design approach, the discrete behavior of the motor and Delta-Sigma modulator is described by a discrete linear time invariant model. Using full-field flow wind profiles as input, the design approach and control performance is verified by simulation in the dynamic model of the wind turbine featuring the DFP transmission. Additionally, the performance is compared to that of the conventional NREL reference turbine, transmission and controller.

scholarly journals AMOGA: A Static-Dynamic Model Generation Strategy for Mobile Apps Testing

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 17158-17173 ◽  
Author(s):  
Ibrahim-Anka Salihu ◽  
Rosziati Ibrahim ◽  
Bestoun S. Ahmed ◽  
Kamal Z. Zamli ◽  
Asmau Usman
Keyword(s):  
Dynamic Model ◽  
Mobile Apps ◽  
Model Generation

Automatic Model Generation for Modular Reconfigurable Robot Dynamics

1998 ◽  
Vol 120 (3) ◽  
pp. 346-352 ◽  
Author(s):  
I-Ming Chen ◽  
Guilin Yang
Keyword(s):  
Closed Form ◽  
Dynamic Model ◽  
Degrees Of Freedom ◽  
Dynamic Models ◽  
Equation Of Motion ◽  
Robot Dynamics ◽  
Model Generation ◽  
Modular Robot ◽  
Form Equation ◽  
Automatic Model Generation

In control and simulation of a modular robot system, which consists of standardized and interconnected joint and link units, manual derivation of its dynamic model needs tremendous effort because these models change all the time as the robot geometry is altered after module reconfiguration. This paper presents a method to automate the generation of the closed-form equation of motion of a modular robot with arbitrary degrees-of-freedom and geometry. The robot geometry we consider here is branching type without loops. A graph technique, termed kinematic graphs and realized through assembly incidence matrices (AIM) is introduced to represent the module assembly sequence and robot geometry. The formulation of the dynamic model is started with recursive Newton-Euler algorithm. The generalized velocity, acceleration, and forces are expressed in terms of linear operations on se(3), the Lie algebra of the Euclidean group SE(3). Based on the equivalence relationship between the recursive formulation and the closed-form Lagrangian formulation, the accessibility matrix of the kinematic graph of the robot is used to assist the construction of the closed-form equation of motion of a modular robot. This automatic model generation technique can be applied to the control of rapidly reconfigurable robotic workcells and other automation equipment built around modular components that require accurate dynamic models.

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