Digital Simulator for Steady-State Performance Prediction of Military Turbofan Engine

1998 ◽  
Vol 14 (1) ◽  
pp. 74-81 ◽  
Author(s):  
Vivek Sanghi ◽  
B. K. Lakshmanan ◽  
V. Sundararajan
Keyword(s):  
Steady State ◽  
Performance Prediction ◽  
Turbofan Engine ◽  
Steady State Performance

Quasi-steady-state performance of a heat pipe subjected to transient acceleration loadings

10.2514/3.895 ◽  
1997 ◽  
Vol 11 ◽  
pp. 306-309 ◽  
Author(s):  
Edwin H. Olmstead ◽  
Edward S. Taylor ◽  
Meng Wang ◽  
Parviz Moin ◽  
Scott K. Thomas ◽  
...  
Keyword(s):  
Steady State ◽  
Heat Pipe ◽  
Quasi Steady State ◽  
Steady State Performance

A Novel Control Scheme for PWM Boost Converter based on Sliding Mode Control using Particle Swarm Optimization

2020 ◽  
Vol 14 ◽  
Author(s):  
Gang Liu ◽  
Dong Qiu ◽  
Xiuru Wang ◽  
Ke Zhang ◽  
Huafeng Huang ◽  
...  
Keyword(s):  
Particle Swarm Optimization ◽  
Steady State ◽  
Sliding Mode ◽  
Particle Swarm ◽  
Mathematic Model ◽  
Absolute Error ◽  
Boost Converter ◽  
Sliding Mode Controller ◽  
Swarm Optimization ◽  
Steady State Performance

Background: The PWM Boost converter is a strongly nonlinear discrete system, especially when the input voltage or load varies widely, therefore, tuning the control parameters of which is a challenge work. Objective: In order to overcome the issues, particle swarm optimization (PSO) is employed for tuning the parameters of a sliding mode controller of a boost converter. Methods: Based on the analysis of the Boost converter model and its non-linear characteristics, a mathematic model of a boost converter with a sliding mode controller is built firstly. Then, the parameters of the Boost controller are adjusted based on the integrated time and absolute error (ITAE), integral square error (ISE) and integrated absolute error (IAE) indexes by PSO. Results: Simulation verification was performed, and the results show that the controllers tuned by the three indexes all have excellent robust stability. Conclusion: The controllers tuned by ITAE and ISE indexes have excellent steady-state performance, but the overshoot is large during the startup. The controller tuned by IAE index has better startup performance and slightly worse steady-state performance.

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