Advanced Control Method of Rotary Kiln Pellet Sintering Process Based on Operation Pattern Optimization

2016 ◽  
Vol 49 (4) ◽  
pp. 350-356 ◽  
Author(s):  
Wen-Hua Cui ◽  
Jie-Sheng Wang ◽  
Chen-Xu Ning ◽  
Xiu-Dong Ren
Keyword(s):  
Rotary Kiln ◽  
Control Method ◽  
Sintering Process ◽  
Operation Pattern ◽  
Advanced Control

scholarly journals The New Evolution for SIA Rotorcraft UAV Project

2010 ◽  
Vol 2010 ◽  
pp. 1-9 ◽  
Author(s):  
Juntong Qi ◽  
Dalei Song ◽  
Lei Dai ◽  
Jianda Han ◽  
Yuechao Wang
Keyword(s):  
Control Method ◽  
Test Bed ◽  
Advanced Control ◽  
Autonomous Mode ◽  
Chinese Academy Of Sciences ◽  
Aerial Vehicle ◽  
Active Modeling ◽  
Rotorcraft Uav ◽  
The One ◽  
Academy Of Sciences

This paper describes recent research on the design, implement, and testing of a new small-scaled rotorcraft Unmanned Aerial Vehicle (RUAV) system—ServoHeli-40. A turbine-powered UAV weighted less than 15 kg was designed, and its major components were tested at the Shenyang Institute of Automation, Chinese Academy of Sciences in Shenyang, China. The aircraft was designed to reach a top speed of more than 20 mps, flying a distance of more than 10 kilometers, and it is going to be used as a test-bed for experimentally evaluating advanced control methodologies dedicated on improving the maneuverability, reliability, as well as autonomy of RUAV. Sensors and controller are all onboard. The full system has been tested successfully in the autonomous mode using the multichannel active modeling controller. The results show that in a real windy environment the rotorcraft UAV can follow the trajectory which was assigned by the ground control station exactly, and the new control method is obviously more effective than the one in the past year's research.

Intelligence Predictive Control Study on Lime Rotary Kiln Temperature

2013 ◽  
Vol 385-386 ◽  
pp. 848-851 ◽  
Author(s):  
Li Zhang ◽  
Song Wang ◽  
Guo Jun Su
Keyword(s):  
Prediction Model ◽  
Predictive Control ◽  
Rotary Kiln ◽  
Flow Measurement ◽  
Gas Flow ◽  
Large Time ◽  
Control Method ◽  
Time Lag ◽  
Kiln Temperature ◽  
Control Study

For the non-linearity, large time lag characters of rotary kiln, we use intelligent predictive control method to control it. The prediction model, scrolling optimization and feedback adjustment are ultimate constituted the predictive control system each part. Gas flow measurement is used to realize rotary kiln`s temperature predictive control,and took NN-Model as prediction model to realize the intelligent forecast. The results of simulation show that this method has better stability and robustness than the traditional control method.

An Advanced Control Method Based on the Pattern Recognize and Neural Network for Bioprocess

1995 ◽  
Vol 28 (3) ◽  
pp. 113-117
Author(s):  
Shuqing Wang ◽  
Wei Zou ◽  
Haibin Qu ◽  
Yibing Yang
Keyword(s):  
Neural Network ◽  
Control Method ◽  
Advanced Control

Research on aero-engine steady model based on an improved compact propulsion system model

2019 ◽  
Vol 234 (6) ◽  
pp. 726-733
Author(s):  
Qiangang Zheng ◽  
Yong Wang ◽  
Fengyong Sun ◽  
Juan Fang ◽  
Haibo Zhang ◽  
...  
Keyword(s):  
Control Method ◽  
System Modeling ◽  
Propulsion System ◽  
System Model ◽  
Testing Time ◽  
Variable Model ◽  
Output Vector ◽  
State Variable ◽  
Advanced Control ◽  
Aero Engine

The aero-engine steady model is the basis of the modern advanced control method such as performance seeking control. An improved compact propulsion system model is proposed to improve the steady model accuracy. The improved compact propulsion system model mainly contains linear model, such as steady-state variable model, and physical-based models, such as inlet model, nonlinear model, and nozzle model. The improved compact propulsion system model applied to full envelop by parameter corrections. The basepoint control vector and basepoint output vector of improved compact propulsion system model are four-dimensional interpolation instead of two-dimensional interpolation as conventional compact propulsion system modeling does. The improved compact propulsion system model not only considers the change of engine state but also take the flight parameter into account. The simulations of the conventional compact propulsion system modeling and the improved compact propulsion system model are conducted in subsonic and transonic flight envelop. The simulations show that, compared with the conventional compact propulsion system modeling, the relative testing errors of the improved compact propulsion system model decrease greatly. Moreover, the testing time of the conventional compact propulsion system modeling and the improved compact propulsion system model are both almost equal to 0.027 ms.

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