scholarly journals Plasma Stabilization System Design on the Base of Model Predictive Control

10.5772/9921 ◽  
2010 ◽  
Author(s):  
Margarita Sotnikova ◽  
Evgeny Veremey
Keyword(s):  
Model Predictive Control ◽  
System Design ◽  
Predictive Control ◽  
Stabilization System ◽  
Plasma Stabilization

Model Predictive Control of Flight Arrival Interval

2012 ◽  
Vol 503-504 ◽  
pp. 1375-1380
Author(s):  
Da Peng Yang ◽  
Ping Bo Sun ◽  
Ke Qiang Hua
Keyword(s):  
Model Predictive Control ◽  
System Design ◽  
Predictive Control ◽  
Traffic Control ◽  
Simulation System ◽  
Arrival Process ◽  
Design Parameters ◽  
Dynamic Matrix ◽  
Parameters Selection ◽  
Wide Range

In order to achieve the automation of Air Traffic Control (ATC), use system to identify the controlled model of flights arrival process which has been already built, using Model Predictive Control (MPC) of the dynamic matrix contro1 (DMC) to control the ATC process. According to DMC algorithm and the features of ATC, the design parameters of this system can be determined by a lot of simulations. It proves that the system design and parameters selection make the system has the required performance and the robustness even if the parameters be changed in a wide range. The experiment on the ATC Simulation System proves that the MPC method is available, conclusion of the study provides a new idea and method for the engineering implementation of the automation of flights arrival process control and some improvement of airspace utilization.

PLASMA STABILIZATION BASED ON MODEL PREDICTIVE CONTROL

2009 ◽  
Vol 24 (05) ◽  
pp. 999-1008 ◽  
Author(s):  
MARGARITA SOTNIKOVA
Keyword(s):  
Nonlinear Dynamics ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Nonlinear Model Predictive Control ◽  
Control Algorithms ◽  
Control Input ◽  
Plasma Current ◽  
Model Based Control ◽  
Sampling Instant ◽  
Plasma Stabilization

The nonlinear model predictive control algorithms for plasma current and shape stabilization are proposed. Such algorithms are quite suitable for the situations when the plant to be controlled has essentially nonlinear dynamics. Besides that, predictive model based control algorithms allow to take into account a lot of requirements and constraints involved both on the controlled and manipulated variables. The significant drawback of the algorithms is that they require a lot of time to compute control input at each sampling instant. In this paper the model predictive control algorithms are demonstrated by the example of plasma vertical stabilization for ITER-FEAT tokamak. The tuning of parameters of algorithms is performed in order to decrease computational load.

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