Continuous State-Space Model in dq Frame of the Thyristor AC/DC Converters for Stability Analysis of ITER Pulsed Power Electrical System

2016 ◽  
Vol 44 (11) ◽  
pp. 2923-2931 ◽  
Author(s):  
Claudio Finotti ◽  
Elena Gaio ◽  
Ivone Benfatto ◽  
Inho Song ◽  
Jun Tao
Keyword(s):  
Stability Analysis ◽  
State Space ◽  
State Space Model ◽  
Pulsed Power ◽  
Electrical System ◽  
Space Model ◽  
Continuous State Space ◽  
Continuous State

Coupled Processor: A Second-Order Continuous-State-Space Model

1990 ◽  
Vol 4 (2) ◽  
pp. 277-298 ◽  
Author(s):  
Haruhisa Takahashi
Keyword(s):  
State Space ◽  
State Space Model ◽  
Second Order ◽  
Two Dimensional ◽  
Riemann Boundary Value Problem ◽  
Riemann Boundary ◽  
Space Model ◽  
Continuous State Space ◽  
Continuous State ◽  
Order Continuous

A second-order continuous-state-space model for two-dimensional queueing systems is developed in this article. A particular problem is treated but the results can apply to some other two-dimensional queueing problems directly. The generating function for the model is obtained by applying a Riemann boundary value problem and leads to a computationally feasible solution.

scholarly journals Adaptive Model Predictive Vibration Control of a Cantilever Beam with Real-Time Parameter Estimation

2014 ◽  
Vol 2014 ◽  
pp. 1-15 ◽  
Author(s):  
Gergely Takács ◽  
Tomáš Polóni ◽  
Boris Rohal’-Ilkiv
Keyword(s):  
Control System ◽  
Vibration Control ◽  
State Space ◽  
Real Time ◽  
Cantilever Beam ◽  
State Space Model ◽  
Model Parameters ◽  
Extended Kalman Filtering ◽  
Space Model ◽  
Continuous State

This paper presents an adaptive-predictive vibration control system using extended Kalman filtering for the joint estimation of system states and model parameters. A fixed-free cantilever beam equipped with piezoceramic actuators serves as a test platform to validate the proposed control strategy. Deflection readings taken at the end of the beam have been used to reconstruct the position and velocity information for a second-order state-space model. In addition to the states, the dynamic system has been augmented by the unknown model parameters: stiffness, damping constant, and a voltage/force conversion constant, characterizing the actuating effect of the piezoceramic transducers. The states and parameters of this augmented system have been estimated in real time, using the hybrid extended Kalman filter. The estimated model parameters have been applied to define the continuous state-space model of the vibrating system, which in turn is discretized for the predictive controller. The model predictive control algorithm generates state predictions and dual-mode quadratic cost prediction matrices based on the updated discrete state-space models. The resulting cost function is then minimized using quadratic programming to find the sequence of optimal but constrained control inputs. The proposed active vibration control system is implemented and evaluated experimentally to investigate the viability of the control method.

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