Open-loop Subspace Identification

2008 ◽  
pp. 31-53
Author(s):  
Biao Huang ◽  
Ramesh Kadali
Keyword(s):  
Open Loop ◽  
Subspace Identification

scholarly journals Closed loop identification of a piezoelectrically controlled radial gas bearing: Theory and experiment

2018 ◽  
Vol 232 (7) ◽  
pp. 926-936
Author(s):  
André Krabdrup Sekunda ◽  
Hans Henrik Niemann ◽  
Niels Kjølstad Poulsen ◽  
Ilmar Ferreira Santos
Keyword(s):  
Feedback Control ◽  
Dynamic Model ◽  
Prediction Error ◽  
Feedback Loop ◽  
Open Loop ◽  
Subspace Identification ◽  
Identification Methods ◽  
The Impact ◽  
Gas Bearing ◽  
Error Method

Gas bearing systems have extremely small damping properties. Feedback control is thus employed to increase the damping of gas bearings. Such a feedback loop correlates the input with the measurement noise which in turn makes the assumptions for direct identification invalid. The originality of this article lies in the investigation of the impact of using different identification methods to identify a rotor-bearing systems’ dynamic model when a feedback loop is active. Two different identification methods are employed. The first method is open loop Prediction Error Method, while the other method is the modified Hansen scheme. Identification based on the modified Hansen scheme is conducted by identifying the Youla deviation system using subspace identification. Identification of the Youla deviation system is based on the Youla–Jabr–Bongiorno–Kucera parametrisation of plant and controller. By using the modified Hansen scheme, identification based on standard subspace identification methods can be used to identify the Youla deviation system of the gas bearing. This procedure ensures the input to the Youla deviation system, and the noise is uncorrelated even though the system is subject to feedback control. The effect of identifying the Youla deviation system compared to direct subspace identification of the gas bearing is further investigated through a simulation example. Experiments are conducted on the piezoelectrically controlled radial gas bearing. A dynamic model is identified using the modified Hansen scheme as well as using Prediction Error Method identification. The resulting models are compared for different imperfect nominal models, to examine under which conditions each method should be used.

scholarly journals Model Predictive Control for the Process of MEA Absorption of CO2 Based on the Data Identification Model

Processes ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 183
Author(s):  
Qianrong Li ◽  
Wenzhao Zhang ◽  
Yuwei Qin ◽  
Aimin An
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Aspen Plus ◽  
Open Loop ◽  
Operating Conditions ◽  
Effective Control ◽  
Subspace Identification ◽  
Capture Process ◽  
The Stability ◽  
Intractable Problem

The absorption process of CO2 by ethanolamine solution is essentially a dynamic system, which is greatly affected by the power plant startup and flue gas load changes. Hence, studying the optimal control of the CO2 chemical capture process has always been an important part in academic fields. Model predictive control (MPC) is a very effective control strategy used for such process, but the most intractable problem is the lack of accurate and effective model. In this work, Aspen Plus and Aspen Plus Dynamics are used to establish the process of monoethanolamine (MEA) absorption of CO2 related models based on subspace identification. The nonlinear distribution of the system under steady-state operation is analyzed. Dynamic tests were carried out to understand the dynamic characteristics of the system under variable operating conditions. Systematic subspace identification on open-loop experimental data was performed. We designed a model predictive controller based on the identified model combined with the state-space equation using Matlab/Simulink to analyze the changes of the system under two different disturbances. The simulation results show that the control performance of the MPC algorithm is significantly better than that of the traditional proportion integral differential (PID) system, with excellent setpoint tracking ability and robustness, which improve the stability and flexibility of the system.

scholarly journals Multivariable Constrained Adaptive Predictive Control based on Closed-loop Subspace Identification

2020 ◽  
Vol 14 ◽  
Keyword(s):  
Predictive Control ◽  
Closed Loop ◽  
Control Method ◽  
Open Loop ◽  
System Model ◽  
Quadratic Program ◽  
Subspace Identification ◽  
Identification Algorithm ◽  
Prediction Errors ◽  
Adaptive Predictive Control

In order to deal with nonlinear, time-varying, and multivariable constrained characteristics in closed-loop industrial processes, a multivariable constrained adaptive predictive control (CAPC) method based on closed-loop subspace identification is proposed. The state-space model is obtained through the closed-loop subspace identification algorithm, which is regarded as the system model. The algorithm is implemented online to update the R matrix with a receding window. By comparing the prediction errors before and after updating, it considers whether or not to update the system model. The model is then used to design the model predictive controller, which involves the solution of a quadratic program solving multivariable constraints. This paper presents a comparison between the performance of the proposed control method when applied to a 2-CSTR system, and that of an open-loop subspace CAPC method. The superiority of the proposed method is illustrated by the simulation results.

scholarly journals Hankel Matrix Correlation Function-Based Subspace Identification Method for UAV Servo System

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Minghong She ◽  
Pengju Zhao
Keyword(s):  
Correlation Function ◽  
Closed Loop ◽  
Hankel Matrix ◽  
Servo System ◽  
Identification Problem ◽  
Open Loop ◽  
Subspace Identification ◽  
Identification Algorithm ◽  
Related Data ◽  
Multiplication Operation

For the identification problem of closed-loop subspace model, we propose a zero space projection method based on the estimation of correlation function to fill the block Hankel matrix of identification model by combining the linear algebra with geometry. By using the same projection of related data in time offset set and LQ decomposition, the multiplication operation of projection is achieved and dynamics estimation of the unknown equipment system model is obtained. Consequently, we have solved the problem of biased estimation caused when the open-loop subspace identification algorithm is applied to the closed-loop identification. A simulation example is given to show the effectiveness of the proposed approach. In final, the practicability of the identification algorithm is verified by hardware test of UAV servo system in real environment.

Set of open-loop block-diagonalizers of transfer matrices

1989 ◽  
Vol 49 (1) ◽  
pp. 161-168
Author(s):  
A. Bülent Özgü Ler ◽  
Vasfi Eldem
Keyword(s):  
Open Loop ◽  
Transfer Matrices

On closed-loop equilibrium strategies for mean-field stochastic linear quadratic problems

2020 ◽  
Vol 26 ◽  
pp. 41
Author(s):  
Tianxiao Wang
Keyword(s):  
Optimal Control ◽  
Closed Loop ◽  
Optimal Control Problems ◽  
Mean Field ◽  
Open Loop ◽  
Time Inconsistency ◽  
Control Problems ◽  
Linear Quadratic ◽  
Linear Quadratic Optimal Control ◽  
Equilibrium Strategies

This article is concerned with linear quadratic optimal control problems of mean-field stochastic differential equations (MF-SDE) with deterministic coefficients. To treat the time inconsistency of the optimal control problems, linear closed-loop equilibrium strategies are introduced and characterized by variational approach. Our developed methodology drops the delicate convergence procedures in Yong [Trans. Amer. Math. Soc. 369 (2017) 5467–5523]. When the MF-SDE reduces to SDE, our Riccati system coincides with the analogue in Yong [Trans. Amer. Math. Soc. 369 (2017) 5467–5523]. However, these two systems are in general different from each other due to the conditional mean-field terms in the MF-SDE. Eventually, the comparisons with pre-committed optimal strategies, open-loop equilibrium strategies are given in details.

Comparison of Dc-Dc SEPIC, CUK and Flyback Converters Based LED Drivers

2020 ◽  
pp. 99-107
Author(s):  
Erdal Sehirli
Keyword(s):  
Integrated Circuit ◽  
Closed Loop ◽  
Input Voltage ◽  
Open Loop ◽  
Current Sensor ◽  
Switching Frequency ◽  
Led Driver ◽  
Advantages And Disadvantages ◽  
Led Drivers ◽  
Conduction Mode

This paper presents the comparison of LED driver topologies that include SEPIC, CUK and FLYBACK DC-DC converters. Both topologies are designed for 8W power and operated in discontinuous conduction mode (DCM) with 88 kHz switching frequency. Furthermore, inductors of SEPIC and CUK converters are wounded as coupled. Applications are realized by using SG3524 integrated circuit for open loop and PIC16F877 microcontroller for closed loop. Besides, ACS712 current sensor used to limit maximum LED current for closed loop applications. Finally, SEPIC, CUK and FLYBACK DC-DC LED drivers are compared with respect to LED current, LED voltage, input voltage and current. Also, advantages and disadvantages of all topologies are concluded.

Highly Linear Open-Loop Amplifiers Using Nonlinearity Cancellation and Gain Adapting Techniques

2016 ◽  
Vol E99.C (6) ◽  
pp. 641-650
Author(s):  
Lilan YU ◽  
Masaya MIYAHARA ◽  
Akira MATSUZAWA
Keyword(s):  
Open Loop
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