Robust Linear Quadratic Gaussian Controller Design for Oil Coolers Based on a State Space Model

2019 ◽  
Vol 31 (3) ◽  
pp. 130-139
Author(s):  
Seok Kwon Jeong ◽  
Tae Eun Kwon
Keyword(s):  
State Space ◽  
Controller Design ◽  
State Space Model ◽  
Linear Quadratic ◽  
Linear Quadratic Gaussian ◽  
Space Model

scholarly journals A State-Space Model of an Inverter-Based Microgrid for Multivariable Feedback Control Analysis and Design

Energies ◽  
2020 ◽  
Vol 13 (12) ◽  
pp. 3279
Author(s):  
Juan F. Patarroyo-Montenegro ◽  
Jesus D. Vasquez-Plaza ◽  
Fabio Andrade
Keyword(s):  
State Space ◽  
Control Strategies ◽  
State Space Model ◽  
Control Analysis ◽  
Control Methods ◽  
Linear Quadratic ◽  
Analysis And Design ◽  
Space Model ◽  
Bus Voltage ◽  
Multivariable Feedback

In this work, a synchronous model for grid-connected and islanded microgrids is presented. The grid-connected model is based on the premise that the reference frame is synchronized with the AC bus. The quadrature component of the AC bus voltage can be cancelled, which allows to express output power as a linear equation for nominal values in the AC bus amplitude voltage. The model for the islanded microgrid is developed by integrating all the inverter dynamics using a state-space model for the load currents. This model is presented in a comprehensive way such that it could be scalable to any number of inverter-based generators using inductor–capacitor–inductor (LCL) output filters. The use of these models allows designers to assess microgrid stability and robustness using modern control methods such as eigenvalue analysis and singular value diagrams. Both models were tested and validated in an experimental setup to demonstrate their accuracy in describing microgrid dynamics. In addition, three scenarios are presented: non-controlled model, Linear-Quadratic Integrator (LQI) power control, and Power-Voltage (PQ/Vdq) droop–boost controller. Experimental results demonstrate the effectiveness of the control strategies and the accuracy of the models to describe microgrid dynamics.

scholarly journals Synthesis of an Optimal Dynamic Regulator Based on Linear Quadratic Gaussian (LQG) for the Control of the Relative Humidity under Experimental Greenhouse

2016 ◽  
Vol 6 (5) ◽  
pp. 2262
Author(s):  
M. Outanoute ◽  
A. Lachhab ◽  
A. Ed-dahhak ◽  
M. Guerbaoui ◽  
A. Selmani ◽  
...  
Keyword(s):  
Relative Humidity ◽  
State Space ◽  
State Space Model ◽  
The State ◽  
Monitoring And Control ◽  
Linear Quadratic ◽  
Linear Quadratic Gaussian ◽  
State Space System ◽  
Optimal Dynamic ◽  
And Control

<p><span lang="EN-US">This paper describes one practical approach that suggests a model based technique to control in real time the relative humidity under greenhouse. The humidity level is one of the most difficult environmental factors to be regulated in greenhouse. Moreover, maintaining and correcting for more or less humidity can be a challenge for even the most sophisticated monitoring and control equipment. For these raisons, a Linear Quadratic Gaussian (LQG) controller for relative humidity regulation under greenhouse turns out to be useful. Indeed a LQG controller is proposed for a relative humidity under a greenhouse control task. So, the state space model, which is best fitting the acquired data, was identified using the Numerical Subspace State Space System IDentification (N4SID) algorithm. The mathematical model that is obtained will be used for evaluating the parameters of LQG strategy. The proposed controller is implemented in two steps, in one hand, Kalman filter (KF) is used to develop an observer that estimates the state of relative humidity under greenhouse. In the other hand, the state feedback controller gain is estimated using a linear quadratic criterion function. The suggested optimal implemented controller using Matlab/Simulink environment is applied to an experimental greenhouse. We found, according to the results, that the controller is able to lead the inside relative humidity to the desired value with high accuracy, regardless of the external disturbances.</span></p>

Synthesis of an Optimal Dynamic Regulator Based on Linear Quadratic Gaussian (LQG) for the Control of the Relative Humidity under Experimental Greenhouse

2016 ◽  
Vol 6 (5) ◽  
pp. 2262 ◽  
Author(s):  
M. Outanoute ◽  
A. Lachhab ◽  
A. Ed-dahhak ◽  
M. Guerbaoui ◽  
A. Selmani ◽  
...  
Keyword(s):  
Relative Humidity ◽  
State Space ◽  
State Space Model ◽  
The State ◽  
Monitoring And Control ◽  
Linear Quadratic ◽  
Linear Quadratic Gaussian ◽  
State Space System ◽  
Optimal Dynamic ◽  
And Control

<p><span lang="EN-US">This paper describes one practical approach that suggests a model based technique to control in real time the relative humidity under greenhouse. The humidity level is one of the most difficult environmental factors to be regulated in greenhouse. Moreover, maintaining and correcting for more or less humidity can be a challenge for even the most sophisticated monitoring and control equipment. For these raisons, a Linear Quadratic Gaussian (LQG) controller for relative humidity regulation under greenhouse turns out to be useful. Indeed a LQG controller is proposed for a relative humidity under a greenhouse control task. So, the state space model, which is best fitting the acquired data, was identified using the Numerical Subspace State Space System IDentification (N4SID) algorithm. The mathematical model that is obtained will be used for evaluating the parameters of LQG strategy. The proposed controller is implemented in two steps, in one hand, Kalman filter (KF) is used to develop an observer that estimates the state of relative humidity under greenhouse. In the other hand, the state feedback controller gain is estimated using a linear quadratic criterion function. The suggested optimal implemented controller using Matlab/Simulink environment is applied to an experimental greenhouse. We found, according to the results, that the controller is able to lead the inside relative humidity to the desired value with high accuracy, regardless of the external disturbances.</span></p>

The Linear Optimal Control for the Mechanical Vibration Based on Remanufacturing Repaired

2013 ◽  
Vol 823 ◽  
pp. 47-51
Author(s):  
Ling Liu
Keyword(s):  
Optimal Control ◽  
State Space ◽  
Vibration Suppression ◽  
State Space Model ◽  
State Regulation ◽  
Order System ◽  
Modal Control ◽  
Linear Quadratic ◽  
Linear Quadratic Optimal Control ◽  
Space Model

It is used by the piezoelectric ceramics sheet of positive-inverse piezoelectric effect in a set of copper alloy remanufacturing repair cantilever vibration system as the research object in the paper.A state space model have been generated on the cantilever beem mechanical structure of dynamics finite element modeling and degrees of freedom dynamic polycondensation.It is inhibited effectively when a cantilever beam subjected to external transient pulse disturbance caused by first order, two order and higher order system mode vibration,by using the linear quadratic optimal control of two state regulation for the detection of position feedback independent modal control on the basis of the state-space model. Software is used to simulate active vibration control effect.The simulation results show that the mode control inhibited have excellent effects for the repaired cantilever vibration, also analysed on the modal control parameters for the vibration suppression effect.

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