Linear Quadratic Gaussian Strategy Research Articles

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

<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

<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>

LQG control of lateral-torsional motion of Nanjing TV transmission tower

The 310 m Nanjing TV transmission tower in China will be installed with an active mass driver on the upper observation deck in order to reduce the acceleration responses under strong wind gusts. This paper presents the linear–quadratic–Gaussian (LQG) control strategy using acceleration feedback to reduce the tower responses under coupled lateral–torsional motion. Emphasis is placed on the practical applications, such as the limitations on actuator peak force and stroke, limited number of sensors, etc. The along- and across-wind components of the wind velocity are defined by the cross-power spectra. In the simulation analysis, both deterministic and stochastic approaches have been used, and the power spectral density, rms values and peak values of response quantities have been computed. Comparisons of the responses of the TV tower due to wind loads from different angles of attack have been made. Simulation results demonstrate that (i) the performance of the active mass driver using the LQG control strategy is remarkable in reducing coupled lateral-torsional motions of the tower, and (ii) the LQG strategy is robust with respect to uncertainties in the angle of attack of wind loads. The LQG strategy is suitable for the full-scale implementation of active mass driver on Nanjing Tower. Copyright © 2000 John Wiley & Sons, Ltd.