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

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

An Impact Evaluation of the Government Grant Programs and Input Efficiency Use in the Production of Greenhouse Tomatoes and Peppers in Kosovo

Determinants of greenhouse tomato and pepper production input efficiency affect a farmer’s decision to contribute to the vegetable sector in Kosovo. This research investigates the non-optimal use of inputs in the production of greenhouse tomatoes and peppers. Two studies were conducted to first measure input efficiency use and then to quantify the impact of the Ministry of Agriculture, Forestry and Rural Development (MAFRD) grant programs in the production of both crops. The first study applied data envelopment analysis (DEA), and linear and logistic regression to assess factors that influence efficiency in production. The second study used propensity score matching with logistic regression and genetic matching in order to evaluate any impacts, including income differences, between MAFRD grantees and non-grantees. The DEA results suggest that of the seven regions in Kosovo, most of the efficient greenhouse tomato producers were found in Prizren with a mean efficiency of 83 percent. While Prishtina had the most efficient greenhouse pepper producers with a mean efficiency of 99 percent. The logistic regression results with the use of technical efficiency (TE) scores as the dependent variable with a threshold produced different results to the linear regression. For example, estimates were more statistically significant under linear regression. The second study using matching techniques demonstrated that greenhouse farmers with higher yields and small total greenhouse areas were more likely to participate in the government’s grant program. The analysis revealed that MAFRD greenhouse tomato grantees compared to the non-grantees may make additionally an estimated of 1,777 euros. Insignificant estimate results were registered for the sample of greenhouse pepper farmers. Overall, the first study demonstrated that depending on the characteristics of the farms, factors related to production efficiency may affect input efficiency use. The second study suggested that a quality matching of the greenhouse tomato farmers could be achieved. However, only a partial matching was obtained among greenhouse pepper farmers