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A greenhouse system (GHS) is a closed structure that facilitates modified growth conditions to crops and provides protection from pests, diseases and adverse weather. However, a GHS exhibits non-linearity due to the interaction between the biological subsystem and the physical subsystem. Non-linear systems are difficult to control, particularly when their characteristics change with time. These systems are best handled with methods of computation intelligence, such as artificial neural networks (ANNs) and fuzzy systems. In the present work, the approximation capability of a neural network is used to model and control sufficient growth conditions of a GHS. An optimal neural network-based non-linear auto regressive with exogenous input (NARX) time series model is developed for a GHS. Based on the NARX model, two intelligent control schemes, namely a neural predictive controller (NPC) and non-linear auto regressive moving average (NARMA-L2) controller are proposed to achieve the desired growth conditions such as humidity and temperature for a better yield. Finally, closed-loop performances of the above two control schemes for servo and regulatory operations are analysed for various operating conditions using performance indices.

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Polyaniline embedded green copper oxide (Cu2O/PANI) nanocomposite has been synthesized through in situ chemical polymerization method in acidic medium at room temperature. The structural, optical, and magnetic properties of Cu2O/PANI nanocomposite were investigated through Fourier transform infrared spectroscopy (FTIR), UV-Vis absorption spectra (UV-Vis spectra), scanning electron microscopy (SEM), photoluminescence spectra (PL), and vibrating sample magnetometer (VSM). FTIR spectra confirmed the formation of Cu2O/PANI composite through the shifting of vibrational peaks of PANI and green Cu2O nanoparticles at 825, 1142, 1299, 1499, 1573 cm−1 and 695 cm−1 respectively. SEM analysis revealed that many aggregations of well-separated irregular shape of Cu2O nanoparticles with diameter about 15–40 nm exist in the composite matrix. Optical absorbance studies further confirmed the formation of composite through the blue shift of absorption peaks of PANI and diminishing intensity peak of Cu2O. Cu2O/PANI nanocomposite demonstrates semiconducting as well as diamagnetic behavior like PANI and Cu2O nanoparticles. The nanocomposite exhibits high relative photoluminescence intensity in blue as well as green-yellow region of visible spectrum. The optical band gap value from absorption coefficient data is found to be 3.23 eV.