Enhancement in Smart Operation of Greenhouse Environment Using Intelligent Biomimetic Control Framework

The greenhouse is a complex nonlinear system, which provides a suitable growing environment for plants. Realizing a comprehensive control for such systems is more challenging in the premise of the presence of model parameter uncertainties and variable time delay. This work presents, develops, and tests the methodology entrenched from the computational inspiration of the biologic immune concept. Mostly, in contention to the widely used classical approach of greenhouse control, an essential facet of the bioinspired algorithm is integrated that synergizes its strength. In this work, the study considers proportional integral and pseudo-derivative-feedback controllers and the artificial immune feature supplements it for the proposal of a new unifying control framework. The non-intelligent techniques are more classical, whereas intelligent techniques involving resistant feature is still relatively new to the control arena. The main distinguishing feature is the superficial resemblance to the conventional controller, but it is inherently more flexible and sophisticated and can exploit the power of heuristics. To deal with the system realistically and to ensure robustness, the Kharitonov theorem is used to synthesize the controller by elucidating the relationship between coefficient perturbations, set of test eight specially constructed vortex polynomials and its stability. Further, Hardware in Loop simulation is performed to verify the performance near physical operating conditions and the results validate the efficacy of the proposed controller frameworks with improvement in dynamic performance and robustness.