Adaptive Fuzzy Control of a Class of MIMO Nonlinear System With Actuator Saturation for Greenhouse Climate Control Problem

PROJECT TITLE :

Adaptive Fuzzy Control of a Class of MIMO Nonlinear System With Actuator Saturation for Greenhouse Climate Control Problem

ABSTRACT:

This paper presents an indirect adaptive fuzzy control scheme for a category of MIMO non-affine nonlinear systems with unknown dynamics and actuator saturation for greenhouse climate control problems. The objective is to implement output tracking management on nonlinear systems. Using feedback linearization, control inputs with known control gains are 1st synthesized by well-modeled dynamics of the system, and Taylor series enlargement is used to rework unknown non-affine dynamics into the corresponding affine forms. Fuzzy logic systems (FLS) are introduced to estimate the unknown nonlinearity of the remodeled affine system and the saturation nonlinearity due to the actuator constraint. The control inputs equivalent to nonlinearity are constructed based on the estimations. By introducing a sturdy control term, estimation errors and external disturbances are well handled, therefore as to ensure the stability when tracking the control process. The control gain estimation obtained by FLS is modified to avoid singularity. Lyapunov stability analysis is performed to derive the adaptive law. To validate the effectiveness of the proposed management scheme, we have a tendency to apply it to a greenhouse climate management drawback. The ventilation rate within the greenhouse model is unknown; therefore, it's estimated by FLS. The simulation exhibits satisfactory results, in that the temperature and humidity inside the greenhouse are well tracked.

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