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Diabetes is a general illness regularly contaminated in people. Numerous approaches to recognize diabetes, one of them is checking circulatory strain, however, along these lines isn't compelling, in light of the fact that it takes blood first and takes a ton of time. Iridology is a one-way investigation wellbeing dependent on the iris. In this manner, we need an apparatus used to recognize pancreatic harm as a sign of diabetes through iridology. TheBurden picture is the initial step to distinguish pancreatic organs dependent on the iris. The eye picture that we utilized as the info framework originates from the eye facility database. The subsequent stage is a versatile middle sifting utilized in the process preprocessing to lessen the commotion on the picture. After that, the subsequent stage is a division process utilizing Hough circle change technique. The consequences of division will be standardized and take the Region of intrigue. Return for money invested will be done element extraction by utilizing GLCM (Gray Level Co-Occurrence Matrix). To know the state of a pancreas organ utilizing back propagation strategy.

A simple relay feedback method is proposed for the identification and control of Wiener-type nonlinear processes. Wiener-type processes comprise a linear dynamic subsystem followed by a nonlinear static element. A linear dynamic subsystem is identified from the shape of the output curve. If the dynamics are not captured then the order of the subsystem is improved. The nonlinear static function is identified by the simple least square estimation (LSE) method. This method avoids the iterative procedure. The inverse static nonlinearity is also obtained by the LSE method. The Wiener-model-based nonlinear control strategy is used to compensate the nonlinear dynamics of the process, so that the controller parameters can be determined by the usual tuning rules developed for linear processes. Two important parameters are obtained through relay feedback test (RFT): amplitude of the periodic output (k u ) and the ultimate period (p u ). Proportional integral (PI) parameters are obtained directly from these two parameters. This proposed method is designed to adapt easily with the real-time processes. Finally, simulated and experimental results are given to validate the proposed method. 

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