Welcome A. Prof. Pritesh Shah from Symbiosis International (Deemed University) to be Committee Member!

日期:2020-01-06 点击量:  223次


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A. Prof. Pritesh Shah, Symbiosis International (Deemed University), India


Research Area:

Application of fractional calculus, mechatronics, control system 


Research Experience:


Dr. Pritesh Shah research interests focus on the design and implementation of an advanced controller for various system. In his previous research experience, he had designed and implemented various controller like PID, fuzzy controller, fractional PID controller. These advanced controllers improve the relative stability, transient and steady-state response for most of the systems. For the design of the model based controller, the model of the plant is required. The plant model can be modeled using an empirical method namely system identification. The modeling of various plants was achieved using system identification for open and closed loop system. 

 

A fractional PID (FPID) controller was designed and implemented for real-time complex non-linear system. Mostly, advanced controllers such as the model predictive controller (MPC), sliding mode controller (SMC) and adaptive used to control nonlinear systems. In some cases, a non-linear system is linearized at various operating points and linear controllers are used to controlling the system between these points.  In this work, a fractional PID controller is implemented for a quadruple tank system, which is non-linear as well as a multivariable system.  The results had achieved better responses as compared to other controllers.

 

Most of the challenging task in the design of FPID is tuning of the controller because there are two more parameters to tune as compared to the PID controller. For the tuning of the controller, the Cohort Intelligence (CI) algorithm had applied and designed for various systems

In the complex order calculus, the order of integration and differential is complex number (a+b*i). The complex order controller will be explored for various applications. Also, the modeling of various system may be improved by using the complex order model structure.