Abstract:
Now a day’s controlling Industrial Processes are very tedious one when considering the disturbances and delays. Industries have employed PID control for the processes and are trying to improve the performance of the process. Even then there are still some drawbacks in the performance of these controllers. Here in this paper we have proposed the fractional order PID for an industrial process. In Normal PID, the controllers current value of the state x (t+1) is depends upon the previous value x (t).In FOPID, the controller current value of the state x (t+1) depends upon all the previous state values. Fractional order PID has shown better results when comparing to integer PID’s in recent days. We are implementing the FOPID for the process and compare the results with Integer PID controller. Industrial data is collected, Collected data is fitted to the transfer function model set of the various parametric system identification models. The simulation is performed in MATLAB environment using System Identification toolbox. We have found the model of the process using this system identification tool and it is almost identical to the ideal model of the plant. The model identification process is used here to identify the system’s nature using identification in the process; and then a proper controller has to be implemented to control the process variable. So we have Implemented Conventional PID and FOPID and their performances were analyzed for the Kiln process.

Keywords: Process control, nonlinear dynamics, nonlinear process control, System identification process, fractional order, mat lab