Conventional PID controller is a simplest well known controller used in almost all process Industries for controlling the process parameters at desired set value. The tuning of these controllers is done by a classical Zeigler Nichols (ZN) tuning. The dynamics of a spherical tank process is nonlinear in nature and it exhibits non linear behavior and time delays between the inputs and outputs. The ZN tuned PID controller parameters does not cope with all operating points as it exhibits different non linear characteristics at various operating points. This paper aims at real time implementation of enhanced PID controller performance for a nonlinear spherical tank process. The idea is to keep the ZN tuned PID values as the base value so as to fine tune these parameters using a Genetic Algorithm approach to obtain the optimal set of tuning values which can cope up with all operating points. The mathematical model is developed by applying the governing mass balance equations and substituting the arbitrary constants. The system identification of the non linear process is done by black box modeling and found to be (FOPDT) First order plus dead time model. The controller performance of the ZN tuned PID controller is fine tuned using GA based PID controller in terms of time domain specification as well as performance indices. Better enhanced controller performance was obtained for a GA tuned PID controller than that of ZN tuned PID controller at all operating points. All the simulations are carried out in Mat lab environment and the real time implementation is done on a single spherical tank setup in LabVIEW Environment.
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