Abstract
In this paper to test the performance of GA a comparative study has been carried out between PI and PD Controller. The two different objective functions have been chosen that is integral absolute error and integral total absolute error on different generations the controller has been run as a result the minimum value of error has been found in controller in which the objective function was ITAE and a detailed evaluation of Genetic Algorithm has been carried out through out the paper. Optimization and search issues may be solved using genetic algorithms, which are seen as a search process in computers. Global search heuristics are another name for them. Many of these methods are derived from concepts found in evolutionary biology such as mutation, selection, and cross-breeding. For programmes, these algorithms provide a way to automatically enhance their settings. The simulations are tallied to ensure that GA delivers the system promising outcomes.
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