Due to the natural intermittent nature of wind and solar PV, autonomous wind/PV systems for renewable energy typically require energy storage or other sources of production to form a hybrid system. in this paper objective of the designing of a grid dynamics controller equipped with IGBT based bridge structure for stabilizing various electrical parameters on the grid system while its renewable energy-based grid integration. And the controller has to be designed with modulation technique, for both voltage and current at particular frequency following stabilization which is both simple in implementation and operation. And the comparative analysis of techniques used has to be carried out with AI-based optimization algorithms for studying its effectiveness. The results of the THD % of voltage in the system having no controller was found to be 3.32 %.  in the system having adaptive neural PSO switching of grid dynamics controller, the distortion level came down to 1.96%. The hybrid system with solar wind energy was further integrated with the grid and was analyzed for the rotor angle stability in the two machines. It was concluded that out of the three controls for grid dynamics controller the artificial intelligence-based adaptive neural PSO switching was found to be best with maximum stability of machines.