Real Time Implementation of GHNN-PI Based ACM Controlled Self-Tuning FS-SNIBB Converter

Synchronous buck-boost DC to DC converters are more often used for automotive battery chargers, industrial computer power supplies, and USB power delivery. This research investigation proposes a real-time implementation of an adaptive control of a four switch synchronous non inverting buck boost converter based on GHNN-PI. The proposed control scheme is capable of automatically tuning the system parameters for optimal performance without requiring prior knowledge of the load characteristics. The system incorporates a PI controller and GHNN to form a hybrid controller, which enables better tracking and disturbance rejection capabilities. The implementation of this synchronous Buck-boost converter included a pair of control loops comprising the inner current and also outer voltage controllers. This paper proposes a GHNNPI algorithm to optimize the self-adaptive controller for automatic line voltage and load control on Buck Boost Converter. Using the GHNNPI algorithm, area control error e(t) values are applied to eliminate the voltage fluctuation issue experienced by DC converters. To enhance the stability of the model a suitable Lyapunav function is employed. To validate the controller's performance is analyzed by converter system has been examined to various load, line and reference variations using MATLAB/Simulink. The exhibited the simulation's results are endorse its practicality of the GHNN-PI algorithm by implementing the 100W rated power prototype FS-SNIBB Converter Hardware setup in real-time. Results from hardware experiments and simulations demonstrate that the suggested GHNN-PI based ACM controller offers better tracking performance, reduced overshoot, and faster transient response under varying reference voltage, load and input voltage conditions.