摘要：AbstractDC-DC step-down/buck converters are prominent part of DC power supply system. The dynamics of DC-DC step down converter are nonlinear in nature and are largely influenced from both parametric and external load perturbations. Under its closed loop operation, obtaining a precise output voltage tracking besides satisfactorily inductor current response is a challenging control objective. In this regard, this article proposes a novel Laguerre neural network estimation technique for the approximation of unknown and uncertain load function, followed by its subsequent compensation in the adaptive backstepping controller. A detailed design of the proposed estimator and adaptive backstepping controller along with closed loop asymptotic stability have been presented. Further, the proposed control mechanism is evaluated through extensive numerical simulations while subjecting the converter to input voltage, reference voltage and load resistance perturbations. Furthermore, the results are verified by testing the proposed controller on a laboratory prototype with DSP based TM320F240 controller board. The transient performance metrics such as settling time and peak overshoot/undershoot are evaluated and compared against adaptive backstepping control and PID control methods. Finally, the analysis of results reveals that the proposed control methodology for DC-DC step down converter offers a faster transient output voltage tracking with smooth and satisfactory inductor current response over a wide operating range.
