Robust self-tuning regressive adaptive controller design for a DC–DC BUCK converter

This paper demonstrates Robust Adaptive Control (RAC) approach using a technique for system identification applied to a Buck (step-down) converter by PWM (Pulse width modulation) in the presence of input voltage variations, load variations, parametric variations and high variance noises. Maintaining stability margins and closed-loop regulation within a pre-determined range of operating condition is the main objective behind designing feedback loops. The proposed control technique omits the need for mathematical model of the system by using a black-box identification procedure. Due to the various disturbing factors on a DC–DC converter, Minimum Degree Pole Placement (MDPP) scheme is proposed as an adaptive control technique, which is optimized with an Improved Exponential Regressive Least identification (IERLS) algorithm. Additionally, to hinder the impact and the uncertainty caused by high variance noise, a robust identification algorithm is introduced. Finally, capability of the proposed method is examined in different operating conditions through simulations and experimental results. •The estimation of parameters values is reached more accurately.•An Identification strategy is presented which handles parametric variations.•Different disturbances are covered by adaptive controller.•The impact of high variance noises is determined by a novel robust estimator.