Enhanced dynamic performance in DC–DC converter‐PMDC motor combination through an intelligent non‐linear adaptive control scheme

A novel neuro-adaptive control scheme is proposed in the context of angular velocity tracking DC–DC buck converter driven permanent magnet DC motor system. The controller builds upon idea backstepping and consists a fast single hidden layer Hermite neural network (HNN) module equipped with on-board (adaptive) learning to counteract unknown non-linear time-varying load torque ensure nominal performance. HNN has simple structure exhibits promising speed accuracy estimating dynamic variations apart from being computationally efficient. method guarantees rapid recovery under parametric non-parametric uncertainties. In order verify performance controller, extensive experimentation been conducted laboratory various real-time scenarios. Results are obtained for start-up, influence highly torque. metrics such as peak undershoot/overshoot settling time computed quantify transient response behaviour. results clearly substantiate theoretical propositions demonstrate an enhanced wide operating regime, thus confirming suitability industrial applications.