The paper presents a super-twisting sliding mode (STSM) regulator with neural networks (NN) of direct power command (DPC) for controlling the active/reactive power of a doubly-fed induction generator (DFIG) using a two-level space vector pulse width modulation (2L-SVPWM). Traditional DPC strategy with proportional-integral (PI) controllers (DPC-PI) has significantly more active/reactive power r...

in spark ignition (si) engines, the accurate control of air fuel ratio (afr) in the stoichiometric value is required to reduce emission and fuel consumption. the wide operating range, the inherent nonlinearities and the modeling uncertainties of the engine system are the main difficulties arising in the design of afr controller. in this paper, an optimization-based nonlinear control law is anal...

This note proposes a novel architecture of integral sliding mode control, in which special “ideal control” part is introduced. incorporates fairly general form internal model to deal with regular (i.e., modeled) persistent disturbances. A key property this complete separation the from design “discontinuous” component controller. In particular, latter designed for systems whose dimension coincid...

This paper deals with the design of a novel neural network based integral sliding mode (NN-ISM) control for nonlinear systems uncertain drift term and effectiveness matrix. Specifically, this extends classical law to case unknown nominal model. The latter is indeed reconstructed by two deep networks capable approximating terms, which are instrumental so-called manifold. In paper, ultimate bound...

in industrial robotic manipulator, due to the presence of quite nonlinear dynamic and structural and nonstructural uncertainties, a precise model is not easily obtained. as a result, designing a controller with a suitable function based on system model is a challenging issue. sliding mode control is a robust control with numerous applications which can overcome the aforementioned uncertainties....