Data‐driven robust backstepping control of unmanned surface vehicles

Summary In this article, a novel data‐driven robust backstepping control (DRBC) approach for tracking of unmanned surface vehicles (USVs) with uncertainties and unknown parametric dynamics has been developed. Main contributions are fourfold: (a) Unlike previous approaches, within the DRBC scheme, backstepping decoupled technique and data‐driven sliding‐mode control (DSMC) can be effectively cohered. (b) Using backstepping philosophy, a new data‐driven PI‐type sliding‐mode surface is devised, such that strong robustness with simple structure can be ensured. (c) Complex unknowns including couplings, uncertainties and parametric dynamics are sufficiently lumped, and are totally compensated by the extended state observer. (d) The entire DRBC scheme eventually achieves accurate tracking of USVs with strong couplings, uncertainties and unknown parametric dynamics. The efficacy and superiority of the proposed DRBC approach is validated on a prototype USV.