Poly͑o-phenylenediamine͒ ͑PoPD͒ has been successfully electropolymerized by cyclic voltammetery on 304 stainless steel from sulfuric acid solution containing o-phenylenediamine monomer. Thin, adherent, and transparent layers of PoPD which have a ladder conductive polymer structure were formed. The layers facilitated the passivation of the stainless steel ͑SS͒ in acid solution. The underlying oxides obtained by aging in acid solution are investigated after peeling off the polymer layers and compared with those formed under polyaniline layers and by applying a constant positive potential. The passive film under PoPD exhibits a superior resistance for pitting in aerated 3% NaCl to other examined passive films. It is shown that the passive film under PoPD has a high Cr content, including other constituents of SS. The film has been characterized as an oxyhydroxide structure. The protection role of PoPD for SS is discussed here.

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This paper proposes a compound control framework for non-affine nonlinear systems facing hysteresis disturbance. The controller consists of linear active disturbance rejection control (LADRC) and backpropagation (BP) neural networks adaptive control. BP neural networks are utilized to arbitrarily approximate the uncertainty nonlinear caused by the deviation of control parameter from its nominal value and LADRC is designed to real-time estimate and compensate the disturbance with vast matched and mismatched uncertainties including unknown internal system dynamic uncertainty and external hysteresis disturbance therein. Combining the adaptive neural networks design with LADRC design techniques, a new dual-channel composite controller scheme is developed herein whereby adaptive neural networks are used as feed-forward inverse control and LADRC as closed-loop feedback control. Furthermore, as compared with a traditional control algorithm, the proposed BP-LADRC dual-channel composite controller can guarantee that the desired signal can be tracked with a small domain of the origin and it is confirmed to be effective under Lyapunov stability theory and MATLAB simulations.

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