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ZnO nanoarray were synthesized by hydrothermal method on Co2+-doped Zn1-xCoxO (x（mol%）=0.00, 0.01, 0.02, 0.03, 0.04, 0.05) seed layers pre-coated on ITO substrate. The effects of different Co2+ doping concentrations on morphology and photoelectric properties of ZnO nanoarray including transient photo-current and charge transfer resistance were investigated. The addition of Co2+ in the seed layer could perfect the oriented growth of ZnO nanoarray and apparently enhance its photo current. FESEM observation confirmed that the ZnO nanoarray were grown in the way perpendicular to ITO substrate along the direction of (002). Meanwhile, UV-vis tests shown that the band gap energy was decreased from 3.37 eV to 3.16 eV due to Co2+ doping and the ZnO nanoarray had a strong visible region in the range 400-650 nm. The transient photo-current was found to vary from 0.005 to 0.15 mA/cm2 under AM 1.5G simulated sunlight illumination. Photoelectric properties was correlated with the recombination of photo-generated charge carriers, which was inhibited with optimal Co2+ doping concentrations and was beneficial for application in perovskite solar cells.

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To meet the progressively stringent demands for trajectory tracking performance in precision/ultra-precision industry, multiple advanced feedforward compensation strategies have been reported in recent years. However, there is no fair and comprehensive performance comparison of advantages and drawbacks of various methods under different industrial working conditions. In this paper, a comparative study of several performance-oriented feedforward strategies represented by standard iterative learning control (ILC), cascaded ILC (CILC), gated recurrent units based feedforward compensation (GRU-FFC), and real-time iterative compensation (RIC) has been systematically conducted by theoretical clarification and experimental verification. Various trajectory tracking tasks are accomplished on a precision mechatronic motion stage, and the tracking performances to be examined include (i) tracking accuracy; (ii) extrapolation capability for non-repetitive trajectories; (iii) disturbance rejection ability. Experimental results are sufficiently summarized with the combination of underlying control mechanism analysis, which can provide a comprehensive and reliable selection guidance of feedforward compensation strategies in different practical industrial scenarios.INDEX TERMS Feedforward compensation, gated recurrent units (GRU), iterative learning control (ILC), precision motion control, real-time iterative compensation (RIC), tracking performance.