摘要：The Phase Plane Divisional Control (PPDC) applies different actions in the phase plane, according to error and error rate, to make the control system satisfy the control requirement. This control structure makes the system possess the characteristics of closed-open loop. Furthermore, just as the PID control, it s unnecessary to build up a mathematical model for the controlled object. This paper combines Neural Network (NN) inverse model with PPDC to generate a new kind of intelligent controller NN-PPDC. This controller is established in the phase plane, real time corresponding relationships between the basic performance of the system response, not only the action logic division but also acting magnitude. Thus the control parameters in each divisional area can make automatic on-line regulation in accordance with the changes in the controlled object possessing adaptive ability. The simulation and its application in the feed-supporting system for the Square Kilometre Array (SKA) show that the controller designed with this method has better close-loop performance and robustness.

摘要：氧化钼(MoO_(3))是一种具有吸引力的锂离子电池(LIBs)负极材料;然而,其导电性低、锂化后体积膨胀大、锂离子扩散动力学缓慢等特点严重限制了其实际应用.本文中,我们利用高量Mo/N掺杂的碳前驱材料合成了超细的MoO_(3)纳米颗粒(NPs,10–15 nm),所合成的MoO_(3)NPs被限制在原位生成的N掺杂碳网络结构中.这种设计既促进了快速的电子传导,又缩短了锂离子扩散路径;同时,MoO_(3)表面丰富的氮物种和氧缺陷有助于降低锂离子的吸附能垒,这些共同支持了MoO_(3)NPs在高电流倍率下耐久储锂性能的提升.值得注意的是,所获得的NCMoO_(3)纳米复合材料表现出1362 mA h g^(−1)(0.1 A g^(−1))的较高容量,并在10.0 A g^(−1)时保持394 mA h g^(−1)的可逆容量.全电池测试表明:在大倍率5 C下,LiFePO_(4)//NC-MoO_(3)-400电池仍可以输出81 mA h g^(−1)的比容量.我们的工作有望启发其他嵌入导电碳网络的过渡金属氧化物的设计合成及其在LIBs中的实际应用.