自适应神经元学习控制(ANELC)策略的研究

本文提出一种针对机械加工中具有非周期扰动的给定信号周期重复的自适应神经学习控制策略（ＡＮＥＬＣ）。采用自适应控制与神经元学习相结合的方法。采用超稳定理论进行了稳定性的证明，仿真表明，ＡＮＥＬＣ有较高的跟踪精度和抗干扰能力。     

Polymerization of filled propylene: A new principle for formation of conducting composites

A new approach to the formation of electrically conducting polymeric materials has been formulated. It is based on the phenomenon of pressure-induced injection of charge carriers from conducting particles into dielectric media. This process has been recently discovered by the authors. In practice, this approach can be accomplished by synthesizing macromolecules of proper dielectric next to the surface of a conducting filler. The experiments supporting the validity of the main assumptions are used to provide a background for the “polymerization filling” concept. The application of this principle makes it possible to obtain systems with larger specific conductivity than with the usual “blended” composites.