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Ensuring Observability and Controllability of Complex Technical Systems in Difficult and Irregular Situations When Commands with a Large Distortion Component Are Received

机译:当接收到具有大失真分量的命令时,确保复杂技术系统在困难和不规则情况下的可观察性和可控性

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The article looks at some problems of development of an automated information system. This system carries out monitoring and technical control of complex technical systems at nuclear power plants (NPP) and thermal power plants (TPP). There is substantiated the necessity of using automatic recognition and data synthesis. This improves control when the received command signal is distorted. The control signal can be complicated by the white-noise component. There is offered the development of a software complex, which provides monitoring and analysis of commands, requests, signals for substitution of questionable and unrecognized command signals, received from an unidentified caller via unprotected communication channel. The most similar command is chosen algorithmically from the library of already accumulated commands. In the library the commands are systemized in consideration of the substantiated probability of coincidence and probable damage to the system in case of erroneous command replacement. There are suggested measures to raise the level of software complex safety using neural technologies.
机译:文章介绍了自动信息系统开发的一些问题。该系统执行核电厂(NPP)和热电厂(TPP)的复杂技术系统的监控和技术控制。实质性地实现了使用自动识别和数据合成的必要性。当接收的命令信号失真时,这改善了控制。控制信号可以通过白噪声分量复杂。提供了一种软件复合体的开发,它提供了通过未受保护的通信信道从未识别的通信信道接收的可疑和无法识别的命令信号的命令,请求,用于替换的命令,请求信号的监视和分析。从已经累积的命令库算法算法选择最相似的命令。在图书馆中,在错误的命令替换情况下,考虑到系统的巧合和可能损坏的实质性和可能的​​损坏概率来制定命令。建议使用神经技术提高软件复杂安全水平。

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