集成模块化神经智能控制系统

C. Lin
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引用次数: 1

摘要

针对高性能控制系统的设计,提出了一种基于先进传感器处理和神经模糊控制集成的集成智能控制方法。我们的方法具有以下创新:1)通过神经网络的分布式并行处理、学习和在线再优化特性来解决复杂性和不确定性问题;2)非线性动力学和剧烈耦合可以自然地纳入设计框架;3)模糊系统提供的知识库和决策逻辑导致了人类智能增强的控制方案。此外,该方法还可以容纳容错、健康监测和可重构控制策略,以确保在发生故障、故障和损坏时的稳定性、优雅退化和重新优化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Integrated modular neural intelligent control systems
An integrated intelligent control approach is proposed for the design of high performance control systems based on advanced sensor processing, and neural fuzzy control integration. Our approach features the following innovations: 1) the complexity and uncertainty issues are addressed via the distributed parallel processing, learning, and online reoptimization properties of neural networks; 2) the nonlinear dynamics and the severe coupling can be naturally incorporated into the design framework; and 3) the knowledge base and decision making logic furnished by fuzzy systems leads to a human intelligence enhanced control scheme. In addition, fault tolerance, health monitoring and reconfigurable control strategies can be accommodated by this approach to ensure stability graceful degradation and reoptimization in the case of failures, malfunctions and damage.
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