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Hybrid intelligent systems for pneumatic sequential circuit design: Hybridizing genetic algorithms and rule-based logic programming

机译:用于气动顺序电路设计的混合智能系统:混合遗传算法和基于规则的逻辑编程

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Logic synthesis is an important step in process design and automation. Electronics witnessed tremendous improvements in the reliability of automatically designed circuits with reduced lead time with the application of logic synthesis in circuit design. Industrial process automation systems using hydraulic and pneumatic circuits need logic synthesis to obtain proper sequence of process operations. Deterministic approaches have been used for decades to aid in logic synthesis. These approaches are limited by the volume of data that could be handled because of phenomena like exponential explosion. This paper presents an approach based on hybrid intelligence for logic synthesis for industrial automation systems using pneumatic sequential circuits. The proposed logic synthesis system starts with the sequence of operations as its input and generates the truth table required for the pneumatic circuit for performing the given set of operations. The proposed system hybridizes rule based logic programming and genetic algorithms and is capable of solving considerably difficult problems through an evolutionary strategy. Case studies are presented to demonstrate the capability of the proposed approach for logic design for pneumatics based industrial automation.
机译:逻辑综合是过程设计和自动化中的重要一步。在电路设计中应用逻辑综合技术后,电子产品见证了自动设计电路可靠性的极大提高,并缩短了交货时间。使用液压和气动回路的工业过程自动化系统需要逻辑综合,以获取适当的过程操作顺序。确定性方法已经使用了数十年,以辅助逻辑综合。由于诸如指数爆炸之类的现象,这些方法受到可以处理的数据量的限制。本文提出了一种基于混合智能的方法,用于使用气动时序电路的工业自动化系统的逻辑综合。所提出的逻辑综合系统以操作序列作为其输入开始,并生成气动回路执行给定操作集所需的真值表。所提出的系统将基于规则的逻辑编程和遗传算法混合在一起,并且能够通过进化策略解决相当困难的问题。案例研究表明了所提出的方法在基于气动的工业自动化中进行逻辑设计的能力。

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