碳纤维纺丝过程的协同智能控制系统研究
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摘要
碳纤维纺丝过程是一个具有高度复杂性的工业过程,其组成环节多样,工作环境各异,整个生产过程随时间变化频繁,相应的产品质量要求高且数量巨大,使得对碳纤维纺丝过程建立可靠、高效、连续的控制体系,成为工程控制领域极具挑战性的任务之一。生物体高效调控机制,是设计新颖的智能化控制算法的灵感来源。碳纤维纺丝过程所具有的高度复杂和行为不确定等特点,以及严格的控制要求和质量要求,与生物体自身的特点相似,具有应用生物启发的智能控制手段的潜力。本论文在生物体神经-内分泌-免疫综合调控体系的基础上,抽象其调节机理设计智能化的协同控制器(体系)及其控制方法,并应用在以碳纤维纺丝过程为典型代表的复杂工业生产过程中,以提高生产过程控制水平,实现生产过程智能化协同运作。本论文的主要贡献如下：
(1)对生物神经-内分泌-免疫综合调控机制进行阐述,重点介绍神经系统与内分泌系统的协调作用,内分泌系统对机体的调控机理和神经系统与免疫系统的互补调节模式,对不同系统之间的具体作用方式进行分析,为下文根据碳纤维纺丝过程不同方面的特点建立多样化的智能协同控制器(体系)提供理论保证。
(2)基于生物体神经-内分泌调节系统的多变量控制机理,抽象智能协同解耦控制策略应用于碳纤维纺丝过程凝固浴多变量控制中,并根据凝固浴的特点将解耦机制推广到多元。该协同智能解耦机制将互相耦合的变量作用完全隔离,而具体算法的复杂度并不高,有利工业生产实践。实验结果表明,相对传统解耦控制方法,所提出的基于神经-内分泌解耦调节机理的协同智能控制方法能够对凝固浴的多个耦合受控变量进行有效的独立控制,且具有良好的过渡过程响应。
(3)基于生物体多级内分泌反馈调节机理,设计内分泌多级反馈协同智能控制体系,针对碳纤维纺丝过程的牵伸工序的工艺要求和设备组成,将其抽象为多个需进行信息交换的工作单元的组合体,从而能够应用所设计的协同智能控制体系。实验结果表明,所提出的多级反馈协同智能控制体系能够有效地将牵伸过程的各个部分联系起来,通过高效的协同调节保证纤维牵伸率的持续稳定。
(4)基于生物体内分泌系统激素调控原理,针对纤维生产过程不易获取精确工作模型的现实情况,以数据驱动思想为基础,嵌入基于激素调控原理的增强环节提出基于激素调控原理的数据驱动智能控制器,并应用于纤维牵伸过程中丝条张力的动态控制。根据激素调控增强单元和数据驱动控制器的不同作用模式,可以引申出具有不同工作特性的数据驱动控制器实例。实验结果表明,该智能控制器有效地提高了数据驱动控制的灵敏度和准确性,有利于被控对象保持在持续稳定的工作状态。
(5)基于生物体神经系统和免疫系统协作模式,针对纤维生产过程对产品分析和整体优化的要求,设计免疫机制增强的神经网络优化模型,提出双向纺丝工艺建模和智能优化方法及其专家系统,形成双向智能优化体系,不仅有助于科研人员对纤维生产过程进行深入研究,而且对纤维生产单位以较小的代价进行合理的制造工艺优化和纤维产品设计,具有积极的意义。
最后,对全文的研究内容进行了总结,指出了目前研究工作中存在的不足,并对该领域下一步的研究方向进行了展望。
The spinning process of the carbon fiber is one of the industrial processes that yield high complexity and high uncertainty. Its components and the corresponding devices differ with the detailed conditions that the whole manufacturing process asks for, and the requirements for the adequate quantity and excellent quality of the as-spun fiber should be met simultaneously. Consequently, these features make the establishment of a reliable, effective and integrated control system for the carbon fiber spinning process a giant task with great challenges. The natural creatures provide inspirations for designing novel intelligent control algorithms. The features that the spinning process of carbon fiber enjoys, e.g. the high complexity and uncertainty, are similar to those in the natural creatures, which reveal the potential of applying bio-inspired control and regulating methods to the manufacturing process. Based on the principle regulating mechanisms of the natural livings and human body, e.g. the neuro-endocrine-immune system, this work makes designing of the intelligent and cooperative controllers and their corresponding algorithms. The generated intelligent schemes can be used in the controlling and optimization of the carbon fiber spinning process or other similar large-scale industrial manufacturing processes so that the control performance of such systems can be raised, and the cooperative mechanisms can also be realized during the production. The main contributions of this thesis lie in:
(1) An introduction of the neuro-endocrine-immune regulation mechanism that has been widely accepted is made. The cooperative mechanisms between the neural system and the endocrine system, the regulating principles of the endocrine system towards the host body and the complementary regulating mode between the neural system and the immune system are the key points in it. The detailed interacting modes among these systems are also analyzed. This part lays a theoretical foundation for building different types of intelligent controllers (systems) for the spinning procedures with features in different working conditions and quality requirements on the basis of such comprehensive bio-inspired regulating mechanism.
(2) An intelligent cooperative decoupling controlling scheme based on the neuroendocrine regulating mechanism for the multivariable tuning is derived to conduct the control of the coagulation bath in the carbon fiber spinning process which also has several variables to be controlled simultaneously. According to the requirements of the coagulation bath, the original decoupling scheme is also expanded to multiple variables. The proposed intelligent cooperative decoupling mechanism has the ability to separate the coupling variables from each other while the detailed decoupling procedure is still kept simple, which brings benefits for the industrial realization of such mechanism. Experiment results show the proposed intelligent cooperative decoupling scheme can maneuver the variables of the coagulation bath independently and effectively, while keeping good transient response at the same time.
(3) A multi-layered intelligent cooperative control scheme based on the endocrine feedback regulation of human body is proposed. The stretching process of the carbon fiber spinning system is taken as the object of the proposed scheme. After analyzing the production requirements and configuration of the stretching process, it can be generalized to a combination of different working units that ask for information exchange among them, which therefore makes it possible to apply the proposed control scheme. Experiment results show that the proposed multi-layered intelligent cooperative control scheme can connect the different parts of the stretching process together with efficiently, and a long-term stability of the stretching ratio can therefore be guaranteed through the cooperative regulation.
(4) The natural endocrine regulation principle is taken as the foundation of a series of novel intelligent controllers, and a data-driven intelligent controller based on such mechanism is proposed to solve the controlling problem of the spinning process whose accurate model is difficult to acquire. The proposed controller roots from the idea of data-driven control but also embedded with an endocrine regulating module as an enhancement. Meanwhile, a series of instances of such kind of intelligent controller can be deducted due to the different working modes. Experiment results on the stretching process of the fiber production indicate that the proposed controller raise the agility and accuracy of the original data-driven controller, which is beneficial for maintaining the target plant at a stable working status for long time.
(5) A bi-directional process modeling and intelligent optimizing approach with its expert system for spinning production is proposed based on the cooperative mechanism of the neural system and immune system. This model has not only the potential of acquiring reasonable configurations for the spinning process, but also the ability to conduct prediction and assessment for the produced fiber products. Such computerized solution provides the academicians with a useful tool for analyzing the details of the fiber production, meanwhile has great meaning for the fiber manufacturing unit and related people to optimize the production techniques and design new fiber products at a lower cost.
Finally, a conclusion is made for the whole contents of this dissertation with the disadvantages of the current work being noted, and the perspectives of this field for the next step have also been discussed.
(1)对生物神经-内分泌-免疫综合调控机制进行阐述,重点介绍神经系统与内分泌系统的协调作用,内分泌系统对机体的调控机理和神经系统与免疫系统的互补调节模式,对不同系统之间的具体作用方式进行分析,为下文根据碳纤维纺丝过程不同方面的特点建立多样化的智能协同控制器(体系)提供理论保证。
(2)基于生物体神经-内分泌调节系统的多变量控制机理,抽象智能协同解耦控制策略应用于碳纤维纺丝过程凝固浴多变量控制中,并根据凝固浴的特点将解耦机制推广到多元。该协同智能解耦机制将互相耦合的变量作用完全隔离,而具体算法的复杂度并不高,有利工业生产实践。实验结果表明,相对传统解耦控制方法,所提出的基于神经-内分泌解耦调节机理的协同智能控制方法能够对凝固浴的多个耦合受控变量进行有效的独立控制,且具有良好的过渡过程响应。
(3)基于生物体多级内分泌反馈调节机理,设计内分泌多级反馈协同智能控制体系,针对碳纤维纺丝过程的牵伸工序的工艺要求和设备组成,将其抽象为多个需进行信息交换的工作单元的组合体,从而能够应用所设计的协同智能控制体系。实验结果表明,所提出的多级反馈协同智能控制体系能够有效地将牵伸过程的各个部分联系起来,通过高效的协同调节保证纤维牵伸率的持续稳定。
(4)基于生物体内分泌系统激素调控原理,针对纤维生产过程不易获取精确工作模型的现实情况,以数据驱动思想为基础,嵌入基于激素调控原理的增强环节提出基于激素调控原理的数据驱动智能控制器,并应用于纤维牵伸过程中丝条张力的动态控制。根据激素调控增强单元和数据驱动控制器的不同作用模式,可以引申出具有不同工作特性的数据驱动控制器实例。实验结果表明,该智能控制器有效地提高了数据驱动控制的灵敏度和准确性,有利于被控对象保持在持续稳定的工作状态。
(5)基于生物体神经系统和免疫系统协作模式,针对纤维生产过程对产品分析和整体优化的要求,设计免疫机制增强的神经网络优化模型,提出双向纺丝工艺建模和智能优化方法及其专家系统,形成双向智能优化体系,不仅有助于科研人员对纤维生产过程进行深入研究,而且对纤维生产单位以较小的代价进行合理的制造工艺优化和纤维产品设计,具有积极的意义。
最后,对全文的研究内容进行了总结,指出了目前研究工作中存在的不足,并对该领域下一步的研究方向进行了展望。
The spinning process of the carbon fiber is one of the industrial processes that yield high complexity and high uncertainty. Its components and the corresponding devices differ with the detailed conditions that the whole manufacturing process asks for, and the requirements for the adequate quantity and excellent quality of the as-spun fiber should be met simultaneously. Consequently, these features make the establishment of a reliable, effective and integrated control system for the carbon fiber spinning process a giant task with great challenges. The natural creatures provide inspirations for designing novel intelligent control algorithms. The features that the spinning process of carbon fiber enjoys, e.g. the high complexity and uncertainty, are similar to those in the natural creatures, which reveal the potential of applying bio-inspired control and regulating methods to the manufacturing process. Based on the principle regulating mechanisms of the natural livings and human body, e.g. the neuro-endocrine-immune system, this work makes designing of the intelligent and cooperative controllers and their corresponding algorithms. The generated intelligent schemes can be used in the controlling and optimization of the carbon fiber spinning process or other similar large-scale industrial manufacturing processes so that the control performance of such systems can be raised, and the cooperative mechanisms can also be realized during the production. The main contributions of this thesis lie in:
(1) An introduction of the neuro-endocrine-immune regulation mechanism that has been widely accepted is made. The cooperative mechanisms between the neural system and the endocrine system, the regulating principles of the endocrine system towards the host body and the complementary regulating mode between the neural system and the immune system are the key points in it. The detailed interacting modes among these systems are also analyzed. This part lays a theoretical foundation for building different types of intelligent controllers (systems) for the spinning procedures with features in different working conditions and quality requirements on the basis of such comprehensive bio-inspired regulating mechanism.
(2) An intelligent cooperative decoupling controlling scheme based on the neuroendocrine regulating mechanism for the multivariable tuning is derived to conduct the control of the coagulation bath in the carbon fiber spinning process which also has several variables to be controlled simultaneously. According to the requirements of the coagulation bath, the original decoupling scheme is also expanded to multiple variables. The proposed intelligent cooperative decoupling mechanism has the ability to separate the coupling variables from each other while the detailed decoupling procedure is still kept simple, which brings benefits for the industrial realization of such mechanism. Experiment results show the proposed intelligent cooperative decoupling scheme can maneuver the variables of the coagulation bath independently and effectively, while keeping good transient response at the same time.
(3) A multi-layered intelligent cooperative control scheme based on the endocrine feedback regulation of human body is proposed. The stretching process of the carbon fiber spinning system is taken as the object of the proposed scheme. After analyzing the production requirements and configuration of the stretching process, it can be generalized to a combination of different working units that ask for information exchange among them, which therefore makes it possible to apply the proposed control scheme. Experiment results show that the proposed multi-layered intelligent cooperative control scheme can connect the different parts of the stretching process together with efficiently, and a long-term stability of the stretching ratio can therefore be guaranteed through the cooperative regulation.
(4) The natural endocrine regulation principle is taken as the foundation of a series of novel intelligent controllers, and a data-driven intelligent controller based on such mechanism is proposed to solve the controlling problem of the spinning process whose accurate model is difficult to acquire. The proposed controller roots from the idea of data-driven control but also embedded with an endocrine regulating module as an enhancement. Meanwhile, a series of instances of such kind of intelligent controller can be deducted due to the different working modes. Experiment results on the stretching process of the fiber production indicate that the proposed controller raise the agility and accuracy of the original data-driven controller, which is beneficial for maintaining the target plant at a stable working status for long time.
(5) A bi-directional process modeling and intelligent optimizing approach with its expert system for spinning production is proposed based on the cooperative mechanism of the neural system and immune system. This model has not only the potential of acquiring reasonable configurations for the spinning process, but also the ability to conduct prediction and assessment for the produced fiber products. Such computerized solution provides the academicians with a useful tool for analyzing the details of the fiber production, meanwhile has great meaning for the fiber manufacturing unit and related people to optimize the production techniques and design new fiber products at a lower cost.
Finally, a conclusion is made for the whole contents of this dissertation with the disadvantages of the current work being noted, and the perspectives of this field for the next step have also been discussed.
引文
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