88FN02B-E GJR2370800R0200脉冲输入模块卡件

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88FN02B-E GJR2370800R0200脉冲输入模块卡件

新一代DCS继续向智能化、开放型方向发展。一些“标准化”的策略软件，以适当的模块方式,组合应用于DCS之中，增强了系统性能。DCS的技术进步，使DCS厂家除提供比值、串级、前馈、PID等基本控制软件外，还提供了一些先进过程控制(APC)软件。如Honey-well公司将HMPC多变量预估控制器作为应用模块组合在TDC23000DCS系统中。日本横河公司CENTUM系统控制策略中,包含了自整定控制、顺序控制、批量控制、预估控制和模糊逻辑控制等等。
2 控制技术发展新方向 2.1 多变量预估控制多变量预估控制器（RMPC）可由多输入多输出、基于模型的、有预估能力和优化功能组成，能够控制和优化高度耦合的石化生产过程。RMPC控制器与要控制的工业过程相结合，根据预估将来情况并决定怎样调节控制器输出把所有被控变量保持在设定的点上或约束范围内。多变量控制在石化行业中应用范围可从蒸馏塔的双组分控制到FCCU两器和主分馏塔的燃烧、苛刻度和产品回收控制,近年在天然气加工、合成氨生产、时滞焦化分馏塔产品控制、加氢裂化、渣油加氢处理等领域中也有诸多应用。 2.2 智能控制随着社会生产的迅速发展，控制科学面临着越来越多的挑战，例如，要实现对越来越复杂且具有不确定性的对象进行有效的控制，要求所设计的控制系统具有学习能力、强鲁棒性、实时性和柔性结构，以及自组织与并行处理等智能化信息处理能力，这就是智能控制。人工神经元网络由于具有学习能力、自适应、自组织、容错与自修复等能力，使它在控制领域中的应用收到了高度的重视，神经控制已成为智能控制的一个重要发展方向[3]。化工生产过程中pH中和过程是一类有代表性的复杂化工过程，不同情况下，溶液pH值相对于加料量的变化非常大，具有明显的非线性，
而且，在实际的反应过程中还存在混合、测量等时滞环节，更加重了这一过程的复杂程度，传统的非线性PID控制能将问题转化到线性区域，然而一旦对象特性发生小的变化，已经整定好的非线性补偿环节就很难抵消pH过程的非线性特性影响，基于此，可将PID控制器与神经元控制器相结合，用一个神经元实现变结构PID控制器中结构变化的部分，同时用另一个神经元实时调整PID控制器的参数，从而解决该问题。 2.3 人工介入控制石油化工的生产过程是一个复杂的人机综合系统，在这个系统中，人、原材料、设备、工艺和环境是组成这个系统的基本要素[4]，人在这个系统中起主导作用。尽管系统的自动化程度提高了，但是还要由人来控制操作，要由人来负责设计、制造、组织、管理、维修、训练，要由人来决策，因此研究人与机器、人与环境及机器与环境之间的相互关系，把人的因素作为系统设计的重要条件和原则，为系统研究提供一种新的理论依据和方法。一般计算机和控制技术在石化公司的应用可分为两大部分：一是管理部分，即管理信息系统（MIS）；二是生产过程控制部分。人工介入控制系统的实质是监督控制，其重要功能在于优化操作，结合石化企业运营实际，可将人工介入生产过程分为以下几个过程：装置监督控制与优化、优化控制与先进控制、中央控制人员、常规过程控制、巡回检查人员以及生产过程。通过采用计算机和通信技术，对石油化工生产过程的作业人员进行管理，将生产过程的人员监控管理和过程控制融为一体。在石油化工生产过程中引入人工介入控制系统，可以达到优化操作，提高企业经济效益的目的。 2.4 统计过程控制统计过程控制即SPC，主要是指应用统计分析技术对生产过程进行实时监控，科学的区分出生产过程中产品质量的随机波动与异常波动。随着客户的要求越来越苛刻，竞争对手的水平越来越高，如何保持过程生产中的稳定，使质量不合格的产品越少越好成为石化企业的当务之急。SPC主要是通过各种控制图来达到进行质量分析、质量控制和质量改进的目的。SPC的核心工具是控制图，如计量型控制图(平均值-极差图、平均值-标准差图等)和计数型控制图(不合格品率图、缺陷数图、单位缺陷数图等)等，用来直接控制生产过程，进行质量诊断和质量改进，在生产过程中起到了预防为主的作用，正所谓：检验是一种浪费，只有预防才会创造价值。The new generation DCS continues to develop in the direction of intelligence and openness. Some "standardized" strategy software is combined and applied in DCS in an appropriate module way, which enhances the system performance. With the technical progress of DCS, the DCS manufacturer provides not only basic control software such as ratio, cascade, feedforward and PID, but also some advanced process control (APC) software. For example, Honeywell combines HMPC multivariable predictive controller as application module in TDC23000DCS system. The control strategy of CENTUM system of Yokogawa Corporation of Japan includes self-tuning control, sequence control, batch control, predictive control and fuzzy logic control.

2 New direction of control technology development 2.1 Multivariable predictive control The multivariable predictive controller (RMPC) can be composed of multiple inputs and multiple outputs, model-based, predictive and optimization functions, and can control and optimize highly coupled petrochemical production processes. The RMPC controller is combined with the industrial process to be controlled. According to the estimated future situation, it decides how to adjust the controller output to keep all controlled variables at the set point or within the constraint range. Multivariable control can be applied in petrochemical industry from two-component control of distillation tower to combustion, caustic scale and product recovery control of FCCU and main fractionator. In recent years, it has also been widely used in natural gas processing, synthetic ammonia production, delayed coking fractionator product control, hydrocracking, residue hydrotreating and other fields. 2.2 Intelligent control With the rapid development of social production, control science is facing more and more challenges. For example, to achieve effective control of increasingly complex and uncertain objects, the designed control system is required to have learning ability, strong robustness, real-time and flexible structure, as well as intelligent information processing capabilities such as self-organization and parallel processing. This is intelligent control. Due to its learning ability, self adaptation, self-organization, fault tolerance, self repair and other capabilities, the application of artificial neural network in the control field has received high attention, and neural control has become an important development direction of intelligent control [3]. The pH neutralization process in chemical production is a typical complex chemical process. Under different circumstances, the pH value of the solution changes greatly with respect to the feeding amount, which has obvious nonlinearity,
In addition, in the actual reaction process, there are also time delay links such as mixing and measurement, which aggravates the complexity of this process. The traditional nonlinear PID control can transform the problem into a linear area. However, once the object characteristics change slightly, it is difficult for the set nonlinear compensation link to offset the impact of the nonlinear characteristics of the pH process. Based on this, the PID controller can be combined with the neuron controller, One neuron is used to realize the structure change part of the variable structure PID controller, and another neuron is used to adjust the parameters of the PID controller in real time to solve this problem. 2.3 The manual intervention control of petrochemical production process is a complex man-machine integrated system, in which people, raw materials, equipment, process and environment are the basic elements of the system [4], and people play a leading role in the system. Although the degree of automation of the system has been improved, people still have to control the operation, design, manufacture, organization, management, maintenance and training, and make decisions. Therefore, the study of the relationship between people and machines, people and the environment, and machines and the environment takes human factors as the important conditions and principles of system design, providing a new theoretical basis and method for system research. The application of general computer and control technology in petrochemical companies can be divided into two parts: one is the management part, that is, management information system (MIS); The second is production process control. The essence of the manual intervention control system is supervision and control, and its important function is to optimize operation. Combined with the actual operation of petrochemical enterprises, the manual intervention production process can be divided into the following processes: plant supervision and control and optimization, optimization and advanced control, central control personnel, conventional process control, patrol inspection personnel, and production process. Through the use of computer and communication technology, the operators in the petrochemical production process are managed, and the personnel monitoring management and process control in the production process are integrated. The introduction of manual intervention control system in the petrochemical production process can achieve the purpose of optimizing operation and improving the economic benefits of enterprises. 2.4 Statistical process control Statistical process control (SPC) mainly refers to the application of statistical analysis technology to monitor the production process in real time and scientifically distinguish the random fluctuation and abnormal fluctuation of product quality in the production process. With the increasingly demanding requirements of customers and the higher level of competitors, how to maintain the stability in the process of production and make the number of unqualified products less and better has become a top priority for petrochemical enterprises. SPC is mainly used for quality analysis, quality control and quality improvement through various control charts. The core tools of SPC are control charts, such as metering control charts (average range chart, average standard deviation chart, etc.) and counting control charts (nonconforming product rate chart, defect number chart, unit defect number chart, etc.), which are used to directly control the production process, carry out quality diagnosis and quality improvement, and play a preventive role in the production process. It is the so-called: inspection is a waste, and only prevention can create value.