Control system structure

This collects information from the plant and the environment, and processes it into a form suitable for the cognition subsystem. The essential elements are  

Cognition in an intelligent eontrol system is eoneerned with the deeision making proeess under eonditions of uneertainty. Key aetivities inelude  

This ehapter is mainly eoneerned with some of the proeesses that are eontained within the eognition subsystem. 

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Fig. 10.1 Intelligent control system structure (adapted from Johnson and Picton).

Then in Chaps. 7 and 8 we will look at closedloop systems. Instrumentation hardware, controller types and performance, controller tuning, and various types of control systems structures will be discussed. 

Despite all these changes in hardware, the basic concepts of control system structure and control algorithms (types of controllers) remain essentially the same as they were thirty years ago. It is now easier to implement control structures wc just reprogram a computer. But the process control engineers joh is the same come up with a control system that will give good, stable, robust control. 

Also covered in this chapter will be some guidelines for developing an appropriate control system structure for a single unit and for a group of units that form a plant. Several realistic examples will be presented. 

After the variables are selected, the structure of the controller itself is chosen. This determines which manipulated variables are changed and on which errors the changes are based. Proper control system structuring can have a significant effect on its reliability. In industry, strategies that work well all the time provide more benefits than those that work optimally but are frequently on manual control. 

The next part is the determination of the control system structure. We must decide what variables to control and manipulate and how these should be paired. The control structure is vitally important because a poor strategy will result in poor performance no matter what type of control algorithm we use or how much we tune it. There is little information or guidance in the literature or in process control textbooks (both introductory and advanced) on how to develop an effective control structure for an entire complex chemical plant. This is the main subject of this book. 

In figure 2 there is presented the proposed control system structure for load balancing control for two parallel passes furnaces. The control system for load balancing in the atmospheric distillation unit furnace must accomplish the following functions ... 

The third level is control system structure—determining what to control, what to manipulate, and how to match one controlled variable with one manipulated variable (called pairing ). The selection of the control structure for a plant is a vitally important function. A good choice of structure makes it easy to select an appropriate algorithm and to tune. No matter what algorithm or tuning is used, it is very unlikely that a poor structure can be made to give effective control. 

The choices of the control system structure, the type of controller, and the tuning of the controller are all important engineering decisions. 

In designing a neural network control system, one must select the overall structure of the system and decide which components will utilize neural network algorithms. Several examples of control system structures are provided below, each of which utilizes one or more neural networks as described above. This section of the chapter provides a brief overview of some neural control systems that have potential for application in biomedical control systems. For excellent, thorough reviews of recent developments in neural network control systems, the reader is referred to Miller [1990b] and White and Sofge [ 1992]. 

FIGURE 12.2 Direct inverse control system structure. 

FIGURE 12.4 Indirect adaptive control system structure. 

FIGURE 12.5 Adaptive critic control system structure. 

Perhaps the central issue to be resolved by the new theories of chemical process control is the determination of the control system structure. .. and it is the burden of new theories to invent ways both of asking and answering the questions in an efficient and organized marmer. ... 

The required electrical interlock reliabilities comprise the interlock schedule from which the coarse control system structure is derived (Fig 2). Those channels based upon programmable logic, including associated input sensing devices and output actuators are considered in detail in the following sections. 

Figure 3 Fuelling Machine Control System Structure...

Imrhan, S.N., 80-12 In vitro cartilage wear studies, 50-11-50-15 Incus (anvil), 5-2 Indirect adaptive control system structure, 12-5 Indirect measurement, of... 

Respiratory chemoreceptors, 7-12 Respiratory control system structure, 11 -2-11 -5 chemical plant in, 11-2-11-4 control object in, 11 -5 mechanical plant in, 11 -4-11 -5... 

Self-tuning regulator models, in respiratory control system structure, 11-12 Sellick, P.M., 63-9 Semantic compaction language representation methods, 72-3... 

Superior colliculus, 4-4 Supervised control system structure, 12-4... 

There exists in the literature, and in the heads of experienced engineers, a body of knowledge about good practices process configurations, hardware installation, control system structure, and so on. Part II of this book tries to assemble this kind of information for distillation columns. 

In Chapter 1 we suggested a control system structure in which most control loops are vided into three classes (1) material balance, (2) product quality, and (3) constraints. If we look at these loops from the standpoint of classic single-loop theory, we see that the material-balance loops function as low-pass filters (slow dynamics) while the product-quality loops function as bandpass or high-pass filters (faster dynamics). 

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