What Are Detective Controls?
Inferential control is an important method of process control. It was proposed by Brosilow and Tong of the United States in 1978. It is a new design method of univariate inference controller. The control designed by this method The device has the characteristics of simple algorithm, good convergence and strong robustness, etc. [1] has achieved satisfactory results in practical applications. There are applications in many different fields, such as industrial production, medical.
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- Because fuzzy control does not require a mathematical model of the object, it can be applied to non-linear, time-varying complex objects and multivariable systems, and it can use multiple evaluation indicators in the control process, and it is easy to change the control principle. The fuzzy control summarized by the operator's skills can exert its specialties in many fields. In addition, artificial intelligence and expert systems can also be applied in the formulation of inference principles, and the intelligence of expert systems can be combined with the skills of skilled workers. With the rapid development of automation today, fuzzy control is bound to get more applications, and more attention from control workers.
- Overview
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- A metafunction is regarded mathematically as a set, that is, a set that represents a degree of "uncertainty", which is called a "fuzzy set". The boundary of a fuzzy set is uncertain. The certainty is fundamentally different from the certainty in probability theory or statistics. Probability represents the uncertainty rate before an event, but it becomes a certain value after the event. However, the metafunction is uncertain even after the event.
- Fuzzy control is a kind of feedback control based on fuzzy theory. In practice, fuzzy theory is used to perform calculations in the regulator section. Fuzzy control is suitable for multi-variable and non-linear control. It does not need to obtain the characteristics of the object and can achieve better results than traditional control. This is the biggest feature of fuzzy control. But fuzzy control requires considerable calculations, which are daunting for conventional analog instruments. Therefore, only when using the DCS system and computer, the conditions for fuzzy control of industrial objects can be achieved. Fuzzy control is a kind of approximate reasoning control, which has several characteristics of human thinking. Based on a series of fuzzy knowledge and data, that is, under a certain prerequisite, the control actions of the control process are considered in a unified manner, and conclusions that are consistent with the reality and logical relationship can be derived. IF A and B, THEN C are inference languages often used in fuzzy control. Because the prerequisites in fuzzy control are obtained by the measurement sensors, they are certain values. The result of the inference is sent to the execution unit as the operating variable of the control system. Therefore, the result of the inference should also be a determined value. Because the only place where ambiguity can be reflected is in the precondition itself, fuzzy control is to apply fuzzy theory to fuzzy inference under some uncertain preconditions to get a certain result. Therefore, the inference itself often contains both definite and vague components. If the output should increase or decrease under certain special conditions, it is generally determined, but how much should be increased or decreased, and the execution speed are all summarized based on the experience of the operator. Sex is, to a certain extent, ambiguous. Fuzzy control is suitable for theoretical and empirical reasoning, and is usually used for control problems related to human judgment and feeling, as well as control systems that are difficult to establish mathematical models, and is used in situations where conventional PID control is not ideal.