Advanced Control of Industrial Processes: Structures and by Piotr Tatjewski

By Piotr Tatjewski

This e-book offers the techniques and algorithms of complex commercial procedure regulate and online optimization in the framework of a multilayer constitution. It describes the interplay of 3 separate layers of approach keep an eye on: direct keep an eye on, set-point keep an eye on, and fiscal optimization. The publication positive aspects illustrations of the methodologies and algorithms by means of labored examples and through result of simulations according to commercial approach types.

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Extra resources for Advanced Control of Industrial Processes: Structures and Algorithms (Advances in Industrial Control)

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In cases of only roughly known abrupt but rare changes in disturbance values), there is an approach which allows to improve optimality of the operating point. It is based on an iterative use of an additional measurement information from the plant and results in the socalled iterative set-point optimizing control algorithms [16]. These algorithms will also be considered in Chapter 4. 1. This time we shall formulate a different optimization objective (b): (b) To optimize the set-points on-line in such a way as to maximize concentration CB (t) in a product stream in the situation of a slowly changing disturbing input FA (t).

58, 155, 111]. The linguistic variables (fuzzy variables) allow to capture roughly defined phenomena better than numerical variables, defined also as crisp variables. For example, the description of a linguistic variable “temperature”, presented in Fig. 1 Takagi-Sugeno (TS) Type Fuzzy Systems 39 on heating appliances (when the temperature is low) or air-conditioning (when the temperature is high). For a specific value of a numerical variable the process of defining its linguistic value together with the appropriate value of the membership function is called fuzzyfication.

This is precisely the place to employ empirical knowledge about the problem, about the character of nonlinearity. Human involvement is here not a drawback of the approach, on the contrary – it is its strong point, as the role of a human expert is well defined. Using expert knowledge is necessary to define a very important specific thing – proper general structure of a fuzzy system. The key is not to precisely define each membership function, but to define the number of these functions and their initial, approximate positioning.

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