Порівняння методів робастно-оптимальних систем керування для технологічних об’єктів із невизначеностями

Автор(и)

  • Н. М. Луцька

Анотація

COMPARISON OF ROBUST-OPTIMAL PROCESS CONTROL SYSTEMS WITH UNCERTAINTY

N. Lutska

Improve product quality and reduce energy costs for food company is directly related to the quality and stability of transients in the system of automatic control. The latter can be achieved by using advanced algorithms synthesis regulators, such as optimal, robust, adaptive and intelligent. Unified approach the selection of a regulator and its setting is not. This is justified by specific control objects and conditions of their operation, so the definition and justification of the relevant regulator is actual problem both in theoretical and practical aspect.

Analysis of recent research and publications. Nowadays, modern control theory offers a wide range of methods and algorithms for the synthesis of the [1] for the objects of uncertainty. Optimal control methods that represented variations, maximum principle and analytical construction of optimal regulators [2] found its development in the best-of robust algorithms [3], and today is an independent theory of synthesis of robust controllers. These controls are designed to work in conditions of substantial uncertainty as parameters and structure of a mathematical model of the object.

The aim of the study. To analyze the modern methods of synthesis of robust controllers for process control objects with uncertainties and develop simulation-based advice on their use.

Materials and methods. All manufacturing facilities in terms of automation is to a greater or lesser extent uncertain. Uncertainties arising from technological objects uncontrolled or unaccounted factors and lead to inadequate assessment of the true value calculation process and improper control actions. They can be divided into several types: uncertainty automation hardware that is malfunctioning presentation and delivery of information; mathematical uncertainty is the uncertainty that arises when describing and calculating mathematical relationships management system.

For example, in the table. 1 shows the main areas of synthesis, robust optimal controllers based on linear control object models, their advantages and disadvantages.

The object management modeled three consistently connected aperiodic links of the first order (an example of such a model can be tube heat exchanger). Uncertainty simulate variable time constants T1, T2, T3 and transmission coefficient ko, structural and multiplicative uncertainty. In the simulation nominal parameters of the object selected: ko = 10; T1-3 = 100 and change them - in the range -50 ... + 50%. In Table. 2 shows the transfer functions of regulators synthesized by different algorithms, which LSh - regulator, synthesized by Glover-MakFarlan method [6]; 2-Ric - regulator, synthesized 2-Riccati approach, Mu - regulator, synthesized algorithm ĩ-synthesis, NSm-pid - proportional-integral-differential (PID) controller, whose parameters are found by nonsmooth synthesis. The structure of the regulator and / or settings found on the criterion of minimum standards Hinf-closed system.

The paper comparing modern methods of robust, optimal control systems for objects with uncertainties. Based on modeling revealed that the best characteristics, such as resistance throughout the range of uncertainties and minimum energy costs have a system of control that is calculated by the algorithm μ-synthesis, however, the system has the highest order of the regulator. Alternatively, you can use the system with a regulator that synthesized 2-Riccati approach that has a low rate of closed system and order the regulator, which is the order of the mathematical model of the object. The controller designed by Glover-McFarlane method should be used when the system are strict requirements in the frequency domain. System of PID-regulator configuration is calculated by the criterion of minimum H∞-norm used effectively only in a small area of uncertainty parameters and structure of the control object model.

Посилання

K. A. Pupkov, N. D. Ehupov. (2004). Metody klassycheskoy I sovremennoy teoryyi avtomatycheskogo upravlenyya [Methods and Modern Classics Automatic management theory]. Moskow: Yzdatel'stvo MHTU ym. N. E. Baumana, 784.

Aleksandrov, A. G. (2003). Optymal'nye i adaptyvnye systemy [Optimal and adaptive systems]. Nauka, 279.

Polyak, B. T. (2002). Robastnaya ustoychyvost' i upravlenye [Robust stability and control]. Nauka, 303.

Sánchez-Peña, Ricardo S. and Mario Sznaier (1998). Robust Systems: Theory and Applications.Wiley, NewYork, 490.

P. Apkarian and D. Noll. (2006). Nonsmooth H-infinity Synthesis. IEEE Transactions on Automatic Control, 51, 1, 71–86.

McFarlane, D. C., K. Glover. (1989). Robust Controller Design using Normalised Coprime Factor Plant Descriptions, Springer Verlag, Lecture Notes in Control and Information Sciences, 181.

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Опубліковано

2017-03-15

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