Article

Article title ANALYTICAL DESIGN OF AUTOMATION CONTROL SYSTEMS
Authors A.R. Gaiduk, M.Yu. Medvedev, E.A. Plaksienko
Section SECTION VI. AUTOMATION AND CONTROL
Month, Year 06, 2017 @en
Index UDC 519.71
DOI
Abstract Now there are many methods of automatic control systems design, however the majority of them are iterative. As a consequence, design of control systems with necessary performances is accompanied by significant expenses of time. The purpose of this report is to represent the method of analytical design of automation systems with control on output and impacts which allows over-coming the specified difficulty. The designed system has partially given structure, desirable per-formance, lowered dimension and increased robustness. Parameters of a controller are the solu-tions of the linear algebraic equations systems. Standard transfer functions are used for mainte-nance of the desirable quality parameters such as: the astatic orders to reference input and external disturbances; overshoot and time response. The resolvability conditions of the task of the analytical design of automatic control systems, with desirable transfer functions are resulted. These functions are formed according to the required designed automatic control system quality. Increase of robustness is achieved by inclusion of a part of its poles and zeros into the roots of the closed system characteristic polynomial of the automation control systems. The suggested method of analytical design can be applied for creation of the multivariable control systems by technical and moving plants. Efficiency of the analytical design method of the control automation systems are shown on the numerical examples. These methods can be used for creation of the automation control systems with less complex, but more robust for plants of chemical, textile, food and other branches of production and also at creation of systems of special assignment.

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Keywords Plant; control system; design; standard transfer functions; technical pant; performance; astatic; invariant; reduction; robustness.
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