Péter Gáspár, Zoltán Szabó, József Bokor

Discrete Feedback Systems 2.

Modern Control


Model predictive control

With availability of fast computers and microprocessors Model Predictive Control (MPC) schemes are increasingly finding application in many engineering domains such as robotics, automobiles and aerospace industries. Major strengths of MPC are abilities to handle multivariable interactions and operating constraints in systematic manner. Origins of MPC can be traced to the classical LQ optimal control and it is formulated as a constrained optimization problem, which is solved on-line repeatedly by carrying out model based forecasting over a moving window of time.

Discrete Feedback Systems 2.

Tartalomjegyzék


Kiadó: Akadémiai Kiadó

Online megjelenés éve: 2019

ISBN: 978 963 454 373 2

The classical control theory and methods that we have been presented in the first volume are based on a simple input-output description of the plant, expressed as a transfer function, limiting the design to single-input single-output systems and allowing only limited control of the closed-loop behaviour when feedback control is used. Typically, the need to use modern linear control arises when working with models which are complex, multiple input multiple output, or when optimization of performance is a concern. Modern control theory revolves around the so-called state-space description. The state variable representation of dynamic systems is the basis of different and very direct approaches applicable to the analysis and design of a wide range of practical control problems. To complete the design workflow, finally some introduction into system identification theory is given.

Hivatkozás: https://mersz.hu/gaspar-szabo-bokor-discrete-feedback-systems-2//

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