Péter Gáspár, Zoltán Szabó, József Bokor

Discrete Feedback Systems 2.

Modern Control

A.12 Constrained Optimization for MPC

At each sampling time the MPC algorithm calls for a solution to a (constrained) optimization problem of the form

subject to some inequality constrains

. In this section, we sketch an iterative method for solving this optimization problem.

Tartalomjegyzék

DISCRETE FEEDBACK SYSTEMS II. Modern Control
COPYRIGHT PAGE
1. Introduction
chevron_rightPART I – State-Space Methods
- chevron_right2. State-Space Analysis
- chevron_right3. State Estimation and Kalman filtering
  - chevron_right3.1. Observers
    - 3.1.1. Controller with Observer
  - chevron_right3.2. The Estimation Problem
    - 3.2.1. Random signals and linear systems
  - chevron_right3.3. The Kalman Filter
  - chevron_right3.4. Bayesian View of State Estimation
    - 3.4.1. The standard Linear Kalman Filter
    - 3.4.2. Nonlinear Kalman Filters
  - chevron_right3.5. The LQG control
    - 3.5.1. The Separation Principle
  - 3.6. LQG: tracking and regulation
- chevron_right4. Model predictive control
  - chevron_right4.1. Prediction models for use in MPC
    - 4.1.1. Cost functions
  - chevron_right4.2. Unconstrained optimization
    - 4.2.1. Unconstrained MPC vs. LQ optinal control
  - chevron_right4.3. MPC with constraints
    - 4.3.1. Quadratic programming
  - 4.4. Closed loop properties of MPC
chevron_rightPart II – System Identification
- chevron_right5. System identification
chevron_rightAppendix
- chevron_rightA. Appendix
Bibliography

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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