1.

Record Nr.

UNIORUON00454780

Autore

ERENBURG, Il'ja Grigor'evič

Titolo

Portrety russkich poetov / Il'ja Erenburg

Pubbl/distr/stampa

Berlin', : Argonavty, 1922

ISBN

50-202-8506-4

Descrizione fisica

160 p. ; 18 cm.

Disciplina

891.7

Soggetti

POESIA RUSSA - 20. SEC

Lingua di pubblicazione

Russo

Formato

Materiale a stampa

Livello bibliografico

Monografia

2.

Record Nr.

UNINA9910483180103321

Autore

Zhang Ridong

Titolo

Model Predictive Control : Approaches Based on the Extended State Space Model and Extended Non-minimal State Space Model  / / by Ridong Zhang, Anke Xue, Furong Gao

Pubbl/distr/stampa

Singapore : , : Springer Singapore : , : Imprint : Springer, , 2019

ISBN

981-13-0083-6

Edizione

[1st ed. 2019.]

Descrizione fisica

1 online resource (xv, 137 pages) : illustrations

Disciplina

629.8

Soggetti

Systems theory

Mathematical optimization

Control and Systems Theory

Systems Theory, Control

Calculus of Variations and Optimal Control; Optimization

Energy Efficiency

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia



Nota di contenuto

Introduction -- Model Predictive Control Based on Extended State Space Model -- Predictive Functional Control Based on Extended State Space Model -- Model Predictive Control Based on Extended Non-Minimal State Space Model -- Predictive Functional Control Based on Extended Non-minimal State Space Model -- Model Predictive Control Under Constraints -- PID Control Using Extended Non-minimal State Space Model Optimization -- Closed-loop System Performance Analysis -- Model Predictive Control Performance Optimized by Genetic Algorithm -- Industrial Application -- Further Ideas on MPC and PFC Using Relaxed Constrained Optimization.

Sommario/riassunto

This monograph introduces the authors’ work on model predictive control system design using extended state space and extended non-minimal state space approaches. It systematically describes model predictive control design for chemical processes, including the basic control algorithms, the extension to predictive functional control, constrained control, closed-loop system analysis, model predictive control optimization-based PID control, genetic algorithm optimization-based model predictive control, and industrial applications. Providing important insights, useful methods and practical algorithms that can be used in chemical process control and optimization, it offers a valuable resource for researchers, scientists and engineers in the field of process system engineering and control engineering. .