Több mint 4 millió cím angol és más nyelveken! Fedezd fel új történetedet még ma!

Advances in Process Control with Real Applications

Name: Advances in Process Control with Real Applications
Brand: Elsevier Science
SKU: 9780443238574
Price: 97509 HUF
Availability: InStock

Szerző: Ch. Venkateswarlu

Nyelv:

Kötés: Puha kötésű

Kiadó: Elsevier Science

Elérhetőség: Beszállítói készleten

Küldés 14-21 napon belül

97 509 Ft

Advances in Process Control with Real Applications presents various advanced models for the control...

Információk a könyvről

Szerző

Ch. Venkateswarlu

Nyelv

Angol

Kötés

Könyv - Puha kötésű

Kiadva

2025

oldal

350

EAN

9780443238574

ISBN

044323857X

Enbook ID

46189270

Kiadó

Elsevier Science

Súly

450

Méretek

191 x 235

Teljes leírás

Advances in Process Control with Real Applications presents various advanced models for the control of nonlinear complex processes, including first principle, data driven and artificial intelligence type of models as well as inferential state estimation & stochastic and evolutionary optimization techniques. The book highlights the significance and importance of advanced controllers with several real applications concerning chemical and biochemical processes. It presents control approaches such as generalized predictive control (GPC) with and without constraints, linear & nonlinear model predictive control (MPC), dynamic matrix control (DMC), nonlinear control such as generic model control (GMC), globally linearizing control (GLC) and nonlinear internal model control (NIMC), optimal & optimizing control, inferential control, intelligent control based on fuzzy reasoning, neural network, machine learning and evolutionary computation.

Describes a broad range of advanced control strategies with several real applications to various processes
Highlights the formulation and design of different controllers are based on first principle, data driven and artificial intelligence type of models
Incorporates inferential estimation and nature inspired optimization as an integral part of various model-based controllers