Modern computer-based control systems are able to collect a large amount of information, display it to operators and store it in databases but the interpretation of the data and the subsequent decision making relies mainly on operators with little computer support. This book introduces developments in automatic analysis and interpretation of process-operational data both in real-time and over the operational history, and describes new concepts and methodologies for developing intelligent, state-space-based systems for process monitoring, control and diagnosis.

The book brings...

Modern industrial processes and systems require adaptable advanced control protocols able to deal with circumstances demanding "judgement" rather than simple "yes/no," "on/off" responses: circumstances where a linguistic description is often more relevant than a cut-and-dried numerical one. The ability of fuzzy systems to handle numeric and linguistic information within a single framework renders them efficacious for this purpose.

Fuzzy Logic, Identification and Predictive Control first shows you how to construct static and dynamic fuzzy models using the numerical data...

A typical plant control system will be subject to the undesirable influence of exogenous commands and disturbances. In order to track and reject these Professor Isidori and his co-authors have designed a feedback control system based on embedding a model of these disturbances within the controller itself - the so-called "internal model."

Beginning with a review of the fundamental principles of internal-model-based feedback control design, Robust Autonomous Guidance moves on to expound recent enhancements to such designs and then to their implementation in systems operating...

Foresight can be crucial in process and production control, production-and-resources planning and in management decision making generally. Although forecasting the future from accumulated historical data has become a standard and reliable method in production and financial engineering, as well as in business and management, the use of time series analysis in the on-line milieu of most industrial plants has been more problematic because of the time and computational effort required.

The advent of intelligent computational technologies such as the neural network and the genetic...

Many process control books focus on control design techniques, taking the construction of a process model for granted. Process Modelling for Control concentrates on the modelling steps underlying a successful design, answering questions like:

How should I carry out the identification of my process in order to obtain a good model?

How can I assess the quality of a model with a view to using it in control design?

How can I ensure that a controller will stabilise a real process sufficiently well before implementation?

What is the most efficient method of...

Covering all aspects of this important topic, this work presents a review of the main control issues in wind power generation, offering a unified picture of the issues surrounding its optimal control. Discussion is focused on a global dynamic optimization approach to wind power systems using a set of optimization criteria which comply with a comprehensive group of requirements including: energy conversion efficiency; mechanical reliability; and quality of the energy provided.