Optimization of PID controllers using ant colony and genetic algorithms / / Muhammet Unal ... [et al.]

• Pubblicazione: Berlin ; ; New York, : Springer, c2013
• Edizione: 1st ed. 2013.
• Descrizione fisica: 1 online resource (XX, 88 p.)
• Disciplina: 629.8
• Soggetto topico: PID controllers - Mathematics; Ant algorithms; Genetic algorithms
• Altri autori: UnalMuhammet
• Note generali: Bibliographic Level Mode of Issuance: Monograph
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Artificial Neural Networks -- Genetic Algorithm -- Ant Colony Optimization (ACO) -- An Application for Process System Control.
• Sommario/riassunto: Artificial neural networks, genetic algorithms and the ant colony optimization algorithm have become a highly effective tool for solving hard optimization problems. As their popularity has increased, applications of these algorithms have grown in more than equal measure. While many of the books available on these subjects only provide a cursory discussion of theory, the present book gives special emphasis to the theoretical background that is behind these algorithms and their applications. Moreover, this book introduces a novel real time control algorithm, that uses genetic algorithm and ant colony optimization algorithms for optimizing PID controller parameters. In general, the present book represents a solid survey on artificial neural networks, genetic algorithms and the ant colony optimization algorithm and introduces novel practical elements related to the application of these methods to process system control.
• Titolo autorizzato: Optimization of PID Controllers Using Ant Colony and Genetic Algorithms
• ISBN: 9783642329005; 3642329004
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910437763903321
• Lo trovi qui: Univ. Federico II
• Serie: Studies in computational intelligence ; ; v. 449.