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Autor(en): 
  • Simon G. Fabri
  • Visakan Kadirkamanathan
  • Functional Adaptive Control: An Intelligent Systems Approach 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  September 2012  
    Genre:  Naturwissensch., Medizin, Technik 
     
    Artificial Intelligence / C / Control and Systems Theory / Control engineering / engineering / Mechanical Engineering
    ISBN:  9781447110903 
    EAN-Code: 
    9781447110903 
    Verlag:  Springer Nature EN 
    Einband:  Kartoniert  
    Sprache:  English  
    Serie:  Communications and Control Engineering  
    Dimensionen:  H 235 mm / B 155 mm / D  
    Gewicht:  450 gr 
    Seiten:  266 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    The field of intelligent control has recently emerged as a response to the challenge of controlling highly complex and uncertain nonlinear systems. It attempts to endow the controller with the key properties of adaptation, learn­ ing and autonomy. The field is still immature and there exists a wide scope for the development of new methods that enhance the key properties of in­ telligent systems and improve the performance in the face of increasingly complex or uncertain conditions. The work reported in this book represents a step in this direction. A num­ ber of original neural network-based adaptive control designs are introduced for dealing with plants characterized by unknown functions, nonlinearity, multimodal behaviour, randomness and disturbances. The proposed schemes achieve high levels of performance by enhancing the controller's capability for adaptation, stabilization, management of uncertainty, and learning. Both deterministic and stochastic plants are considered. In the deterministic case, implementation, stability and convergence is­ sues are addressed from the perspective of Lyapunov theory. When compared with other schemes, the methods presented lead to more efficient use of com­ putational storage and improved adaptation for continuous-time systems, and more global stability results with less prior knowledge in discrete-time sys­ tems.

      
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