Computational Intelligence and Optimization Methods for Control Engineering

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Blondin, Maude Josée (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Pardalos, Panos M. (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Sanchis Sáez, Javier (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2019.
• Έκδοση: 1st ed. 2019.
• Σειρά: Springer Optimization and Its Applications, 150
• Θέματα: Calculus of variations.; Control engineering.; Robotics.; Mechatronics.; Microprogramming .; System theory.; Calculus of Variations and Optimal Control; Optimization.; Control, Robotics, Mechatronics.; Control Structures and Microprogramming.; Systems Theory, Control.

 This volume presents some recent and principal developments related to computational intelligence and optimization methods in control. Theoretical aspects and practical applications of control engineering are covered by 14 self-contained contributions. Additional gems include the discussion of future directions and research perspectives designed to add to the reader's understanding of both the challenges faced in control engineering and the insights into the developing of new techniques. With the knowledge obtained, readers are encouraged to determine the appropriate control method for specific applications. 

 Foreword -- Preface. - Control engineering from classical to intelligent control theory - An overview (Blondin, Sáez, Pardalos) -- Main metaheuristics used for the optimization of the control of the complex systems (Borne, Gharbi) -- Optimal controller parameter tuning from multi/many objective optimization algorithms (Altinoz) -- Fuzzy and neuro-fuzzy control for smart structures (Tairidis, Stavroulakis) -- Computational intelligence in the desalination industry (Cabrera, Carta) -- Control of complex biological systems utilizing the neural network predictor (Bamgbose, Li, Qian) -- A real-time big-data control-theoretical framework for cyber-physical-human systems (Gusrialdi, Xi, Qu, Simaan) -- Distributed optimization based control on the example of microgrids (Braun, Sauerteig, Worthmann) -- Coherency estimation in power systems: A Koopman operator approach (Chamorro, Ordonez, Peng, Gonzalez-Longatt, Sood) -- Appliance identification through non-intrusive load monitoring in residences (Gogos, Georgiou) -- Management suggestions for process control of semiconductor manufacturing: An operations research and data science perspective (Khakifirooz, Fathi, Chien, Pardalos) -- Feedback control algorithms for the dissipation of traffic waves with autonomous vehicles (Monache, Liard, Rat, Stern, Bhadani, Seibold, Sprinkle, Work, Piccoli) -- Disturbance rejection run-to-run controller for semiconductor manufacturing (Khakifirooz, Fathi, Pardalos) -- Energy management improvement based on fleet learning for hybrid electric buses (López-Ibarra, Herrera, Milo, Gaztañaga, Camblong). .