Titlebook: Computational Intelligence and Optimization Methods for Control Engineering; Maude Josée Blondin,Panos M. Pardalos,Javier Sanch Book 2019

BOOST

Energy Management Improvement Based on Fleet Digitalization Data Exploitation for Hybrid Electric Badded to the routes to simulate “real” road and daily operation conditions. This data is used for monitoring the energetic key performance factors by learning from the buses with the best energetic behavior. Finally, a decision-making process is applied to improve the local energy management of the

反叛者

冬眠

1931-6828 reader with future directions and insights into developing .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 c

陶器

https://doi.org/10.1007/3-540-29983-1 cutting-edge steps in wafer fabrication is selected for illustrating the power of disturbance rejection algorithm for compensating the misalignment. Along with this case study, some classification of disturbance rejection control algorithm with the structure of control plant is discussed.

浮雕

Disturbance Rejection Run-to-Run Controller for Semiconductor Manufacturing, cutting-edge steps in wafer fabrication is selected for illustrating the power of disturbance rejection algorithm for compensating the misalignment. Along with this case study, some classification of disturbance rejection control algorithm with the structure of control plant is discussed.

大炮

完整

,Ma?regeln der Besserung und Sicherung,ations, the chapter focuses on four intelligent control techniques, which are fuzzy logic control, neural networks, metaheuristics control tuning, and multi-agent systems. Perspective and new trends of research are also exposed for each presented control technique as well as for control systems in general.

一再煩擾

https://doi.org/10.1007/978-3-540-89064-5heir applicability, their efficiency, and their robustness. In other words, the controllers can be designed based on intuition and basic engineering principles, and then they can be subjected to optimization, e.g., to training/learning using artificial neural networks, in order to achieve certain properties.

無思維能力

grounded

,Control Engineering from Classical to Intelligent Control Theory—An Overview,ations, the chapter focuses on four intelligent control techniques, which are fuzzy logic control, neural networks, metaheuristics control tuning, and multi-agent systems. Perspective and new trends of research are also exposed for each presented control technique as well as for control systems in general.