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Power-steering control architecture for automatic driving.

, , , , and . IEEE Trans. Intell. Transp. Syst., 6 (4): 406-415 (2005)

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Optimal fuzzy control system using the cross-entropy method. A case study of a drilling process., , and . Inf. Sci., 180 (14): 2777-2792 (2010)Embedded Fuzzy Control System: Application to an Electromechanical System., , , and . International Conference on Computational Science, volume 2658 of Lecture Notes in Computer Science, page 812-821. Springer, (2003)Industrial cyber-physical system for condition-based monitoring in manufacturing processes., , , and . ICPS, page 637-642. IEEE, (2018)Intelligent Models for Predicting the Thrust Force and Perpendicular Vibrations in Microdrilling Processes., , , , and . ICTAI, page 506-511. IEEE Computer Society, (2014)Application of hybrid incremental modeling for predicting surface roughness in micromachining processes., , , and . CIES, page 54-59. IEEE, (2014)Optimal Fuzzy Control for a Time-Delay System Using Simulated Annealing: An Application to High-Performance Drilling., , and . ICNC (5), page 639-643. IEEE Computer Society, (2007)Embedded Fuzzy Control System in an Open Computerized Numerical Control; A Technology Transfer Case-Study., , , , and . IFSA, volume 2715 of Lecture Notes in Computer Science, page 442-449. Springer, (2003)A Distributed Intelligent Monitoring System Applied to a Micro-scale Turning Process., , and . IWANN (2), volume 5518 of Lecture Notes in Computer Science, page 338-345. Springer, (2009)Transductive-Weighted Neuro-Fuzzy Inference System for Tool Wear Prediction in a Turning Process., , , and . HAIS, volume 5572 of Lecture Notes in Computer Science, page 113-120. Springer, (2009)Dynamic Model of the Machining Process on the Basis of Neural Networks: From Simulation to Real Time Application., , , , and . International Conference on Computational Science (3), volume 2331 of Lecture Notes in Computer Science, page 574-583. Springer, (2002)