Integrated PID-type Learning and Fuzzy Control for Flexible-joint Manipulators
Journal of Intelligent and Robotic Systems
Fuzzy Variable Structure Control of a Class of Nonlinear Sampled-Data Systems
Journal of Dynamical and Control Systems
Neural Network Control for Visual Guidance System of Mobile Robot
ICANNGA '07 Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part II
Neural Network Mapping of Magnet Based Position Sensing System for Autonomous Robotic Vehicle
ICANNGA '07 Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part II
Image technology for camera-based automatic guided vehicle
PSIVT'06 Proceedings of the First Pacific Rim conference on Advances in Image and Video Technology
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Intelligent control is the discipline in which control algorithms are developed by emulating certain characteristics of intelligent biological systems. It is quickly emerging as a technology that may open avenues for significant advances in many areas. In fact, fueled by advancements in computing technology, it has already achieved some very exciting and promising results. Here, the author argues that a mixture of intelligent and conventional control methods may be the best way to implement autonomous control systems