About this Research Topic
Intelligent control is an active field of research that brings artificial intelligence and automatic control together to solve complex control problems, such as that in robotics. This family of control techniques and algorithms spanning from traditional ones of fuzzy logic, neurofuzzy to more recent developments in brain-inspired algorithms such as neural network control, evolutionary computation etc. With recent advances in artificial intelligence, the incorporation of machine learning, self-learning and soft computing has brought new insights into this field, especially for systems without available priori mathematical model.
This Research Topic intends to bring in the latest developments in various intelligent control theory and its application to robotics. Topics of interests include but not limited to:
• Brain-inspired algorithms and application in robotic control
• Deep learning, reinforcement learning, and meta learning of autonomous systems;
• Evolved neural networks, Evolutionary fuzzy systems, and Evolved neuro-fuzzy systems;
• Neural network and fuzzy control of autonomous systems;
• Evolutionary control of autonomous systems;
• Intelligent multi-agent control systems in robotics;
• Stability and robustness analysis of intelligent control systems;
• Fuzzy inference systems, artificial neural networks, and genetic algorithms for autonomous systems.
Keywords: Intelligent control, autonomous system, fuzzy system, Brain-inspired algorithm, Robotics
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