Hybrid Intelligent Systems For Smart Control And Mobile Robotics Hands-On Guide To Fuzzy Logic, Neural Networks, And Evolutionary Techniques For Real World Robotic Systems

Hybrid Intelligent Systems for Smart Control and Robotics
✔️ Edition 2011, 496 pages, English, soft computing, single copy

This book describes how soft computing techniques, fuzzy logic, neural networks, and bio-inspired optimization algorithms, combine to form hybrid intelligent systems for real-world intelligent control and mobile robotics. It is organized into five parts, covering theory, intelligent control, fuzzy controller optimization, time-series prediction, and computer vision in robotics.

✅ 496 pages detailing hybrid intelligent systems with fuzzy logic, neural networks, and evolutionary optimization
✅ Five parts covering theory, intelligent control, fuzzy controller optimization, time-series, and robotics
✅ Practical applications in intelligent control and mobile robotics
✅ English language edition released in 2011, with extensive examples
✅ Focus on real-world problems and hands-on case studies

💡 How can hybrid intelligent systems be applied to smart control in mobile robotics?

This handy answer outlines practical steps to blend fuzzy logic, neural networks, and evolutionary optimization for real-world robotic control and perception.

- Start with a simple fuzzy controller and progressively tune it with evolutionary methods - Use neural networks for state estimation and feature extraction in motion and vision tasks - Integrate these techniques for robust time-series prediction and adaptive planning in dynamic settings ✝️