£119.09

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Springer Intelligent Control - Stochastic Optimization Book

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Description

Explore advanced control theory in Intelligent Control: A Stochastic Optimization Based Adaptive Fuzzy Approach. Published by Springer as part of the Cognitive Intelligence and Robotics series, this text provides a deep look into the systematic design of stable adaptive fuzzy logic controllers. It focuses on the integration of Lyapunov strategy-based and H infinity theory-based approaches with modern stochastic optimization techniques. Readers will learn how to utilize candidate stochastic optimization methods, including Particle Swarm Optimization (PSO), Harmony Search (HS) algorithms, and Covariance Matrix Adaptation (CMA). By combining these techniques with Lyapunov or H infinity theory, the book demonstrates how to develop hybrid control strategies that improve system stability and performance in complex environments.

Key Features

This Springer publication covers systematic designs for stable adaptive fuzzy logic controllers.

The text explores hybridizations of Lyapunov strategy-based and H infinity theory-based approaches.

Learn to apply stochastic optimization techniques like Particle Swarm Optimization (PSO) and Harmony Search (HS) algorithms.

Detailed instruction on using Covariance Matrix Adaptation (CMA) in conjunction with Lyapunov theory.

Part of the Cognitive Intelligence and Robotics series for specialized engineering study.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
05 September 2018
Listed Since
25 May 2018

Barcode

No barcode data available

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