£115.87

Springer - Intelligent Control: Stochastic Optimization Book

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Description

Explore advanced methodologies in control theory with 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 detailed look at the systematic design of stable adaptive fuzzy logic controllers. By utilizing hybridizations of Lyapunov strategy-based approaches and H infinity theory-based approaches, this book offers a deep dive into contemporary stochastic optimization techniques. It demonstrates how to integrate candidate methods such as Particle Swarm Optimization (PSO), Harmony Search (HS) algorithms, and Covariance Matrix Adaptation (CMA) with established Lyapunov or H infinity theory. This hybridization process is designed to develop robust control strategies for complex systems. This resource is essential for researchers and professionals looking to combine classical stability theories with modern optimization algorithms to improve adaptive fuzzy logic control performance.

Key Features

Covers systematic designs for stable adaptive fuzzy logic controllers using hybrid approaches.

Integrates Lyapunov strategy-based and H infinity theory-based methodologies.

Demonstrates the use of Particle Swarm Optimization (PSO) in control strategies.

Includes Harmony Search (HS) algorithms and Covariance Matrix Adaptation (CMA) techniques.

Part of the specialized Cognitive Intelligence and Robotics book series by Springer.

Focuses on the hybridization of stochastic optimization with established control theories.

Product Specifications

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

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No barcode data available

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