1.

Record Nr.

UNINA9910349473203321

Autore

Das Sharma Kaushik

Titolo

Intelligent Control : A Stochastic Optimization Based Adaptive Fuzzy Approach / / by Kaushik Das Sharma, Amitava Chatterjee, Anjan Rakshit

Pubbl/distr/stampa

Singapore : , : Springer Singapore : , : Imprint : Springer, , 2018

ISBN

9789811312984

981-13-1298-2

Edizione

[1st ed. 2018.]

Descrizione fisica

1 online resource (XVI, 302 p. 159 illus., 146 illus. in color.)

Collana

Cognitive Intelligence and Robotics, , 2520-1956

Disciplina

006.3

Soggetti

Computational intelligence

Automatic control

Robotics

Mechatronics

Probabilities

Mathematical optimization

Optical data processing

Computational Intelligence

Control, Robotics, Mechatronics

Probability Theory and Stochastic Processes

Optimization

Image Processing and Computer Vision

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di contenuto

Part 1_ Prologue -- Chapter 1. Intelligent Adaptive Fuzzy Control -- Chapter 2. Some Contemporary Stochastic Algorithms: A Glimps -- Chpater 3. Fuzzy Controller Design-I: Stochastic Algorithm Based Approac -- Part II_Lyapunov Strategy Based Design Methodologie -- Chapter 4. Fuzzy Controller Design-II: Lyapunov Strategy Based Adaptive Approac -- Chapter 5. Fuzzy Controller Design-III: Hybrid Adaptive Approache -- Part III_H∞ Strategy Based Design Methodologies -- Chapter 6. Fuzzy Controller Design-IV: H∞ Strategy Based Robust Approac -- Chapter 7. Fuzzy Controller Design-V:



Robust Hybrid Adaptive Approaches -- Part IV _Applications -- Chapter 8. Experimental Study-I: Temperature Control of an Air Heater System with Transportation Delay -- Chapter 9. Experimental Study-II: Vision Based Control of Robot Manipulators -- Chapter 10. Experimental Study-III: Vision Based Navigation of Mobile Robots -- Part V_Epilogue -- Chapter 11. Emerging Areas in Intelligent Fuzzy Control and Future Research Scopes.

Sommario/riassunto

This book discusses systematic designs of stable adaptive fuzzy logic controllers employing hybridizations of Lyapunov strategy-based approaches/H∞ theory-based approaches and contemporary stochastic optimization techniques. The text demonstrates how candidate stochastic optimization techniques like Particle swarm optimization (PSO), harmony search (HS) algorithms, covariance matrix adaptation (CMA) etc. can be utilized in conjunction with the Lyapunov theory/H∞ theory to develop such hybrid control strategies. The goal of developing a series of such hybridization processes is to combine the strengths of both Lyapunov theory/H∞theory-based local search methods and stochastic optimization-based global search methods, so as to attain superior control algorithms that can simultaneously achieve desired asymptotic performance and provide improved transient responses. The book also demonstrates how these intelligent adaptive control algorithms can be effectively utilized in real-life applications such as in temperature control for air heater systems with transportation delay, vision-based navigation of mobile robots, intelligent control of robot manipulators etc.