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Enhancing the Control of Systems and Devices cover

Enhancing the Control of Systems and Devices

Improving Performance, Reliability and Adaptability in Dynamic Environments

by Sheetla Prasad, Vipin Chandra Pal, Mohammad Rashid Ansari

1st Edition

Publisher: Academic Press

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Book Details

Print ISBN9780443302855
eText ISBN9780443302862
PublisherAcademic Press
Publishing Year2026
Edition1st Edition
LanguageEnglish
Pages436

Enhancing the Control of Systems and Devices, 1st Edition, examines advanced control design strategies structured to improve system performance, operational reliability, and environmental adaptability. Written by Sheetla Prasad, Vipin Chandra Pal, and Mohammad Rashid Ansari, the book investigates how Industry 4.0 technologies and artificial intelligence contribute to modern control strategies across dynamic settings.

The volume addresses manufacturing control across several core domains, including robotics, automation, machining, and flexible process systems. Through explicit technical analysis, the text presents machine learning-based adaptive control techniques that enable operating systems to adjust effectively to new scenarios and changing environmental conditions.

With the central system scope established, the volume highlights machine learning-based adaptive control as a defining feature of modern process management. This text provides targeted analytical material for researchers, engineers, and practitioners seeking to optimize control strategies throughout process environments.

Table of Contents

  1. Chapter 1: Introduction: Foundations of Advanced Control Design in Process Engineering

  2. Chapter 2: Fundamentals of Control Systems in Process Engineering

  3. Chapter 3: Linear Model Predictive Control: Concepts and Applications

  4. Chapter 4: Robust Adaptive Control: Theory and Application

  5. Chapter 5: Scalability of the Nonlinear Control Scheme with its Efficacy Analysis

  6. Chapter 6: Reduced order modelling based on Sub-optimal control design of Bicycle Robot

  7. Chapter 7: Neural Network-observer based Adaptive Finite-time Frequency Control of Cyber-physical Power Systems

  8. Chapter 8: Machine Learning-based Adaptive Control

  9. Chapter 9: Distributed Adaptive Fault-tolerant Consensus Control of Multi-agent Systems with Deception attacks

  10. Chapter 10: Perception and Planning of Autonomous Vehicle Driving

  11. Chapter 11: Sensor Data Fusion: Techniques and Practical Applications

  12. Chapter 12: Cybersecurity Measures and its Mitigation

  13. Chapter 13: EYE on HMI is a Comprehensive Framework Designed to Track Human Machine Interfaces in Control Areas

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