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Enhancing the Control of Systems and Devices

Improving Performance, Reliability and Adaptability in Dynamic Environments

  • 1st Edition - May 29, 2026
  • Latest edition
  • Editors: Sheetla Prasad, Vipin Chandra Pal, Mohammad Rashid Ansari
  • Language: English

Enhancing the Control of Systems and Devices: Improving Performance, Reliability and Adaptability in Dynamic Environments provides an in-depth exploration of the application of sop… Read more

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Description

Enhancing the Control of Systems and Devices: Improving Performance, Reliability and Adaptability in Dynamic Environments provides an in-depth exploration of the application of sophisticated control design strategies to enhance the control of systems and devices in terms of performance, reliability, and adaptability in dynamic environments. A sophisticated control design strategy refers to the use of advanced and intricate control techniques to achieve specific objectives in complex systems.

Key features

  • Explores how Industry 4.0 technologies and AI contribute to advanced control strategies
  • Examines the interdisciplinary nature of manufacturing control, including aspects of robotics, automation, machining, and flexible process systems
  • Includes real-world examples and case studies that illustrate the application of sophisticated control in the process system
  • Shows how machine learning-based adaptive control allows the system to learn and adapt to new scenarios and conditions

Readership

Researchers, engineers, and practitioners interested in applying and optimizing control strategies for improved performance, reliability, and adaptability in the dynamic and challenging landscape of process environment

Table of contents

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

2. Fundamentals of Control Systems in Process Engineering

3. Linear Model Predictive Control: Concepts and Applications

4. Robust Adaptive Control: Theory and Application

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

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

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

8. Machine Learning-based Adaptive Control

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

10. Perception and Planning of Autonomous Vehicle Driving

11. Sensor Data Fusion: Techniques and Practical Applications

12. Cybersecurity Measures and its Mitigation

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

Product details

  • Edition: 1
  • Latest edition
  • Published: May 29, 2026
  • Language: English

About the editors

SP

Sheetla Prasad

Dr. Sheetla Prasad is an Associate Professor at the Department of Electrical, Electronics and Communication Engineering, Galgotias University, Uttar Pradesh, India. Sheetla Prasad received the bachelor’s degree (B.Tech.) in Electrical and Electronics Engineering from Biju Patnaik University of Technology, Rourkela, India in 2010, the master in technology (M.Tech.) in Power Systems from National Institute of Technology, Tiruchirappalli India in 2012, and the philosophy of doctorate (Ph.D.) degree in Electrical Engineering from Motilal Nehru National Institute of Technology Allahabad, India in 2017 respectively. His research interest includes, sliding mode control, load frequency control, cyber-attacks on automatic generation systems, microgrid operation and control, Intelligent controller design, Multi-terminal DC system power flow control, droop control.

Affiliations and expertise
Associate Professor, Department of Electrical, Electronics and Communication Engineering, Galgotias University, Uttar Pradesh, India

VP

Vipin Chandra Pal

Dr. Vipin Chandra Pal is an Assistant Professor in the Department of Electronics and Instrumentation Engineering, National Institute of Technology Silchar, Assam, India. He has completed his Ph.D. in the area of control systems from Motilal Nehru National Institute of Technology Allahabad, Uttar Pradesh in 2017. He did his M.Tech. (with Gold Medal) in Control & Instrumentation Engineering from the department of Electrical Engineering, Motilal Nehru National Institute of Technology Allahabad, UP in 2012 and B.Tech in Electronics Instrumentation and Control Engineering form Uttar Pradesh Technical University Lucknow, UP in 2006. His research interests include Time delay Systems, Modeling and control of Electric Vehicle, model order reduction, electronic devices and renewable energy applications, Biological Control System.

Affiliations and expertise
Assistant Professor, Department of Electronics and Instrumentation Engineering, National Institute of Technology Silchar, Assam, India

MA

Mohammad Rashid Ansari

Dr. Mohamad Rashid Ansari is a Professor at the Department of Electrical, Electronics and Communication Engineering, Galgotias University, India. He has earned his B.Tech., from, AMU, Aligarh in 2001, M.Tech. (Digital Systems), from MNNIT, Allahabad, in the year 2003 and completed his Ph.D. from Jamia Millia Islamia (A Central University) in 2019. He is having more than twenty years of teaching and research experience. His areas of interest include Control Systems, Artificial Intelligent, Network-on-Chip, Digital Signal Processing and Image Processing.

Affiliations and expertise
Department of Electrical, Electronics and Communication Engineering, Galgotias University, Uttar Pradesh, India