Enhancing the Control of Systems and Devices

Nyhet

Improving Performance, Reliability and Adaptability in Dynamic Environments

Häftad, Engelska, 2026

Av Sheetla Prasad, Vipin Chandra Pal, Mohamad Rashid Ansari

2 349 kr

Kommande

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.

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

Produktinformation

Utgivningsdatum2026-03-01
Mått152 x 229 x undefined mm
Vikt450 g
FormatHäftad
SpråkEngelska
Antal sidor250
FörlagElsevier Science
ISBN9780443302855

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Energiteknik inom Naturvetenskap och teknik

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.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. 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.

1. Introduction: Foundations of Advanced Control Design in Process Engineering2. Fundamentals of Control Systems in Process Engineering3. Linear Model Predictive Control: Concepts and Applications4. Robust Adaptive Control: Theory and Application5. Scalability of the Nonlinear Control Scheme with its Efficacy Analysis6. Reduced order modelling based on Sub-optimal control design of Bicycle Robot7. Neural Network-observer based Adaptive Finite-time Frequency Control of Cyber-physical Power Systems8. Machine Learning-based Adaptive Control9. Distributed Adaptive Fault-tolerant Consensus Control of Multi-agent Systems with Deception attacks10. Perception and Planning of Autonomous Vehicle Driving11. Sensor Data Fusion: Techniques and Practical Applications12. Cybersecurity Measures and its Mitigation13. EYE on HMI is a Comprehensive Framework Designed to Track Human Machine Interfaces in Control Areas