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Descripción

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

1. Chapter 1 Introduction: Foundations of advanced control design in process engineering - p. 1 2. Chapter 2 Fundamentals of control systems in process engineering - p. 31 3. Chapter 3 Linear model predictive control: Concepts and applications - p. 57 4. Chapter 4 Robust adaptive control: Theory and application - p. 79 5. Chapter 5 Scalability of the nonlinear control scheme with its efficacy analysis - p. 109 6. Chapter 6 Chattering mitigation against system nonlinearities and disturbances using active disturbance prediction-based sliding mode control - p. 135 7. Chapter 7 Reduced-order modeling based on suboptimal control design of bicycle robot - p. 155 8. Chapter 8 Optimal control of hydropower-based microgrid with electric vehicles and wind power integration using linear quadratic regulator and linear matrix inequality techniques for frequency regulation - p. 171 9. Chapter 9 Neural network observer-based adaptive finite-time frequency control of cyber-physical power systems - p. 195 10. Chapter 10 Machine learning-based adaptive control - p. 215 11. Chapter 11 Distributed adaptive fault-tolerant consensus control of multiagent systems with deception attacks - p. 243 12. Chapter 12 Perception and planning of autonomous vehicle driving - p. 273 13. Chapter 13 Sensor data fusion: Techniques and practical applications - p. 297 14. Chapter 14 Cybersecurity measures and their mitigation - p. 321 15. Chapter 15 Data integrity attack mitigation using intelligent control scheme in multiarea power grids - p. 347 16. Chapter 16 EYE-on-HMI is a comprehensive framework designed to track human–machine interfaces in control areas - p. 377 17. Chapter 17 Conclusion and future prospectives - p. 403 18. Index - p. 409

Descripcion
Descripción

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

1. Chapter 1 Introduction: Foundations of advanced control design in process engineering - p. 1 2. Chapter 2 Fundamentals of control systems in process engineering - p. 31 3. Chapter 3 Linear model predictive control: Concepts and applications - p. 57 4. Chapter 4 Robust adaptive control: Theory and application - p. 79 5. Chapter 5 Scalability of the nonlinear control scheme with its efficacy analysis - p. 109 6. Chapter 6 Chattering mitigation against system nonlinearities and disturbances using active disturbance prediction-based sliding mode control - p. 135 7. Chapter 7 Reduced-order modeling based on suboptimal control design of bicycle robot - p. 155 8. Chapter 8 Optimal control of hydropower-based microgrid with electric vehicles and wind power integration using linear quadratic regulator and linear matrix inequality techniques for frequency regulation - p. 171 9. Chapter 9 Neural network observer-based adaptive finite-time frequency control of cyber-physical power systems - p. 195 10. Chapter 10 Machine learning-based adaptive control - p. 215 11. Chapter 11 Distributed adaptive fault-tolerant consensus control of multiagent systems with deception attacks - p. 243 12. Chapter 12 Perception and planning of autonomous vehicle driving - p. 273 13. Chapter 13 Sensor data fusion: Techniques and practical applications - p. 297 14. Chapter 14 Cybersecurity measures and their mitigation - p. 321 15. Chapter 15 Data integrity attack mitigation using intelligent control scheme in multiarea power grids - p. 347 16. Chapter 16 EYE-on-HMI is a comprehensive framework designed to track human–machine interfaces in control areas - p. 377 17. Chapter 17 Conclusion and future prospectives - p. 403 18. Index - p. 409

Indice
Autores
Muestra
Ficha Técnica