Modeling, Identification, and Control for Cyber- Physical Systems Towards Industry 4.0

Paolo Mercorelli, Weicun Zhang, Hamidreza Nemati, YuMing Zhang, Paolo Mercorelli, Weicun Zhang, Hamidreza Nemati, YuMing Zhang

• Publisher: Academic Press
• Year: 2024
• Print ISBN:
  9780323952071
• eBook ISBN:
  9780323952088
• Topic: Technology & Engineering
• Subtopic: Artificial Intelligence (AI) & Semantics
• Index: Technology & Engineering

Modeling, Identification, and Control for Cyber-Physical Systems Towards Industry 4.0 studies and analyzes the role of algorithms in identifying and controlling such a system towards Industry 4.0, which is the digital transformation of manufacturing and related industries and value creation processes. This book focuses on the conception and implementation of intelligent algorithms. It will help readers who work on sensors, virtual sensors, actuators and virtual actuators embedded systems, network infrastructures, servers with computing and storage capacity, autonomous computing software, real-time data processing, and database graphical user interfaces wireless networking technologies. Cyber-Physical Systems are network components that coordinate physical actions with each other. These autonomous systems perceive their surroundings using virtual sensors and actively influence them via virtual actuators. Adaptable and continuously evolving, these systems free up skilled workers to perform complex tasks, avoiding productivity loss and re-work. - Provides the new and cutting-edge research and development and a series of guidance procedures for potential applications from academic research to industrial R&D - Focuses on the conception and implementation of intelligent algorithms - Covers a wide spectrum of topics, including sensors, virtual sensors, actuators and virtual actuators embedded systems, network infrastructures, servers with computing and storage capacity, autonomous computing software, real-time data processing, and database graphical user interfaces wireless networking technologies

Table of contents

• Cover image
• Title page
• Table of Contents
• Copyright
• Dedication
• Epigraph
• Contributors
• Biography
• Preface
• Chapter 1: Industry 4.0 more than a challenge in modeling, identification, and control for cyber-physical systems
• Part I: Manufacturing as a challenge in Industry 4.0 process
• Introduction
• Chapter 2: Advanced ice-clamping control in the context of Industry 4.0
• Chapter 3: Temperature control in Peltier cells comparing sliding mode control and PID controllers
• Chapter 4: A Digital Twin for part quality prediction and control in plastic injection molding
• Part II: Motion control and autonomous robots as a challenge in Industry 4.0 process
• Introduction
• Chapter 5: SLAM algorithms for autonomous mobile robots
• Chapter 6: Optimization of motion control smoothness based on Eband algorithm
• Chapter 7: Modeling a modular omnidirectional AGV developmental platform with integrated suspension and power-plant
• Chapter 8: Control system strategy of a modular omnidirectional AGV
• Chapter 9: Mecanum wheel slip detection model implemented on velocity-controlled drives
• Chapter 10: Safety automotive sensors and actuators with end-to-end protection (E2E) in the context of AUTOSAR embedded applications
• Part III: Motion and control of autonomous unmanned aerial systems as a challenge in Industry 4.0 process
• Introduction
• Chapter 11: Multibody simulations of distributed flight arrays for Industry 4.0 applications
• Chapter 12: Recent advancements in multi-objective pigeon inspired optimization (MPIO) for autonomous unmanned aerial systems
• Chapter 13: U-model-based dynamic inversion control for quadrotor UAV systems
• Chapter 14: Nonlinear control allocation applied on a QTR: the influence of the frequency variation
• Part IV: Theoretical and methodological advancements in disturbance rejection and robust control
• Introduction
• Chapter 15: Active disturbance rejection control of systems with large uncertainties
• Chapter 16: Gain scheduling design based on active disturbance rejection control for thermal power plant under full operating conditions
• Chapter 17: Active disturbance rejection control of large-scale coal fired plant process for flexible operation
• Chapter 18: Desired dynamic equational proportional-integral-derivative controller design based on probabilistic robustness
• Index