Modeling, Identification, and Control for Cyber- Physical Systems Towards Industry 4.0. Emerging Methodologies and Applications in Modelling, Identification and Control

Table of Contents

1. Industry 4.0 more than a challenge in modelling, identification, and control for cyber-physical systems Part I: Manufacturing as a challenge in industry 4.0 process 2 Advanced Ice Clamping Control in the Context of Industry 4.0 3 Temperature Control in Peltier Cells Comparing Sliding Mode Control and PID Controllers 4 A Digital Twin for Part Quality Prediction and Control in Plastic Injection Molding Part II: 2 Motion control and autonomous robots as a challenge in industry 4.0 process 5 SLAM Algorithms For Autonomous Mobile Robots 6 Optimization of Motion Control Smoothness Based on Eband Algorithm 7 Modelling a Modular Omni-directional AGV Developmental Platform with Integrated Suspension and Power-plant 8 Control System Strategy of a Modular Omni-directional AGV 9 Mecanum wheel slip detection model implemented on velocity-controlled drives 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 11 Multibody Simulations of Distributed Flight Arrays for Industry 4.0 Applications 12 Recent Advancements in Multi-Objective Pigeon Inspired Optimization (MPIO) for Autonomous Unmanned Aerial System 13 U-Model Based Dynamic Inversion Control for Quadrotor UAV systems 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 15 Active Disturbance Rejection Control of Systems with Large Uncertainties 16 Gain Scheduling Design Based on Active Disturbance Rejection Control for Thermal Power Plant under Full Operating Conditions 17 Active disturbance rejection control of large-scale coal fired plant process for flexible operation 18 Desired Dynamic Equational Proportional-Integral-Derivative Controller Design Based on Probabilistic Robustness

Authors

Paolo Mercorelli Professor (Chair), Control and Drive Systems, Institute of Product and Process Innovation, Leuphana University of Lueneburg, Lueneburg, Germany. Paolo Mercorelli received his MS degree (Laurea) in Electronic Engineering from the University of Florence, Italy, in 1992, and Ph.D. degree in Systems Engineering from Alma Mater Studiorum University of Bologna, Italy, in 1998. He was awarded the Marie Sklodowska-Curie Actions Research Fellowship sponsored by the European Commission in 1998, and spent time in the ABB (Asea Brown Boveri) Corporate Research Heidelberg until 2001. From 2002 to 2005, he was a Senior Researcher with the Institute of Automation and Informatics, Wernigerode, Germany. From 2005 to 2011, he became Associate Professor of Process Informatics at Ostfalia University of Applied Sciences, Wolfsburg, Germany. There, he was involved in various projects with the Volkswagen AG Research Center. Since 2012, he has been a distinguished Full Professor (Chair) of Control and Drive Systems at the Institute of Product and Process Innovation, Leuphana University of Lueneburg, Lueneburg, in Germany, and has recently obtained an International Distinguished Visiting Professor Fellowship at the Institute of Automatic Control of Lodz University of Technology, in Poland. Weicun Zhang Associate Professor, School of Automation and Electrical Engineering, University of Science and Technology, Beijing, China. Weicun Zhang is an associate professor at the School of Automation and Electrical Engineering, University of Science and Technology, in Beijing. He obtained his MSc degree in Automatic Control (1989) from the Beijing Institute of Technology and the PhD in Control Theory and Applications (1993) from Tsinghua University, P. R. China. From 1997 to 1998, he was a visiting research fellow in the Industrial and Operations Engineering Department, University of Michigan at Ann Arbor, and from 2006 to 2007 was a visiting professor in the Department of Electrical and Computer Engineering, Seoul National University, South Korea. His research interests include self-tuning adaptive control, multiple model adaptive control, and estimation for both linear and nonlinear dynamic systems. As representative research work, he established the Virtual Equivalent System (VES) theory for unified analysis of self-tuning control systems and other model based complex control systems. Prof. Zhang is the Editor-In-Chief for International Journal of Cybernetics and Cyber-Physical Systems. Hamidreza Nemati Lecturer, Avionics and Control, Engineering Design and Mathematics Department, University of the West of England (UWE), Bristol, UK. Hamidreza Nemati is a lecturer in avionics and control at the Engineering Design and Mathematics Department of the University of the West of England (UWE), Bristol, in the UK. His work focuses on autonomous navigation and intelligent control of cyber-physical systems in harsh environments. He previously served as Research Associate at Lancaster University, Lancaster, UK, working on robotic mobility and navigation for decommissioning and demolishing processes in nuclear facilities funded by the Engineering and Physical Sciences Research Council (EPSRC) via National Centre for Nuclear Robotics (NCNR). Hamidreza is a founder of 'Vickers Robotics & AI' and is trying to display great curiosity and attempts to fit his diverse experience into a clear understanding of the world. YuMing Zhang Professor, University of Kentucky, Lexington, Kentucky, USA. YuMing Zhang is a Full Professor at the University of Kentucky, Lexington, Kentucky, in the USA. He received his BS and MS degrees in control major from Harbin Institute of Technology (HIT), China where he finished his PhD degree in welding major in 1990. He has over 200 Journal Papers and 12 US Patents, with his expertise including advanced sensing, control, learning/modelling, and intelligent robotic systems with application to real-time monitoring and control of innovative welding processes, human-robot collaborative systems, and intelligent welding robots. He is currently an Editor for the Journal of Manufacturing Processes. He is a Fellow of the American Welding Society (AWS), American Society of Mechanical Engineers (ASME), and Society of Manufacturing (SME).