| Description |
1 online resource (486 p.). |
| Series |
Emerging Methodologies and Applications in Modelling, Identification and Control Series |
|
Emerging Methodologies and Applications in Modelling, Identification and Control Series.
|
| Note |
Description based upon print version of record. |
| Contents |
Front Cover -- Modeling, Identification, and Control for Cyber-Physical Systems Towards Industry 4.0 -- Copyright -- Dedication -- Contents -- Contributors -- Biography -- Paolo Mercorelli -- Prof. Weicun Zhang -- Hamidreza Nemati -- YuMing Zhang -- Preface -- Objectives -- 1 Industry 4.0 more than a challenge in modeling, identification, and control for cyber-physical systems -- 1.1 Introduction -- 1.1.1 Background and challenging issues -- 1.1.2 Basic concepts of Industry 4.0 -- 1.2 Theoretical background -- 1.2.1 Internet of Things and services -- 1.2.2 Smart manufacturing |
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1.2.3 Vertical integration and networked manufacturing system -- 1.2.4 Marginalization of the network center: towards horizontal integration -- 1.2.5 Cyber-physical system -- 1.2.6 Commercialization of CPS -- 1.2.7 Outcomes of application of CPS -- 1.3 Method and implementation -- 1.3.1 Research process -- 1.3.2 Findings and analysis -- 1.4 Conclusions -- References -- I Manufacturing as a challenge in Industry 4.0 process -- 2 Advanced ice-clamping control in the context of Industry 4.0 -- 2.1 Introduction -- 2.2 Model -- 2.3 Advanced ice-camping structure |
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2.4 Measured results and performance evaluation -- 2.4.1 Performance comparison -- 2.5 Towards intelligent clamping -- 2.6 Towards Industry 4.0 -- 2.7 Conclusions -- Appendix -- References -- 3 Temperature control in Peltier cells comparing sliding mode control and PID controllers -- 3.1 Introduction -- 3.1.1 Sliding mode controller -- 3.1.2 Multi-input multi-output control motivation -- 3.2 Sliding mode control law derivation -- 3.2.1 Simulation results of MIMO SM controller -- 3.3 Experimental validation -- 3.4 Controller extension -- 3.5 Controller comparison |
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3.5.1 PI controller and feedforward regulator -- 3.5.2 Conclusions and comparative measurements between PI and SM controllers -- References -- 4 A Digital Twin for part quality prediction and control in plastic injection molding -- Funding -- 4.1 Introduction -- 4.1.1 Digital Twin -- 4.1.2 Challenges -- 4.1.3 Solution approach -- 4.2 Plastic injection molding -- 4.2.1 Process cycle and machine components -- 4.2.2 Machine setpoints and measured process variables -- 4.2.3 State of the art: process control in injection molding -- 4.3 Data acquisition and management |
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4.3.1 Machine and process values acquisition via OPC UA -- 4.3.2 In-line part quality data acquisition -- 4.4 Control-oriented modeling of final part quality -- 4.4.1 Final part quality prediction -- 4.4.2 Preliminaries -- 4.4.3 Internal dynamics quality model -- 4.4.4 External dynamics quality model -- 4.4.5 Static quality model -- 4.5 Case study: tamper-evident closure quality prediction -- 4.6 Conclusions and outlook -- 4.6.1 Conclusions -- 4.6.2 Outlook -- References -- II Motion control and autonomous robots as a challenge in Industry 4.0 process |
| Note |
5 SLAM algorithms for autonomous mobile robots |
| Added Author |
Zhang, Weicun.
|
|
Nemati, Hamidreza.
|
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Zhang, Yuming.
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| Other Form: |
Print version: Mercorelli, Paolo Modeling, Identification, and Control for Cyber- Physical Systems Towards Industry 4. 0 San Diego : Elsevier Science & Technology,c2024 9780323952071 |
| ISBN |
9780323952088 |
|
0323952089 |
|
