Multivariate Statistical Process Control by Zhiqiang Ge
Given their key position in the process control industry, process monitoring techniques have been extensively investigated by industrial practitioners and academic control researchers. Multivariate statistical process control (MSPC) is one of the most popular data-based methods for process monitoring and is widely used in various industrial areas. Effective routines for process monitoring can help operators run industrial processes efficiently at the same time as maintaining high product quality.
Multivariate Statistical Process Control reviews the developments and improvements that have been made to MSPC over the last decade, and goes on to propose a series of new MSPC-based approaches for complex process monitoring. These new methods are demonstrated in several case studies from the chemical, biological, and semiconductor industrial areas.
Control and process engineers, and academic researchers in the process monitoring, process control and fault detection and isolation (FDI) disciplines will be interested in this book. It can also be used to provide supplementary material and industrial insight for graduate and advanced undergraduate students, and graduate engineers.
Advances in Industrial Control aims to report and encourage the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.
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Robust Autonomous Guidance
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Robust Model Predictive Control for Autonomous Underwater Vehicles
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Model-Based Control of Mass–Stiffness–Damping Systems
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Pneumatic Servo Systems Analysis
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Control of Large Wind Energy Systems
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Predictive Functional Control
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Advanced Control and Supervision of Mineral Processing Plants
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Networked and Distributed Predictive Control
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Fault Detection and Fault-Tolerant Control Using Sliding Modes
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Reset Control Systems
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Industrial Process Identification and Control Design
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Cooperative Control of Multi-agent Systems
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Sliding-Mode Control of PEM Fuel Cells
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Control of Integral Processes with Dead Time
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Internet-based Control Systems
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Drives and Control for Industrial Automation
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PID Control in the Third Millennium
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Model Predictive Control of Wastewater Systems
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Structured Controllers for Uncertain Systems
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Fractional-order Systems and Controls
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Quad Rotorcraft Control
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Active Control of Flexible Structures
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Detection and Diagnosis of Stiction in Control Loops
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Motion Coordination for VTOL Unmanned Aerial Vehicles
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Vehicle-Manipulator Systems
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Optimal Control of Hybrid Vehicles
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Optimal Control and Optimization of Stochastic Supply Chain Systems
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Dynamics and Control of Switched Electronic Systems
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Hybrid Predictive Control for Dynamic Transport Problems
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Model-Based Fault Diagnosis Techniques
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Adaptive Control of Solar Energy Collector Systems
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Practical Grey-box Process Identification
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Relay Tuning of PID Controllers
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Control of Solar Energy Systems
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Deadlock Resolution in Automated Manufacturing Systems
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Induction Motor Control Design
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Data-driven Methods for Fault Detection and Diagnosis in Chemical Processes
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Dynamics and Control of Industrial Cranes
From the reviews:
“The aim of this book is to present an actual panorama of the statistical monitoring methods applied to industrial processes… The presentation of the book makes it ready to use for an audience already aware of the vocabulary and main techniques of statistical analysis. … the books contains a wealth of examples and benchmarks that are very valuable for estimating the quality of the methods as well as for supporting further researches in the area.” (Pierre Leone, zbMATH, Vol. 1272, 2013)| SKU | Unavailable |
| ISBN 13 | 9781447145127 |
| ISBN 10 | 1447145127 |
| Title | Multivariate Statistical Process Control |
| Author | Zhiqiang Ge |
| Series | Advances In Industrial Control |
| Condition | Unavailable |
| Binding Type | Hardback |
| Publisher | Springer London Ltd |
| Year published | 2012-11-21 |
| Number of pages | 194 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |