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100512s2010 xxk| s |||| 0|eng d |
| 020 |
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|a 9781849960304
|9 978-1-84996-030-4
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7 |
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|a 10.1007/978-1-84996-030-4
|2 doi
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|a TJ212-225
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|a TJFM
|2 bicssc
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|a TEC004000
|2 bisacsh
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|a 629.8
|2 23
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| 100 |
1 |
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|a Guo, Lei.
|e author.
|
| 245 |
1 |
0 |
|a Stochastic Distribution Control System Design
|b A Convex Optimization Approach /
|c by Lei Guo, Hong Wang.
|h [electronic resource] :
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| 264 |
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1 |
|a London :
|b Springer London,
|c 2010.
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| 300 |
# |
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|b online resource.
|
| 336 |
# |
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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| 338 |
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|a online resource
|b cr
|2 rdacarrier
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| 347 |
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|a text file
|b PDF
|2 rda
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| 490 |
1 |
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|a Advances in Industrial Control,
|x 1430-9491
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| 505 |
0 |
# |
|a Introduction -- Basic Stochastic Distribution Control Systems: Modelling and Controller Design Tools -- PDF Tracking Control with PID Structure for Non-Gaussian Continuous System -- PDF Tracking Control with PID Structure for Non-Gaussian Discrete-time Systems -- Statistic Tracking Control: A Multi-objective Optimization Algorithm -- Optimal Output Probability Density Function Control for Nonlinear ARMAX Stochastic Systems -- FDD for Non-Gaussian Continuous Systems Based on Output PDFs -- Optimal FDD for Non-Gaussian Time-delayed Systems Based on Output PDFs -- Optimal FDD for Non-Gaussian Discrete Systems Based on Output PDFs -- Entropy Optimization Filtering for Fault Isolation of Non-Gaussian Systems -- Conclusions.
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| 520 |
# |
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|a Stochastic distribution control (SDC) systems are widely seen in practical industrial processes, the aim of the controller design being generation of output probability density functions for non-Gaussian systems. Examples of SDC processes are: particle-size-distribution control in chemical engineering, flame-distribution control in energy generation and combustion engines, steel and film production, papermaking and general quality data distribution control for various industries. SDC is different from well-developed forms of stochastic control like minimum-variance and linear-quadratic-Gaussian control, in which the aim is limited to the design of controllers for the output mean and variances. An important recent development in SDC-related problems is the establishment of intelligent SDC models and the intensive use of linear-matrix-inequality-based (LMI-based) convex optimization methods. Within this theoretical framework, control parameter determination can be designed and stability and robustness of closed-loop systems can be analyzed. Stochastic Distribution Control System Design describes the new framework of SDC system design and provides a comprehensive description of the modelling of controller design tools and their real-time implementation. The book starts with a review of current research on SDC and moves on to some basic techniques for modelling and controller design of SDC systems. This is followed by a description of controller design for fixed-control-structure SDC systems, PDF control for general input- and output-represented systems, filtering designs, and fault detection and diagnosis (FDD) for SDC systems. Many new LMI techniques being developed for SDC systems are shown to have independent theoretical significance for robust control and FDD problems. This monograph will be of interest to academic researchers in statistical, robust and process control, and FDD, process and quality control engineers working in industry and as a reference for graduate control students. �
|
| 650 |
# |
0 |
|a Engineering.
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| 650 |
# |
0 |
|a Chemical engineering.
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| 650 |
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0 |
|a Distribution (Probability theory).
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| 650 |
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0 |
|a Machinery.
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| 650 |
# |
0 |
|a System safety.
|
| 650 |
1 |
4 |
|a Engineering.
|
| 650 |
2 |
4 |
|a Control.
|
| 650 |
2 |
4 |
|a Probability Theory and Stochastic Processes.
|
| 650 |
2 |
4 |
|a Industrial Chemistry/Chemical Engineering.
|
| 650 |
2 |
4 |
|a Manufacturing, Machines, Tools.
|
| 650 |
2 |
4 |
|a Quality Control, Reliability, Safety and Risk.
|
| 650 |
2 |
4 |
|a Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
|
| 700 |
1 |
# |
|a Wang, Hong.
|e author.
|
| 710 |
2 |
# |
|a SpringerLink (Online service)
|
| 773 |
0 |
# |
|t Springer eBooks
|
| 776 |
0 |
8 |
|i Printed edition:
|z 9781849960298
|
| 830 |
# |
0 |
|a Advances in Industrial Control,
|x 1430-9491
|
| 856 |
4 |
0 |
|u https://ezaccess.library.uitm.edu.my/login?url=http://dx.doi.org/10.1007/978-1-84996-030-4
|
| 912 |
# |
# |
|a ZDB-2-ENG
|
| 950 |
# |
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|a Engineering (Springer-11647)
|