Stochastic distribution control system design : a convex optimization approach
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 engineeri...
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| Auteurs principaux: | , |
|---|---|
| Formato: | Livre numérique |
| Idioma: | Anglais |
| Publicado em: |
London :
Springer London
[20..].
Cham : Springer Nature |
| Edição: | 1st ed. 2010. |
| Colecção: | Advances in Industrial Control
|
| Acesso em linha: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Nota: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Stochastic Distribution Control System Design, Texte imprimé, 9781849960298 • Stochastic Distribution Control System Design, Texte imprimé, 9781849960335 • Stochastic Distribution Control System Design, Texte imprimé, 9781849960298 • Stochastic Distribution Control System Design, Texte imprimé, 9781447125594 |
Sumário:
- Developments in Stochastic Distribution Control Systems Developments in Stochastic Distribution Control Systems Structural Controller Design for Stochastic Distribution Control Systems Proportional Integral Derivative Control for Continuous-time Stochastic Systems Constrained Continuous-time Proportional Integral Derivative Control Based on Convex Algorithms Constrained Discrete-time Proportional Integral Control Based on Convex Algorithms Two-step Intelligent Optimization Modeling and Control for Stochastic Distribution Control Systems Adaptive Tracking Stochastic Distribution Control for Two-step Neural Network Models Constrained Adaptive Proportional Integral Tracking Control for Two-step Neural Network Models with Delays Constrained Proportional Integral Tracking Control for Takagi-Sugeno Fuzzy Model Statistical Tracking Control Driven by Output Statistical Information Set Multiple-objective Statistical Tracking Control Based on Linear Matrix Inequalities Adaptive Statistical Tracking Control Based on Two-step Neural Networks with Time Delays Fault Detection and Diagnosis for Stochastic Distribution Control Systems Optimal Continuous-time Fault Detection Filtering Optimal Discrete-time Fault Detection and Diagnosis Filtering Conclusions Summary and Potential Applications