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Co-design Approaches to Dependable Networked Control Systems [Kõva köide]

(INRIA Rhone-Alpes), (Nancy University, France), (Nancy University, France)
  • Formaat: Hardback, 336 pages, kõrgus x laius x paksus: 241x163x25 mm, kaal: 621 g
  • Ilmumisaeg: 15-Jan-2010
  • Kirjastus: ISTE Ltd and John Wiley & Sons Inc
  • ISBN-10: 1848211767
  • ISBN-13: 9781848211766
Teised raamatud teemal:
Co-design Approaches to Dependable Networked Control SystemsSuurem pilt
  • Formaat: Hardback, 336 pages, kõrgus x laius x paksus: 241x163x25 mm, kaal: 621 g
  • Ilmumisaeg: 15-Jan-2010
  • Kirjastus: ISTE Ltd and John Wiley & Sons Inc
  • ISBN-10: 1848211767
  • ISBN-13: 9781848211766
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9781848211766.html
Märksõnad:
Networked Control Systems (NCS) is a growing field of application and calls for the development of integrated approaches requiring multidisciplinary skills in control, real-time computing and communication protocols. This book describes codesign approaches, and establishes the links between the QoC (Quality of Control) and QoS (Quality of Service) of the network and computing resources. The methods and tools described in this book take into account, at design level, various parameters and properties thatmust be satisfied by systems controlled through a network. Among the important network properties examined are the QoC, the dependability of the system, and the feasibility of the real-time scheduling of tasks and messages. Correct exploitation of these approaches allows for efficient design, diagnosis, and implementation of the NCS.This book will be of great interest to researchers and advanced students in automatic control, real-time computing, and networking domains, and to engineers tasked with development of NCS, as well as those working in related network design and engineering fields.

This book describes co-design approaches, and establishes the links between the QoC (Quality of Control) and QoS (Quality of Service) of the network and computing resources. The methods and tools described in this book take into account, at design level, various parameters and properties that must be satisfied by systems controlled through a network. Among the important network properties examined are the QoC, the dependability of the system, and the feasibility of the real-time scheduling of tasks and messages. Correct exploitation of these approaches allows for efficient design, diagnosis, and implementation of the NCS. This book will be of great interest to researchers and advanced students in automatic control, real-time computing, and networking domains, and to engineers tasked with development of NCS, as well as those working in related network design and engineering fields.
Foreword xiii
Dominique Sauter
Introduction and Problem Statement 1(1)
Christophe Aubrun
Daniel Simon
Ye-Qiong Song
Networked control systems and control design challenges
2(2)
Control design: from continuous time to networked implementation
4(2)
Timing parameter assignment
6(2)
Control and task/message scheduling
8(2)
Diagnosis and fault tolerance in NCS
10(1)
Co-design approaches
11(1)
Outline of the book
12(3)
Bibliography
15(4)
Preliminary Notions and State of the Art
19(44)
Christophe Aubrun
Daniel Simon
Ye-Qiong Song
Overview
19(1)
Preliminary notions on real-time scheduling
20(6)
Some basic results on classic task model scheduling
21(1)
Fixed priority scheduling
22(1)
EDF scheduling
23(1)
Discussion
23(1)
(m, k)-firm model
24(2)
Control aware computing
26(4)
Off-line approaches
27(1)
Quality of Service and flexible scheduling
28(2)
Feedback-scheduling basics
30(13)
Control of the computing resource
32(1)
Control structure
32(1)
Sensors and actuators
32(1)
Control design and implementation
33(2)
Examples
35(1)
Feedback scheduling a web server
35(1)
Optimal control-based feedback scheduling
36(3)
Feasibility: feedback-scheduler implementation for robot control
39(4)
Fault diagnosis of NCS with network-induced effects
43(10)
Fault diagnosis of NCS with network-induced time delays
44(1)
Low-pass post-filtering
44(2)
Structure matrix of network-induced time delay
46(1)
Robust deadbeat fault filter
47(2)
Other work
49(1)
Fault diagnosis of NCS with packet losses
50(1)
Deterministic packet losses
50(1)
Stochastic packet losses
50(1)
Fault diagnosis of NCS with limited communication
51(1)
Fault-tolerant control of NCS
52(1)
Summary
53(1)
Bibliography
53(10)
Computing-aware Control
63(42)
Mongi Ben Gaid
David Robert
Olivier Sename
Alexandre Seuret
Daniel Simon
Overview
63(2)
Robust control w.r.t. computing and networking-induced latencies
65(11)
Introduction
65(2)
What happens when delays appear?
67(1)
Initial conditions
67(1)
Infinite dimensional systems
68(2)
Delay models
70(1)
Stability analysis of TDS using Lyapunov theory
71(1)
The second method
71(1)
The Lyapunov-Razumikhin approach
72(1)
The Lyapunov-Krasovskii approach
73(2)
Summary: time-delay systems and networking
75(1)
Weakly hard constraints
76(13)
Problem definition
77(2)
Notion of accelerable control
79(1)
Design of accelerable controllers
79(1)
Accelerable LQR design for LTI systems
80(2)
Kalman filtering and accelerability
82(1)
Robustifying feedback scheduling using weakly hard scheduling concepts
83(2)
Application to the attitude control of a quadrotor
85(4)
LPV adaptive variable sampling
89(9)
A polytopic discrete-plant model
90(2)
Performance specification
92(1)
LPV/H∞ control design
93(1)
Experimental assessment
94(4)
Summary
98(1)
Bibliography
99(6)
QoC-aware Dynamic Network QoS adaptation
105(44)
Christophe Aubrun
Belynda Brahimi
Jean-Philippe Georges
Guy Juanole
Gerard Mouney
Xuan Hung Nguyen
Eric Rondeau
Overview
105(2)
Dynamic CAN message priority allocation according to the control application needs
107(25)
Context of the study
107(1)
The considered process control application
107(1)
Control performance evaluation
108(1)
The implementation through a network
108(2)
Evaluation of the influence of the network on the behavior of the process control application
110(1)
Idea of hybrid priority schemes: general considerations
111(3)
Three hybrid priority schemes
114(1)
hp scheme
114(1)
(hp+sts) scheme
115(1)
(hp+dts) scheme
116(3)
Study of the three schemes based on hybrid priorities
119(1)
Study conditions
119(1)
hp scheme
120(5)
(hp+sts) scheme
125(3)
(hp+dts) scheme
128(1)
QoC visualization
128(1)
Comment
129(3)
Bandwidth allocation control for switched Ethernet networks
132(12)
NCS performance analysis
134(1)
NCS modeling
134(1)
Introduction
134(1)
Network modeling
135(3)
System modeling
138(1)
Controller modeling
139(2)
Network adaptation mechanism
141(1)
Example
141(1)
Maximum delay computation
141(1)
Results
142(2)
Conclusion
144(1)
Bibliography
145(4)
Plant-state-based Feedback Scheduling
149(36)
Mongi Ben Gaid
David Robert
Olivier Sename
Daniel Simon
Overview
149(2)
Adaptive scheduling and varying sampling robust control
151(5)
Extended elastic tasks controller
152(1)
Case study
153(3)
MPC-based integrated control and scheduling
156(6)
Resource constrained systems
157(3)
Optimal integrated control and scheduling of resource constrained systems
160(2)
A convex optimization approach to feedback scheduling
162(8)
Problem formulation
162(2)
Cost function definition and approximation
164(1)
Cost function definition
164(1)
Introductory example: quadrotor attitude control
165(1)
Optimal sampling period selection
166(1)
Problem formulation
166(1)
Problem solving
167(1)
Feedback-scheduling algorithm deployment
167(1)
Application to the attitude control of a quadrotor
168(2)
Control and real-time scheduling co-design via a LPV approach
170(7)
A LPV feedback scheduler sensible to the plant's closed-loop performances
171(3)
Application to a robot-arm control
174(1)
Performance evaluation of the control tasks in view of optimal resource distribution
174(1)
Simulation with TrueTime
175(2)
Feasibility and possible extensions
177(1)
Summary
177(4)
Bibliography
181(4)
Overload Management Through Selective Data Dropping
185(38)
Flavia Felicioni
Ning Jia
Francoise Simonot-Lion
Ye-Qiong Song
Introduction
185(3)
System architecture
186(2)
Problem statement
188(1)
Scheduling under (m, k)-firm constraint
188(5)
Dynamic scheduling policy under (m, k)-firm constraints
189(1)
Static scheduling policy under (m, k)-firm constraints and schedulability issue
189(1)
Static scheduling under (m, k)-constraints and mechanical words
190(1)
Sufficient condition for schedulability assessment under (m, k)-pattern defined by a mechanical word
191(1)
Systematic dropping policy in control applications
192(1)
Stability analysis of a multidimensional system
193(4)
Generic model
193(1)
Example of multidimensional system
194(1)
Sampling period definition
195(1)
Controller parameters
195(1)
Stability condition
195(2)
Optimized control and scheduling co-design
197(12)
Optimal control and individual cost function
198(2)
Global optimization
200(1)
Case study
201(2)
Plants and controllers
203(1)
Scheduling parameters
203(1)
Optimal controller
203(1)
Simulation scenario
204(1)
Simulation results for hard real-time constraints
204(1)
Simulation results for (m, k)-firm constraints
205(4)
Plant-state-triggered control and scheduling adaptation and optimization
209(9)
Closed-loop stability of switching systems
210(1)
On-line plant state detection
210(1)
Global optimization of control tasks taking into account the plant state
211(2)
Case study
213(1)
Simulation scenario
214(3)
Observed performance
217(1)
Summary
218(1)
Conclusions
218(2)
Bibliography
220(3)
Fault Detection and Isolation, Fault Tolerant Control
223(44)
Christophe Aubrun
Cedric Berbra
Sylviane Gentil
Suzanne Lesecq
Dominique Sauter
Introduction
223(1)
FDI and FTC
224(14)
Introduction to diagnosis
224(2)
Quantitative model-based residuals
226(2)
Parity relations
228(1)
Observers bank
229(2)
Example
231(1)
The system-residual generation
231(2)
Observer-based residuals
233(2)
Diagnostic summary
235(1)
Introduction to FTC
236(2)
Networked-induced effects
238(5)
Example of network-induced drawbacks
239(1)
Modeling data dropouts
240(2)
Modeling network delays
242(1)
Pragmatic solutions
243(5)
Data synchronization
244(1)
Clock synchronization
244(1)
Data reconstruction
245(1)
Example
246(1)
Data loss and diagnostic blocking
247(1)
Advanced techniques
248(14)
Residual generation with transmission delay
248(1)
Adaptive thresholding
249(1)
Optimization-based approach for threshold selection
250(1)
Network calculus-based thresholding
251(5)
Fault isolation filter design in the presence of packet dropouts
256(3)
Estimation and diagnosis with data loss
259(1)
Problem formulation
259(1)
Kalman filter with partial data loss
260(2)
Conclusion and perspectives
262(1)
Bibliography
262(5)
Implementation: Control and Diagnosis for an Unmanned Aerial Vehicle
267(38)
Cedric Berbra
Sylviane Gentil
Suzanne Lesecq
Daniel Simon
Introduction
267(2)
The quadrotor model, control and diagnosis
269(13)
The system
269(1)
The physical system model
270(1)
Introduction to quaternions
270(1)
The quadrotor model
271(2)
The inertial measurement unit (IMU) model
273(1)
The attitude control
274(1)
Nonlinear control
274(1)
Linear quadratic control
274(2)
The attitude observer
276(1)
Nonlinear observer
276(1)
Extended Kalman filter
277(2)
Simulation results
279(1)
The quadrotor diagnosis
279(1)
Sensor diagnosis
279(3)
Actuator diagnosis
282(1)
Simulation of the network
282(3)
Architecture of the networked control system
282(2)
Network design
284(1)
Tool implemented in the network simulation
285(1)
Hardware in the loop architecture
285(5)
The Orccad approach
286(2)
Quadrotor simulation setup
288(2)
Experiments and results
290(12)
Basic attitude control
290(1)
Packet loss
291(1)
Pragmatic solution
291(1)
(m, k)-firm solutions
292(3)
Dynamic priorities
295(2)
Extended Kalman filter
297(1)
Hardware-in-the loop experiment
298(1)
Basic scenario
298(1)
Packet loss
299(1)
Sensor failure
299(3)
Summary
302(1)
Bibliography
303(2)
Glossary and Acronyms 305(4)
List of Authors 309(4)
Index 313
Daniel Simon is a scientist at INRIA Rhône-Alpes with the NeCS project team. His areas of research include real-time software design for robot control. He has provided effective solutions to implement real-time controllers on embedded targets to deal with control and real-time scheduling co-design.

Ye-Qiong Song is Professor at Nancy University in France and with LORIA lab. His research interests include modeling and performance evaluation of networks and real-time distributed systems, as well as the development of real-time QoS mechanisms taking into account the control performance requirements in networked control systems.

Christophe Aubrun is Professor at Nancy University in France. His research areas are in the field of fault diagnosis and fault tolerant control for networked control systems.