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Cross-Layer Adaptive Feedback Scheduling of Wireless Control System

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Title: Cross-Layer Adaptive Feedback Scheduling of Wireless Control System Author: Computer Science Dept Last modified by: Computer Science Dept Created Date – PowerPoint PPT presentation

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Title: Cross-Layer Adaptive Feedback Scheduling of Wireless Control System


1
Cross-Layer Adaptive Feedback Scheduling of
Wireless Control System
  • Presented by Bin Tang

2
Wireless Control Systems (WCSs)
  • Spatially distributed nodes of sensors,
    controllers, and/or actuators interconnected with
    wireless links
  • Advantages
  • Flexible installation and maintenance, mobile
    operation
  • Hazardous and inaccessible environment
  • Cheaper cost
  • Disadvantages
  • Path loss, multi-path fading, interference, etc
  • Delay, packet losses, jitters get more pronounced

3
WCS System Model
  • Independent control loop
  • Smart sensor (S)
  • Smart actuator (A)
  • Controller (C)
  • Physical process (P)
  • IEEE801.11b
  • Variable channel capacity
  • Control performance is decided by Deadline Miss
    Ratio (DMR)

4
Deadline Miss Ratio (DMR)
  • Deadline is equal to the sampling period
  • Two cases for DMR
  • Sample data/control command is lost through
    wireless medium (bit error, interference, varying
    strength)
  • Control command is received by actuator, later
    than deadline

5
Cross-layer adaptive feedback scheduling (CLAFS)
scheme
  • Information exchanging b/w application layer and
    physical layer
  • Dynamically adjust sampling period w.r.t.
  • transmission rate
  • deadline miss ratio (DMR)
  • Feedback scheduler
  • uses PID algorithm with adaptive parameters
  • Event-driven invocation algorithm

6
Sampling Period
  • Sampling period of the control loop
  • QoC and workload
  • Delay and DMR
  • Adjust sampling period based on transmission rate
    and DMR

7
Analysis of DMR over WLAN
  • DMR at appropriate non-zero desired
  • Smaller sample period, larger DMR
  • Larger sample period, poorer Quality of Control

8
PID (Proportional-Integral-Derivative) control
algorithm
9
feedback scheduling
  • Sampling period at jth invocation instant of the
    feedback scheduler
  • h(j) minh(j-1)?h(j), hmax
  • hmax maximum allowable sampling period
  • ?h(j)Ke(j)
  • e(j)?(j)-?r actual and setpoint DMR
  • K proportional coefficient

10
Proportional Coefficient K
  • K0 from simulation
  • ??, ??- parameter

11
Optimal Quality of Control (hr, ?r)
12
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13
Event-triggered invocation
  • Time-triggered not suitable for wireless
  • A
  • Execution-request event iff ?(j)-?rd

14
Performance Evaluation
  • Matlab with TrueTime toolbox
  • Two scenarios
  • Scenario I Controller and process close to each
    other 11Mbps no interfering
  • Scenario I Increased distance 5.5 Mbps
    interfering signal

15
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16
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17
Wireless Sensor/Actuator Network Design for
Mobile Control Applications
18
Semi-Automated Architecture
Automated Architecture
19
Experimental Analysis of Link Quality
20
Dealing with Packet Loss on Actuator
  • Idea when sensor data lost, actuator still
    produce control command
  • Prediction from prev commands
  • û(k) estimate of k-th control command

21
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22
  • Inverted pendulum system
  • PID control algorithm

r(k) desired system output y(k) measured
system output
Integral of absolute error (IAE)
23
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24
Random Thoughts
  • Control Side
  • How to find the optimal operating point (hr, ?r)?
  • So far reactive, not proactive
  • Automated or semi-automated?
  • Wireless Network Side
  • Can MAC layers and routing algorithms play a more
    active in WCS?
  • Sensors/actuators/controllers coordination is not
    considered
  • Data sensed by sensor is solely for the purpose
    of control
  • Control application and other applications
    together
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