Optimised Sensor Selection for Control: A Hardware-in-the-Loop - - PowerPoint PPT Presentation

▶
optimised sensor selection for control a hardware in the
SMART_READER_LITE
LIVE PREVIEW

Optimised Sensor Selection for Control: A Hardware-in-the-Loop - - PowerPoint PPT Presentation

Oct 07, 2022 38 likes •253 views

Optimised Sensor Selection for Control: A Hardware-in-the-Loop Realization on FPGA for an EMS System K. Deliparaschos, K. Michail, S. G. Tzafestas, A. C. Zolotas 2 nd Int'l Conference on Control and Fault-Tolerant Systems (SysTol'13), October

slide-1
SLIDE 1

Optimised Sensor Selection for Control: A Hardware-in-the-Loop Realization on FPGA for an EMS System

  • K. Deliparaschos, K. Michail, S. G. Tzafestas,
  • A. C. Zolotas

2nd Int'l Conference on Control and Fault-Tolerant Systems (SysTol'13), October 9-11, 2013, Nice, France.

slide-2
SLIDE 2
  • Introduction and the proposed framework
  • Maglev suspension (case study)
  • FPGA-In-the-Loop with Kalman estimator
  • Results
  • Conclusions

CONTENTS

Systol’13, Nice (FR)

slide-3
SLIDE 3

System

Uncertainties

A Typical Control System

Faults Faults

Disturbances Could be nonlinear; Stable?

Which is the best sensor/actuator set for control (and fault tolerance)?

Systol’13, Nice (FR)

slide-4
SLIDE 4

Within the control properties:

 Sensor (Actuator) fault tolerance  Minimize complexity  Reduce cost  Provide balance of robustness/optimised performance

Sensor optimisation framework adopted here:

  • K. Michail, A. Zolotas, and R. M. Goodall, J. F. Whidborne. Optimised configuration of

sensors for fault tolerant control of an electromagnetic suspension system. International Journal of Systems Science, 43(10):1785–1804, 2012 using Hardware-In-The-Loop

(HIL) concept.

Why number of sensors ...

Systol’13, Nice (FR)

slide-5
SLIDE 5

Overall control constraint violation function If Ω=0 then performance requirements are

  • satisfied. If Ω≠0 then there is some

violation of control constraints. Sensor fault accommodation ratio (Future work) Controller selection criteria Used for the final selection of controller

Framework flowchart

Systol’13, Nice (FR)

slide-6
SLIDE 6

The HIL Concept

Model of the plant will be embedded in software (Simulink/MATLAB) Controller is realized

  • n an FPGA board

FPGA-In-The-Loop (FIL)

Software-based Model of the plant Hardware-based (FPGA) Controller implementation

Communication Channel

Systol’13, Nice (FR)

slide-7
SLIDE 7
  • Introduction and the proposed framework
  • Maglev suspension (case study)
  • FPGA-In-the-Loop with Kalman estimator
  • Results
  • Conclusions

Sections

Systol’13, Nice (FR)

slide-8
SLIDE 8

Suspended mass (m)

Mg F

Track

The test case: Maglev System

Electromagnet Pole Power Amplifier

Driving Signal Flux circulation Airgap

  • Vert. Accleration
  • Vert. Velocity

Current

K

Controller

EMS serves two purposes:

  • Support the vehicle and passengers
  • Ensure proper ride quality

Systol’13, Nice (FR)

slide-9
SLIDE 9

Input disturbances and performance requirements

Deterministic Stochastic Performance requirements

Systol’13, Nice (FR)

> Deterministic and Stochastic control performance using minimum number

  • f sensors.
slide-10
SLIDE 10
  • Introduction and the proposed framework
  • Maglev suspension (case study)
  • FPGA-In-the-Loop with Kalman estimator
  • Results
  • Conclusions

Sections

Systol’13, Nice (FR)

slide-11
SLIDE 11

FIL for the MAGLEV suspension

1 Sensor selection 3

FIL realization

2

High Level Software

Systol’13, Nice (FR)

slide-12
SLIDE 12

Xilinx Spartan-6 SP605 development board (XC6SLX45TFGG484-3C device) in 484-pin fine Ball Grid Array package SP605 board features an ethernet physical interface transceiver chip KBE + peripheral cores synthesized via Xilinx Synthesis Tool

FPGA design /implement

Systol’13, Nice (FR)

slide-13
SLIDE 13

Required wordlength Inequality for combined range + resolution

> KBE achieves system clock > operating freq. of 39.544ns

FPGA design /implement

Systol’13, Nice (FR)

slide-14
SLIDE 14

HIL design / implementation flow diagram

Discretization Quantization

Implementation on FPGA

MATLAB FPGA

Systol’13, Nice (FR)

slide-15
SLIDE 15
  • Introduction and the proposed framework
  • Maglev suspension (case study)
  • FPGA-In-the-Loop with Kalman estimator
  • Results
  • Conclusions

Sections

Systol’13, Nice (FR)

slide-16
SLIDE 16

Optimised sensor selection for maglev case

LQR Similar response Test

Systol’13, Nice (FR)

slide-17
SLIDE 17

Optimised sensor selection on maglev case

LQR Similar response Test

Systol’13, Nice (FR)

slide-18
SLIDE 18

Airgap deflection (deterministic)

Systol’13, Nice (FR)

continuous-time KE vs. FIL-implemented KEC

slide-19
SLIDE 19

State estimation performance (deterministic)

current velocity Airgap

Systol’13, Nice (FR)

slide-20
SLIDE 20
  • Practical investigation of optimised sensor

selection for control on FPGA

  • Attempt to minimizing complexity
  • Shows potential for industrial applications

Conclusions & Discussion

Systol’13, Nice (FR)

slide-21
SLIDE 21

Optimised Sensor Selection for Control: A Hardware-in-the-Loop Realization on FPGA for an EMS System

  • K. Deliparaschos, K. Michail,
  • S. G. Tzafestas, A. C. Zolotas
  • A. Zolotas acknowledges

University of Sussex travel grant support