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System Identification of the SPDM Ground Test Facility Shawn Greene Dr. Raymond Kwong, Academic Supervisor Raja Mukherji Industrial Supervisor, MDA Space.

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Presentation on theme: "System Identification of the SPDM Ground Test Facility Shawn Greene Dr. Raymond Kwong, Academic Supervisor Raja Mukherji Industrial Supervisor, MDA Space."— Presentation transcript:

1 System Identification of the SPDM Ground Test Facility Shawn Greene Dr. Raymond Kwong, Academic Supervisor Raja Mukherji Industrial Supervisor, MDA Space Missions

2 ECE Graduate Symposium 2005, UofT System Identification of the SPDM GT  SPDM Ground Test Facility (GT)  Motivation/Objective  Approach  System Modeling  Identification Methods

3 ECE Graduate Symposium 2005, UofT System Identification ? Experimentally Determined SPDM GT Model Measured Disturbance Input Unmeasured Disturbance Output System Identification Problem: Unmeasured Disturbance Experiment Design Choose Model Set Choose Fit Criterion Validate Model Calculate Model Data Prior Knowledge Not OK: Revise OK: Use it! System Identification Process

4 ECE Graduate Symposium 2005, UofT System Identification – SPDM GT Modeling the SPDM GT Chain of Rigid Bodies Newton-Euler Equation of Motion State-Space Model  Challenges:  Nonlinear Equation of Motion  Configuration dependent  Nonlinear gearbox stiffness  Friction modeling and observation difficult  Sensor availability  System delays

5 ECE Graduate Symposium 2005, UofT System Identification Tasks  Find robust method(s) to…  Determine locally linear models of the system to be used in controller design  Determine certain physical properties about a configuration  Fault diagnosis?  Perform load identification (A,B,C,D,K) SPDM GT Mass, Damp, Stiffness SPDM GT Load SPDM GT

6 ECE Graduate Symposium 2005, UofT Experimental Design  Simulation generates data in open-loop  MATLAB System Identification Routines  Search for best model involves estimating   PEM – Prediction Error Method (Max. Likelihood)  Structured and Greybox Identification models  Compare against expected model Input Signals Output Signals Step Signal Pulse Signal Chirp Signal Band-Limited White Noise Joint and Motor Positions, Motor Velocities


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