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Technical Briefs

Recursive Identification of Nonlinear Cascade Systems With Time-Varying General Input Backlash

[+] Author and Article Information
Jozef Vörös

Faculty of Electrical Engineering and
Information Technology,
Slovak Technical University,
Institute of Control and Industrial Informatics,
Ilkovicova 3, 812 19 Bratislava, Slovakia
e-mail: jvoros@elf.stuba.sk

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNALOF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received September 20, 2011; final manuscript received March 14, 2012; published online October 30, 2012. Assoc. Editor: Douglas Adams.

J. Dyn. Sys., Meas., Control 135(1), 014504 (Oct 30, 2012) (5 pages) Paper No: DS-11-1293; doi: 10.1115/1.4006630 History: Received September 20, 2011; Revised March 14, 2012

Recursive identification of nonlinear cascade systems with a time-varying general input backlash and a linear dynamic system is presented. A new analytic form of general backlash characteristic description is used, where instead of the straight lines determining the upward and downward parts of backlash characteristic, general curves are considered. All the parameters in the cascade model equation are separated and their estimation is solved as a quasi-linear problem using the recursive least squares method with internal variable estimation. Simulation studies are included for more cascade systems with time-varying general input backlash.

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Figures

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Fig. 1

General backlash characteristic

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Fig. 2

Cascade systems with general input backlash

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Fig. 3

The original (dashed) and the new (solid) general backlash characteristics—Example 1

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Fig. 4

General backlash parameter estimates—Example 1 (the top-down order of new parameters is mL1, mR1, mR3, mL3, cL = cR, mL2, mR2)

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Fig. 5

Linear system parameter estimates—Example 1 (the top-down order of parameters is b2, a2, b1)

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Fig. 6

The original (dashed) and the new (solid) general backlash characteristics—Example 2

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Fig. 7

General backlash parameter estimates—Example 2 (the top-down order of new parameters is mR3, mL3, mL1, mR1, cR, cL, mL2, mR2)

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Fig. 8

Linear system parameter estimates—Example 2 (the top-down order of parameters is b2, a2, b1)

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