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Adaptive Nonlinear \({{\mathcal{H}}}_{\user2{\infty}}\) Control

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Robust Control of Robots

Abstract

In this chapter, we present adaptive nonlinear \({\mathcal{H}}_{\infty}\) controllers for robot manipulators. Similarly to the controllers presented in Chap. 3, the ones here guarantee robustness to parametric uncertainty and external disturbances. They go beyond, however, by allowing us to estimate the parametric uncertainties and the unmodeled dynamics. These adaptive control laws are added into the standard nonlinear \({\mathcal{H}}_{\infty}\) control approach whose derivation is based on the nominal model of the manipulator. Two adaptive control strategies are considered in this chapter, the first one based on linear parameterizations and the second one based on neural networks estimates.

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References

  1. Bergerman M (1996) Dynamics and control of underactuated manipulators. Ph.D. Thesis, Carnegie Mellon University, Pittsburgh, p 129

    Google Scholar 

  2. Chang YC (2000) Neural network-based \({\mathcal{H}}_{\infty}\) tracking control for robotic systems. IEE Proc Control Theory Appl 147(3):303–311

    Article  Google Scholar 

  3. Chang YC, Chen BS (1997) A nonlinear adaptive \({\mathcal{H}}_{\infty}\) tracking control design in robotic systems via neural networks. IEEE Trans Control Syst Technol 5(1):13–29

    Article  Google Scholar 

  4. Chen BS, Chang YC, Lee TC (1997) Adaptive control in robotic systems with \({\mathcal{H}}_{\infty}\) tracking performance. Automatica 33(2):227–234

    Article  MathSciNet  MATH  Google Scholar 

  5. Chen BS, Lee TS, Feng JH (1994) A nonlinear \({\mathcal{H}}_{\infty}\) control design in robotic systems under parameter perturbation and external disturbance. Int J Control 59(2):439–461

    Article  MathSciNet  MATH  Google Scholar 

  6. Craig JJ (1985) Adaptive control of mechanical manipulators. Addison-Wesley, Reading

    Google Scholar 

  7. Ge SS, Lee TH, Harris CJ (1998) Adaptive neural network control of robotic manipulators. World Scientific, Singapore

    Google Scholar 

  8. Lewis FL, Abdallah CT, Dawson DM (2004) Robot manipulator control: theory and practice. Marcel Dekker, Inc., New York

    Google Scholar 

  9. Postlethwaite I, Bartoszewicz A (1998) Application of non-linear \({\mathcal{H}}_{\infty}\) control to the Tetrabot robot manipulator. Proc Inst Mech Eng: Part I. J Syst Control Eng 212(16):459–465

    Article  Google Scholar 

  10. Siqueira AAG, Petronilho A, Terra MH (2003) Adaptive nonlinear \({\mathcal{H}}_{\infty}\) techniques applied to a robot manipulator. In: Proceedings of the IEEE conference on control applications, Istanbul, Turkey

    Google Scholar 

  11. Slotine JJ, Li W (1987) On the adaptive control of robot manipulators. Int J Rob Res 6(3):49–59

    Article  Google Scholar 

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Correspondence to Marcel Bergerman .

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Siqueira, A.A.G., Terra, M.H., Bergerman, M. (2011). Adaptive Nonlinear \({{\mathcal{H}}}_{\user2{\infty}}\) Control. In: Robust Control of Robots. Springer, London. https://doi.org/10.1007/978-0-85729-898-0_4

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  • DOI: https://doi.org/10.1007/978-0-85729-898-0_4

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  • Publisher Name: Springer, London

  • Print ISBN: 978-0-85729-897-3

  • Online ISBN: 978-0-85729-898-0

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