Journal of Intelligent & Robotic Systems

, Volume 95, Issue 1, pp 61–75 | Cite as

New AFSMC Method for Nonlinear System with State-dependent Uncertainty: Application to Hexapod Robot Position Control

  • Hamed Navvabi
  • A. H. D. MarkaziEmail author


Conventional Adaptive Fuzzy Sliding Mode Control (AFSMC) method is extended for nonlinear affine systems with state-dependent upper bound of uncertainties. More general affine model of the system with state-dependent uncertainties is proposed where such a model is more applicable in robotics. Position control of a Stewart Manipulator (SM) is then considered as a challenging case study to experimentally verify the effectiveness of the proposed Extended AFSMC (E-AFSMC) method. The proposed method is encompassed of a fuzzy system for estimation of a nonlinear system, a robust controller for compensation of uncertainties and some appropriate adaptation laws for optimization of performance. The second Lyapunov theorem and Barbalat lemma are used to prove the closed-loop asymptotic stability. Furthermore, numerical simulations depict the robustness of the proposed controller and in particular, under the very critical situation of actuator saturation and unexpected uncertainties. The effectiveness of the proposed control method is validated through experimental results.


Stewart Manipulator (SM) State-dependent uncertainty Extended adaptive fuzzy sliding mode controller E-AFSMC 


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© Springer Science+Business Media B.V., part of Springer Nature 2018

Authors and Affiliations

  1. 1.Digital Control Laboratory, School of Mechanical EngineeringIran University of Science and TechnologyNarmakIran

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