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논문검색

Parallel Soft Computing Control Optimization Algorithm for Uncertainty Dynamic Systems

초록

영어

This research contributes to the on-going research effort by exploring alternate methods for soft computing optimization the highly nonlinear and uncertain systems. This research addresses two basic issues related to the control of an uncertain system; (1) design of a robust feedback controller, and (2) the design of a parallel artificial intelligence based optimization to increase the result qualification. The robust backstepping controller proposed in this research is used to further demonstrate the appealing features exhibited by the continuum robot. Robust feedback controller is used to position control of continuum robot in presence of uncertainties. Using Lyapunov type stability arguments, a robust backstepping controller is designed to achieve this objective. The controller developed in this research is designed in two steps. Firstly, a robust stabilizing torque is designed for the nominal continuum robot dynamics derived using the constrained Lagrangian formulation. Next, the fuzzy logic methodology applied to it to solution uncertainty problem by parallel optimization. The fuzzy model free optimization is formulated to minimize the problem of nonlinear formulation of uncertain systems.

목차

Abstract
 1. INTRODUCTION AND BACKGROUND
 2. Theory
 3. Methodology
 4. Result and Discussion
 5. Conclusion
 Acknowledgements
 References

저자정보

  • Mansour Bazregar Senior Researcher at Research and Development Department, SSP Research and Development Company
  • Farzin Piltan Senior Researcher at Research and Development Department, SSP Research and Development Company
  • AliReza Nabaee Senior Researcher at Research and Development Department, SSP Research and Development Company
  • Mohammad Mahdi Ebrahimi Senior Researcher at Research and Development Department, SSP Research and Development Company

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