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Intelligent Force Control for Hydraulic Manipulator within the Impedance Control Framework

Alimohammadi, Hossein | 2017

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  1. Type of Document: M.Sc. Thesis
  2. Language: English
  3. Document No: 50507 (58)
  4. University: Sharif University of Technology, International Campus, Kish Island
  5. Department: Science and Engineering
  6. Advisor(s): Khayyat, Amir Ali Akbar
  7. Abstract:
  8. The main concept of this thesis is to simulate, develop, and analyze the performance of force control method by applying to a Unimate MK-II hydraulic manipulator. In this investigation, simulation studies are based on the concept of impedance control technique. Position-based formulation of impedance control is employed. First in this research, a PID controller is employed and is shown to be capable of performing position control task precisely despite the fact that inertia, joint stiction, valve deadband and other nonlinearities are presented. Although trajectory tracking is performed well after several investigations, we have concluded that the impedance control cannot perform a desirable force regulation by itself without precise data from the environment. Consequently, by adding a novel control loop to aforesaid impedance control loop, performing an appropriate force regulation is considered as the main challenge. In this research, we have developed an intelligent controller in order to improve force regulation based on the assumption that there is no exact information about the external environment. The intelligent controller that is used in this investigation is Emotional Learning Based on Intelligent Controller (ELIC) which is categorized as Neuro-Fuzzy learning method. Lastly, it has been shown through simulation results that without implementing ELIC method in the controlling process, position control is performed well, but the force regulation is below expectation. However, by applying ELIC method to controlling process, this problematic issue is solved
  9. Keywords:
  10. Force Control ; Impedance Control ; Manipulator ; Emotional Learning ; Intelligent Control ; Hydraulic Manipulator

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