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Impedance Force Control of a Robot Manipulator Using a Neuro-Fuzzy Controller

Kharmandar, Negar | 2011

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  1. Type of Document: M.Sc. Thesis
  2. Language: English
  3. Document No: 41963 (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 present study discusses the problem of enabling a PUMA 560 electrical robot manipulator to interact with the environment using impedance control concept. The impedance control strategy maintains a pre-specified desired second order dynamic relation between the end-effector position and force and enables a stable transmission between unconstrained and constrained motion. In this study Position-Based Impedance Control (PBIC) is used which is more suitable for industrial manipulators. PBIC requires a position controller with high accuracy. Therefore, a nonlinear PID controller is used in the position loop which is capable of both tracking and regulating of the input signals and shows better performance compared to the conventional PID controller. Different tests including free space and contact tasks are done to show that the manipulator impedance can exactly match the target impedance. When the robot end-effector comes into contact with the environment, the control of force generated between the environment and the end-effector will be a considerable issue but the impedance control lacks the ability to track a desired force by itself when the environmental parameters are unknown. This problem leads to using an extra controller in order to make the manipulator track the desired force. Therefore, to overcome this inability, a neuro-fuzzy controller (ANFIS) is proposed. The ANFIS uses the available data from the end-effector position and force sensors to estimate the stiffness of environment. This leads to obtaining the environment location. Finally, the estimated values are applied to the system to modify the position reference trajectory in order to minimize force error which causes the impedance control to improve the ability of force tracking even in the presence of time-varying stiffness and location of the environment
  9. Keywords:
  10. Fuzzy Controller ; Impedance Control ; Nonlinear Proportional-Integral-Derivative (PID)Controller ; Environment Stiffness

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  • Chapter 1
    • 1.1 Control of robots in contact tasks
    • 1.2 Classification of constraint motion
    • In recent years different control strategies have been proposed on the problem of controlling the compliant motion. Various cr
      • 1.2.1 Passive compliance
      • 1.2.2 Active compliance
        • 1.2.2.1 Hybrid position/force control
        • 1.2.2.2 Impedance control
    • 1.3 Objective of the study
    • 1.4 Organization of thesis
    • 1.5 Summary
  • Chapter 2
    • 2.1 Introduction
    • 2.2 What is impedance control?
      • 2.2.1 Torque-based impedance control
      • 2.2.2 Position-based impedance control
    • 2.3 Impedance control and force tracking
    • 2.4 Review of impedance control and force tracking
    • 2.5 Summary
  • Chapter 3
  • The Electrical PUMA560 Robot
    • 3.1 Description of manipulator
    • 3.2 Kinematics of PUMA 560
    • where, .
    • 3.3 Dynamic model of PUMA 560
      • 3.3.1 Dynamic characteristic of PUMA 560
    • 3.4 PUMA 560 actuation system
    • 3.5 Simulation program
    • 3.6 Summary
  • Chapter 4
  • The Application of Position-Based Impedance Control to PUMA 560 Manipulator
    • 4.1 Introduction
    • 4.2 Position-Based Impedance Control structure
    • 4.3 Nonlinear PID position controller
      • 4.3.1 Applying conventional PID controllers
      • 4.3.2 Modified rate-varying integral
  • Chapter 5
    • 5.1 Introduction
    • 5.2 Force tracking in impedance control
    • 5.3 Neuro-Fuzzy system
      • 5.3.1 Fuzzy system
      • 5.3.2 Neural Network
      • 5.3.3 Adaptive Network-based Fuzzy Inference System (ANFIS) architecture
        • 5.3.3.1 Basic learning rule
      • 5.3.4 Architecture of ANFIS
      • 5.3.5 Hybrid learning procedure for ANFIS
    • 5.4 Applying the ANFIS to the PBIC for the purpose of force tracking
    • 5.5 Comparison of the proposed method with the previous works
    • 5.6 Summary
  • Chapter 6
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