Two-Time Scale Fuzzy Logic Controller and Observer Design for Trajectory Tracking of Two Cooperating Robot Manipulators Handling a Flexible Beam

2007 ◽  
Author(s):  
Ali Ashayeri ◽  
Mohammad Eghtesad ◽  
Mehrdad Farid ◽  
Faridoon Shabani
Keyword(s):  
Fuzzy Logic ◽  
Trajectory Tracking ◽  
Time Scale ◽  
Fuzzy Logic Controller ◽  
Robot Manipulators ◽  
Observer Design ◽  
Flexible Beam

scholarly journals Social spider optimization algorithm for tuning parameters in PD-like Interval Type-2 Fuzzy Logic Controller applied to a parallel robot

2021 ◽  
Vol 54 (3-4) ◽  
pp. 303-323
Author(s):  
Amjad J Humaidi ◽  
Huda T Najem ◽  
Ayad Q Al-Dujaili ◽  
Daniel A Pereira ◽  
Ibraheem Kasim Ibraheem ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Trajectory Tracking ◽  
Fuzzy Logic Controller ◽  
Optimization Technique ◽  
Parallel Robot ◽  
Design Parameters ◽  
Social Spider ◽  
Social Spider Optimization ◽  
Interval Type

This paper presents control design based on an Interval Type-2 Fuzzy Logic (IT2FL) for the trajectory tracking of 3-RRR (3-Revolute-Revolute-Revolute) planar parallel robot. The design of Type-1 Fuzzy Logic Controller (T1FLC) is also considered for the purpose of comparison with the IT2FLC in terms of robustness and trajectory tracking characteristics. The scaling factors in the output and input of T1FL and IT2FL controllers play a vital role in improving the performance of the closed-loop system. However, using trial-and-error procedure for tuning these design parameters is exhaustive and hence an optimization technique is applied to achieve their optimal values and to reach an improved performance. In this study, Social Spider Optimization (SSO) algorithm is proposed as a useful tool to tune the parameters of proportional-derivative (PD) versions of both IT2FLC and T1FLC. Two scenarios, based on two square desired trajectories (with and without disturbance), have been tested to evaluate the tracking performance and robustness characteristics of proposed controllers. The effectiveness of controllers have been verified via numerical simulations based on MATLAB/SIMULINK programming software, which showed the superior of IT2FLC in terms of robustness and tracking errors.

Fuzzy Logic Control for an Integrated System of a Micro-Manipulator with a Single Flexible Beam

2004 ◽  
Vol 10 (5) ◽  
pp. 755-776 ◽  
Author(s):  
N. G. Chalhoub ◽  
B. A. Bazzi
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Angular Displacement ◽  
Digital Simulation ◽  
Linear Quadratic Regulator ◽  
Integrated System ◽  
Flexible Beam ◽  
Linear Quadratic ◽  
End Effector ◽  
Micro Manipulator

The use of lightweight robotic manipulators in advanced assembly and manufacturing applications is hindered by the end-effector positional inaccuracies induced by the structural deformations of the arm. To address this problem, a macro- and micro-manipulator system is considered herein. Three rigid and flexible motion controllers, consisting of an integral plus state feedback controller (ISFC), linear quadratic regulator with an integral action (LQI) and a fuzzy logic controller (FLC), have been implemented in this study. The performances of these controllers are compared based on achieving zero steady-state error in the rigid body angular displacement of the beam, damping out the unwanted vibrations, rendering the end-effector insensitive to the vibrations of the arm, and avoiding excessive control torque requirements. The digital simulation results demonstrate the superiority of the FLC over the ISFC and LQI in damping out the vibrations of the beam and reducing the gripper positional inaccuracies while requiring relatively smaller control torques. Furthermore, the results clearly demonstrate the robustness of the FLC to significant variations in the payload mass.

Fuzzy Logic Control of the End-Point Vibration in an Experimental Flexible Beam

2004 ◽  
Vol 10 (4) ◽  
pp. 493-506 ◽  
Author(s):  
A. Jnifene ◽  
W Andrews
Keyword(s):  
Fuzzy Logic ◽  
Strain Gage ◽  
Degrees Of Freedom ◽  
Fuzzy Logic Controller ◽  
Angular Displacement ◽  
Angular Position ◽  
Rule Base ◽  
Flexible Beam ◽  
End Point ◽  
Logic Control

This paper is concerned with the design and implementation of a fuzzy logic controller (FLC) to control the end-point vibration in a single flexible beam mounted on a two-degrees-of-freedom platform. The angular position of the hub and the signal from a strain gage mounted on the beam are used as the two inputs to the FLC. In order to add more damping, the strain gage signal is combined with the hub angular velocity represented by the output of a tachometer attached to the motor shaft. We discuss how to build the rule base for the flexible beam based on the relation between the angular displacement of the hub and the end-point deflection, as well as the effect of different scaling gains on the performance of the FLC. We present several experimental results showing the effectiveness of the FLC in reducing the end-point vibration of the flexible beam.

scholarly journals Integrated Design of Adaptive & Fuzzy Logic Control for Trajectory Tracking of 2 DOF Quadrotor

2021 ◽  
Author(s):  
Mustefa Jibril
Keyword(s):  
Fuzzy Logic ◽  
Trajectory Tracking ◽  
Degrees Of Freedom ◽  
Fuzzy Logic Controller ◽  
Control Method ◽  
Fuzzy Controller ◽  
Vertical Plane ◽  
Integrated Design ◽  
Adaptive Fuzzy ◽  
Quadrotor Uav

Accurate and precise trajectory tracking is crucial for a quadrotor to operate in disturbed environments. This paper presents a novel tracking hybrid controller for a quadrotor UAV that combines the Adaptive and Fuzzy logic controller. The Adaptive fuzzy controller is implemented to govern the behavior of two degrees of freedom quadrotor UAV. The proposed controller allows controlling the movement of UAVs to track a given trajectory in a 2D vertical plane. The Fuzzy Logic system provides an automatic adjustment of the Adaptive parameters to reduce tracking errors and improve the quality of the controller. The results showed perfect behavior for the control law to control a quadrotor trajectory tracking task. To show the effectiveness of the intelligent controller, simulation results are given to confirm the advantages of the proposed control method, compared with Fuzzy and Proportional integral derivative (PID) control methods.

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