Robust fuzzy logic controller for trajectory tracking of robotic systems

2002 ◽  
Author(s):  
A. Cela ◽  
Y. Hamam ◽  
A. Carriere
Keyword(s):  
Fuzzy Logic ◽  
Trajectory Tracking ◽  
Fuzzy Logic Controller ◽  
Robotic Systems

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.

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.

Intelligent Control System Design for a Teleoperated Endoscopic Surgical Robot

2015 ◽  
Vol 789-790 ◽  
pp. 693-699
Author(s):  
Alaa Khalifa ◽  
Ahmed Ramadan
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
System Design ◽  
Trajectory Tracking ◽  
Parallel Manipulator ◽  
Control Algorithm ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Control System Design ◽  
Matlab Simulink

This paper concerns with the control system design for a teleoperated endoscopic surgical manipulator system that uses PHANTOM Omni haptic device as the master and a 4-DOF parallel manipulator (2-PUU_2-PUS) as the slave. PID control algorithm was used to achieve the trajectory tracking, but the error in each actuated joint reached 0.6 mm which is not satisfactory in surgical application. The design of a control algorithm for achieving high trajectory tracking is needed. Simulation on the virtual prototype of the 4-DOF parallel manipulator has been achieved by combining MATLAB/Simulink with ADAMS. Fuzzy logic controller is designed and tested using the interface between ADAMS and MATLAB/Simulink. Signal constraint block adjusted the controller parameters for each actuated prismatic joint to eliminate the overshoot in most of position responses. The simulation results illustrate that the fuzzy logic control algorithm can achieve high trajectory tracking. Also, they show that the fuzzy controller has reduced the error by approximately 50 percent.

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