Trajectory tracking control of underactuated tendon‐driven truss‐like manipulator based on type‐1 and interval type‐2 fuzzy logic approach

This paper presents a new strategy for the trajectory tracking control of robot, using a fuzzy logic approach and sliding mode control. The key properties of sliding mode control are robustness and chattering which are greatly affected by the motion quality of the reaching phase. The reach law is taken to determine the control law which can improve the convergence speed in the reaching phase and impair the chattering.A fuzzy logic controller is taken to adjust the parameters of the reach law timely which makes the system have a high and rational reaching speed during the whole reaching phase. The error convergencing speed is enhanced which boosted the robustness of system indirectly. And the reaching speed is reduced enough to impair the chattering when the system is very near the sliding mode surface. At last, both the robustness and chattering are improved. A mobile manipulator with two arms is taken as an example to track a given trajectory with the proposed controller. It is found that the results are very encouraging.

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

Measurement and Control ◽

10.1177/0020294021997483 ◽

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.

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