Fuzzy PI Controller for Mobile Robot Navigation and Tracking

Allagui, Najah Yousfi; Abid, Donia Ben Halima; Derbel, Nabil

doi:10.1109/ssd.2018.8570477

Cited by 5 publications

(2 citation statements)

References 14 publications

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“…This problem is categorized into three categories: navigation, path following, and trajectory tracking. The control algorithm plays an important role in the working ability of mobile robotic platform; therefore, the overall mobile robot system with its subsystems and components must be designed to be robust and adaptive system, as well as operates with improved dynamic and with a good steady state system performances [ 1 ].…”

Section: Introductionmentioning

confidence: 99%

“…These controllers are widely used to produce control outputs for complex and/or nonlinear systems, thanks to its capability to handle with heuristic and imprecise information. The flexibility of FLC to establish nonlinear control algorithms is a well-known argument to use these algorithms, especially in motion control and tracking of mobile robots [ 1 , 6 – 11 ].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Artificial Fuzzy‐PID Gain Scheduling Algorithm Design for Motion Control in Differential Drive Mobile Robotic Platforms

Allagui

Salem

Aljuaid

2021

Computational Intelligence and Neuroscience

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Mobile robots are promising devices which are dedicated to human comfort in all areas. However, the control algorithm of the wheels of mobile robot is entirely challenging due to the nonlinearity. Recently, the classical PID (proportional-integral-derivative) controllers are frequently used in robotics for their high accuracy and the smooth determination of their parameters. A robust approach called fuzzy control which is based on the conversion of linguistic inference sets in a suitable control value is a widely used method in industrial system control in our days. A new challenging method to solve the problem of intelligent navigation of nonholonomic mobile robot is suggested. In this work, the presented methodology is based on three hybrid fuzzy logic PID controllers which are adapted to guarantee target achievement and trajectory tracking. A fuzzy-PID control algorithm is designed with 2 inputs and 3 outputs. By the information given by the system response, error and error derivate can be used to extract and adopt the PID controller parameters: proportional, integral, and derivative gains. Besides, a tuning value A is introduced to improve the resulted response in terms of speeding up and reducing error, overshoot, and oscillation, as well as reducing ISE and IAE values. A modelization of a differential drive mobile robot is presented. The developed algorithm is tested and implemented to this mobile robot model via Simulink/MATLAB.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%