The Autonomous Performance Improvement of Mobile Robot using Type-2 Fuzzy Self-Tuning PID Controller

2016 ◽  
Author(s):  
Sang Hyuk Park ◽  
Ki Woo Kim ◽  
Won Hyuk Choi ◽  
Min Seok Jie ◽  
Young In Kim
Keyword(s):  
Mobile Robot ◽  
Performance Improvement ◽  
Pid Controller ◽  
Self Tuning

scholarly journals Design Interval Type-2 Fuzzy Like (PID) Controller for Trajectory Tracking of Mobile Robot

2019 ◽  
pp. 1-15
Keyword(s):  
Fuzzy Logic ◽  
Mobile Robot ◽  
Mobile Robots ◽  
Trajectory Tracking ◽  
Pid Controller ◽  
Kinematic Model ◽  
Superior Performance ◽  
Fuzzy Like ◽  
Interval Type

One of the major problems in the field of mobile robots is the trajectory tracking problem. There are a big number of investigations for different control strategies that have been used to control the motion of the mobile robot when the nonlinear kinematic model of mobile robots was considered. The trajectory tracking control of autonomous wheeled mobile robot in a changing unstructured environment needs to take into account different types of uncertainties. Type-1 fuzzy logic sets present limitations in handling those uncertainties while type-2 fuzzy logic sets can manage these uncertainties to give a superior performance. This paper focuses on the design of interval type-2 fuzzy like proportional-integral-derivative (PID) controller for the kinematic model of mobile robot. The firefly optimization algorithm has been used to find the best values of controller’s parameters. The aim of this controller is trying to force the mobile robot tracking a pre-defined continuous path with minimum tracking error. The Matlab simulation results demonstrate the good performance and robustness of this controller. These were confirmed by the obtained values of the position tracking errors and a very smooth velocity, especially with regards to the presence of external disturbance or change in the initial position of mobile robot. Finally, in comparison with other proposed controllers, the results of nonlinear IT2FLC PID controller outperform the nonlinear PID neural controller in minimizing the MSE for all control variables and in the robustness measure.

BP Neural Network for Mobile Robot Self-Tuning PID Controller Design

2014 ◽  
Vol 898 ◽  
pp. 755-758 ◽  
Author(s):  
Wei Li ◽  
Jian Fang
Keyword(s):  
Neural Network ◽  
Mobile Robot ◽  
Bp Neural Network ◽  
Pid Controller ◽  
Controller Design ◽  
System Stability ◽  
Stabilization Control ◽  
Pid Controller Design ◽  
Self Tuning ◽  
Attitude Model

Establish the attitude model for self-designed mobile robot, According to the characteristics of nonlinear, unstable, using BP neural network method to achieve self-tuning PID parameters to make optimal parameters of the PID controller. Stabilization control of two-wheeled self-balanced robots at the same time, decrease the overshoot of the system and the number of shocks. Simulation experiments show that: Using BP neural network self-tuning PID controller improves system stability, effectiveness has been well controlled, with high practical value

Design of a Data-Driven Multi-loop Self-Tuning PID Controller

2019 ◽  
Vol 139 (4) ◽  
pp. 356-363
Author(s):  
Yoichiro Ashida ◽  
Shin Wakitani ◽  
Toru Yamamoto
Keyword(s):  
Pid Controller ◽  
Data Driven ◽  
Self Tuning
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