Improved Path Tracking Control in Mobile Robots Using a Hybrid FOPID Controller with Backstepping Technique: An Experimental Study
Why this work is in the frame
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Bibliographic record
Abstract
This study aims to address the challenge of low-cost hardware implementation of a combined backstepping with fractional order PID (FOPID) controller for mobile robots in real-time applications.Moreover, this work proposes a self-designed mobile robot prototype that is easy to realize, low in cost, spares time, and reduces human effort.This robot platform was equipped with two DC motors with quadratic encoders and two passive wheels, controlled by an Arduino mega, where the software code was developed in the Matlab-Simulink environment, using Simulink support package for Arduino.Four case studies were conducted to demonstrate the effectiveness of the suggested methodology.Experimental results demonstrate improved trajectory tracking performance with less tracking error and smooth control efforts, and is capable of handling trajectories with continuous and non-continuous gradients.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it