Data Driven Sigmoid Proportional-Integral-Derivative (SPID) Controller for Twin Rotor MIMO System
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Bibliographic record
Abstract
This paper presents a data driven Sigmoid Proportional-Integral-Derivation (SPID) controller for a Twin Rotor Multiple-Input-Multiple-Output (MIMO) System (TRMS).A time-varying PID parameters based on sigmoid function is adopted to solve the low control accuracy of the conventional PID controller.In particular, the parameters of new version controller were vigorously changed based on its error signal of sigmoid function where its variability is limited in a predefined upper and lower bound.These SPID parameters are then optimized by using Adaptive Safe Experimentation Dynamics (ASED) method such that the control performance accuracy in terms of trajectory tracking error and control input energy are minimized.The simulations of step response analysis and stability analysis are conducted to evaluate the effectiveness of the proposed SPID controller compared to PID controller on TRMS system.Consequently, the results obtained from the simulations revealed that the SPID controller has successfully produced improvement in terms of objective function, , total norm of error, ̅ 1 + ̅ 2 and total norm of output, ̅ ℎ + ̅ by reduced 6.84%, 6.38% and 4.25%, respectively compared to the PID controller.In addition, the results of Integral-Absolute-Error (IAE), Integral-Square-Error (ISE), Integral-Time-Absolute-Error (ITAE) and Integral-Square-Error (ITSE) are proven that the SPID controller is outperform on horizontal and vertical planes for TRMS system in comparison with PID controller.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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