Speed control of a DC motor using a feedforward computed torque control scheme
Bibliographic record
Abstract
This paper presents a feedforward control scheme using an inverse dynamic model of a DC motor for speed control in the presence of changes in dynamics during motion. Conventional velocity control schemes perform well for nominal operating conditions of the motor as the gains are tuned for such operating conditions. Some of the operating conditions considered are the changes in damping torque as speed changes, the vertical load which results in frictional load when the motor is used to drive a wheeled mobile robot or automated guided vehicles, and gravity loading and centrifugal effects when the motor is used as an actuator for robot joints. The gains and the acceleration values of conventional velocity control schemes need to be retuned in order to achieve a satisfactory performance under such circumstances. Further, the amplifiers used for conventional velocity control schemes operate in voltage mode and the current output of the amplifiers is not limited. The feedforward control scheme proposed in this paper predicts the current requirement based on the changes in the dynamics of the motor and the operating environment and limits the current drawn by the motor instead of simply adjusting the voltage. The amplifier provides as much voltage needed to achieve the desired speed while the current drawn by the motor is limited to the value allowed by the inverse dynamic model. Experimental results indicate that the proposed feedforward control scheme exhibits good speed control compared to the conventional velocity control scheme.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".