Type-3 Fuzzy Logic-Based Robust Speed Control for an Indirect Vector-Controlled Induction Motor

Induction motors require effective speed controllers to handle challenging conditions such as indirect vector control, nonlinear dynamics, load-disturbances, and changes in rotor resistance. Although proportional–integral (PI) controllers and type-1 fuzzy logic controllers (T1-FLC) are relatively straightforward to implement, they can produce significant overshoot and slow recovery; type-2 fuzzy logic controllers (T2-FLC), on the other hand, improve uncertainty management at the cost of higher computational complexity. This study proposes a type-3 fuzzy logic controller (T3-FLC) that balances robustness with a single α-slice using two inputs and seven membership functions per input (49 rules). In six comparison scenarios, the type-3 FLC (T3-FLC) consistently offers a lower overshoot percentage and shorter recovery/settling times than the PI controller and type-1 FLC (T1-FLC). Overshoot drops to 0.13% with T3-FLC during a high-speed positive step, while this value for the PI controller is 4.43%. During a low-amplitude positive step, T3-FLC reaches 1.37%, while the PI controller reaches 11.12% and T1-FLC reaches 4.13%. After load torque is removed, the recovery time trec under T3-FLC is 0.064 s at high speed and 0.158 s at low speed, while for PI, these values are 0.400 s and 1.975 s, respectively. Under variations in rotor resistance, T3-FLC maintains a significantly smaller overshoot value: with a −20% change (3–6 s window), the values are 1.45% (T3-FLC) versus 9.59% (PI) and 4.51% (T1-FLC); with a +20% change (3–6 s), the values are 0.14% (T3-FLC) versus 4.36% (PI) and 0.15% (T1-FLC). Although there are isolated cases in which PI or T1-FLC shows a marginal advantage in a single metric (e.g., slightly smaller overshoot during transition or lower peak error during disturbance), T3-FLC generally provides the best balance, combining low overshoot with short settling/recovery time while keeping steady-state error at zero in all scenarios.

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Publication Details

Journal
Applied Sciences
Published
2025-11-12
DOI
https://doi.org/10.3390/app152211994
Citations
3
Primary Topic
Sensorless Control of Electric Motors
Type
article
Field-Weighted Citation Impact
2.19
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article

Type-3 Fuzzy Logic-Based Robust Speed Control for an Indirect Vector-Controlled Induction Motor

Cafer Bal
3 citations
Applied Sciences
Sensorless Control of Electric Motors
2.19
article

Type-3 Fuzzy Logic-Based Robust Speed Control for an Indirect Vector-Controlled Induction Motor

Cafer Bal
article en
3 citations

Abstract

Induction motors require effective speed controllers to handle challenging conditions such as indirect vector control, nonlinear dynamics, load-disturbances, and changes in rotor resistance. Although proportional–integral (PI) controllers and type-1 fuzzy logic controllers (T1-FLC) are relatively straightforward to implement, they can produce significant overshoot and slow recovery; type-2 fuzzy logic controllers (T2-FLC), on the other hand, improve uncertainty management at the cost of higher computational complexity. This study proposes a type-3 fuzzy logic controller (T3-FLC) that balances robustness with a single α-slice using two inputs and seven membership functions per input (49 rules). In six comparison scenarios, the type-3 FLC (T3-FLC) consistently offers a lower overshoot percentage and shorter recovery/settling times than the PI controller and type-1 FLC (T1-FLC). Overshoot drops to 0.13% with T3-FLC during a high-speed positive step, while this value for the PI controller is 4.43%. During a low-amplitude positive step, T3-FLC reaches 1.37%, while the PI controller reaches 11.12% and T1-FLC reaches 4.13%. After load torque is removed, the recovery time trec under T3-FLC is 0.064 s at high speed and 0.158 s at low speed, while for PI, these values are 0.400 s and 1.975 s, respectively. Under variations in rotor resistance, T3-FLC maintains a significantly smaller overshoot value: with a −20% change (3–6 s window), the values are 1.45% (T3-FLC) versus 9.59% (PI) and 4.51% (T1-FLC); with a +20% change (3–6 s), the values are 0.14% (T3-FLC) versus 4.36% (PI) and 0.15% (T1-FLC). Although there are isolated cases in which PI or T1-FLC shows a marginal advantage in a single metric (e.g., slightly smaller overshoot during transition or lower peak error during disturbance), T3-FLC generally provides the best balance, combining low overshoot with short settling/recovery time while keeping steady-state error at zero in all scenarios.

Applied SciencesVol. 15(22)
Fırat University (TR)
Openalex Percentile: Top 11%
Sensorless Control of Electric Motors
2.19
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