Comparison between Genetic Algorithms of Proportional–Integral–Derivative and Linear Quadratic Regulator Controllers, and Fuzzy Logic Controllers for Cruise Control System
Abstract
:1. Introduction
2. Model of the Cruise Control System
3. Controller Design
3.1. PID and LQR Controllers with the GA Optimization Method
3.2. Fuzzy Logic Controller
- Negative big (NB);
- Negative medium (NM);
- Negative small (NS);
- Zero (Z);
- Positive small (PS);
- Positive medium (PM);
- Positive big (PB).
4. Simulation and Results
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Parameter/Specification | Value |
---|---|
C1 | 743 |
Ca | 1.19 N (m/s)2 |
M | 1599 kg |
τ | 0.2 s |
T | 1 s |
Fdmax | 3500 N |
Fdmin | −3500 N |
g | 9.8 m/s2 |
v | 30 Km/h |
PE\CE | NB | NM | NS | ZR | PS | PM | PB |
---|---|---|---|---|---|---|---|
NB | NB | NB | NB | NB | NS | Z | PS |
NM | NB | NB | NB | NM | NS | Z | PS |
NS | NB | NB | NM | NS | Z | PS | PM |
Z | NB | NM | NS | Z | PS | PM | PB |
PS | NM | NS | Z | PS | PM | PB | PB |
PM | NS | Z | PS | PM | PB | PB | PB |
PB | Z | PS | PM | PB | PB | PB | PB |
Controller | Kp | Ki | Kd |
---|---|---|---|
PID-MSE | 2.8 | 0.437 | 2 |
PID-ISE | 2.8 | 1.247 | 2 |
PID-ITSE | 2.8 | 0.4 | 2 |
PID-ITAE | 2.8 | 0.493 | 2 |
Controller | K11 | K22 | K33 |
---|---|---|---|
LQR-ISE | 0.0204 | 1.5362 | 1.4038 |
LQR-ITSE | 0.1968 | 4.4657 | 3.5938 |
LQR-ITAE | 0.0898 | 1.5708 | 1.4131 |
LQR-MSE | 7.3238 | 6.9351 | 3.8548 |
Controller | %MP | Tr (s) | Ts (s) | Ess | Jmin |
---|---|---|---|---|---|
PID-MSE | 10.1 | 1.483 | 11.118 | 0 | 22.701 |
PID-ISE | 27.564 | 1.072 | 10.859 | 0 | 39.495 |
PID-ITSE | 9.2 | 1.471 | 11.407 | 0 | 22.078 |
PID-ITAE | 11.3 | 1.502 | 10.759 | 0 | 23.561 |
LQR-MSE | 3.646 | 1.232 | 4.316 | 0 | 9.194 |
LQR-ISE | 0.496 | 2.033 | 5.498 | 0 | 8.027 |
LQR-ITSE | 0.503 | 4.146 | 8.748 | 0 | 13.397 |
LQR-ITAE | 0.495 | 1.961 | 5.419 | 0 | 7.875 |
Controller | %MP | Tr (s) | Ts (s) | Ess | Jmin |
---|---|---|---|---|---|
PID-GA | 9.2 | 1.471 | 11.407 | 0 | 22.078 |
LQR-GA | 0.495 | 2.018 | 5.419 | 0 | 7.932 |
Fuzzy | 0.476 | 2.131 | 5.926 | 0.011 | 8.544 |
Fuzzy-I | 0.472 | 2.145 | 5.232 | 0 | 7.849 |
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Mahmood, A.; Al-bayati, K.Y.A.; Szabolcsi, R. Comparison between Genetic Algorithms of Proportional–Integral–Derivative and Linear Quadratic Regulator Controllers, and Fuzzy Logic Controllers for Cruise Control System. World Electr. Veh. J. 2024, 15, 351. https://doi.org/10.3390/wevj15080351
Mahmood A, Al-bayati KYA, Szabolcsi R. Comparison between Genetic Algorithms of Proportional–Integral–Derivative and Linear Quadratic Regulator Controllers, and Fuzzy Logic Controllers for Cruise Control System. World Electric Vehicle Journal. 2024; 15(8):351. https://doi.org/10.3390/wevj15080351
Chicago/Turabian StyleMahmood, Ali, Karrar Y.A. Al-bayati, and Róbert Szabolcsi. 2024. "Comparison between Genetic Algorithms of Proportional–Integral–Derivative and Linear Quadratic Regulator Controllers, and Fuzzy Logic Controllers for Cruise Control System" World Electric Vehicle Journal 15, no. 8: 351. https://doi.org/10.3390/wevj15080351
APA StyleMahmood, A., Al-bayati, K. Y. A., & Szabolcsi, R. (2024). Comparison between Genetic Algorithms of Proportional–Integral–Derivative and Linear Quadratic Regulator Controllers, and Fuzzy Logic Controllers for Cruise Control System. World Electric Vehicle Journal, 15(8), 351. https://doi.org/10.3390/wevj15080351