B. Varga, S. Meier, S. Schwab, and S. Hohmann, “Model predictive control and trajectory optimization of large vehicle-manipulators,” in 2019 IEEE International Conference on Mechatronics (ICM), Ilmenau, Germany, 2019, pp. 60–66. [Google Scholar][Crossref]
2.
H. A. Azzawi, N. M. Ameen, and S. A. Gitaffa, “Comparative performance evaluation of swarm intelligencebased FOPID controllers for PMSM speed control,” J. Europ. Syst. Autom., vol. 56, no. 3, pp. 475–482, 2023. [Google Scholar][Crossref]
3.
K. Yuan, H. Shu, Y. J. Huang, Y. B. Zhang, A. Khajepour, and L. Zhang, “Mixed local motion planning and tracking control framework for autonomous vehicles based on model predictive control,” IET Intell. Transp. Syst., vol. 13, no. 6, pp. 950–959, 2019. [Google Scholar][Crossref]
4.
A. T. Humod and N. M. Ameen, “Robust nonlinear PD controller for ship steering autopilot system based on particle swarm optimization technique,” IAES Int. J. Artif. Intell., vol. 9, no. 4, pp. 662–669, 2020. [Google Scholar][Crossref]
5.
I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio, “Generative adversarial networks,” Commun. ACM, vol. 63, no. 11, pp. 139–144, 2020. [Google Scholar][Crossref]
6.
M. R. Amini, V. Feofanov, L. Pauletto, E. Devijver, and Y. Maximov, “Self-training: A survey,” arXiv:2202.12040, 2022. [Google Scholar][Crossref]
7.
S. Sanchez and P. A. Bhounsule, “Design, modeling, and control of a differential drive rimless wheel that can move straight and turn,” Automation, vol. 2, no. 3, pp. 98–115, 2021. [Google Scholar][Crossref]
8.
A. Barsan, “Position control of a mobile vehicle through PID controller,” Acta Univ. Cibiniensis, Tech. Ser., vol. 71, no. 1, pp. 14–20, 2019. [Google Scholar][Crossref]
9.
A. H. Issa, S. A. Mahmood, A. T. Humod, and N. M. Ameen, “Robustness enhancement study of augmented positive identification controller by a sigmoid function,” Int. J. Electr. Eng. Inform., vol. 12, no. 2, pp. 686–695, 2023. [Google Scholar][Crossref]
10.
D. K. Muhsen, A. T. Sadiq, and F. A. Raheem, “Memorized rapidly exploring random tree optimization (MRRTO): An enhanced algorithm for robot path planning,” Cybern. Inf. Technol., vol. 24, no. 1, pp. 190–204, 2024. [Google Scholar][Crossref]
11.
S. A. Mahmood, A. T. Humod, A. H. Issa, and N. M. Ameen, “Robust AVR based on augmented pi controller for synchronous generator,” AIP Conf. Proc., vol. 2804, p. 030005, 2023. [Google Scholar][Crossref]
12.
E. S. Rahayu, A. Ma’arif, and A. Cakan, “Particle swarm optimization (PSO) tuning of PID control on DC motor,” Int. J. Veh. Control Syst., vol. 2, no. 2, pp. 435–447, 2022. [Google Scholar][Crossref]
13.
S. Bharat, A. Ganguly, R. Chatterjee, B. Basak, D. K. Sheet, and A. Ganguly, “A review on tuning methods for PID controller,” Asian J. Converg. Technol., vol. 5, no. 1, pp. 1–4, 2019. [Google Scholar]
14.
S. B. Joseph, E. G. Dada, A. Abidemi, D. O. Oyewola, and B. M. Khammas, “Metaheuristic algorithms for PID controller parameters tuning: Review, approaches and open problems,” Heliyon, vol. 8, no. 5, p. e09399, 2022. [Google Scholar][Crossref]
15.
C. Jeyachandran and M. Rajaram, “Neural network based predictive, NARMA-L2 and neuro-fuzzy control for a CSTR process,” J. Eng. Appl. Sci., vol. 5, no. 3, pp. 30–42, 2011. [Google Scholar]
16.
Y. Kondratenko, K. Wang, O. Kozlov, A. Shevchenko, and A. Denysenko, “Neural network control of the mobile robotic platform’s adhesion force,” CEUR Workshop Proc., vol. 3538, pp. 65–77, 2023. [Google Scholar]
17.
K. Srakaew, V. Sangveraphunsiri, S. Chantranuwathana, and R. Chancharoen, “Design of NARMA L2 neurocontroller for nonlinear dynamical system,” in 29th International Conference on Modeling, Identification, and Control, Innsbruck, Austria, 2010, pp. 210–215. [Google Scholar]
18.
A. S. Al-Araji, A. K. Ahmed, and K. E. Dagher, “A cognition path planning with a nonlinear controller design for wheeled mobile robot based on an intelligent algorithm,” J. Eng., vol. 25, no. 1, pp. 64–83, 2019. [Google Scholar][Crossref]
19.
K. Shojaei, A. Tarakameh, and A. M. Shahri, “Adaptive trajectory tracking of WMRs based on feedback linearization technique,” in 2009 International Conference on Mechatronics and Automation, Changchun, China, 2009, pp. 729–734. [Google Scholar][Crossref]
20.
A. F. Mohammed, N. Basil, R. B. Abdulmaged, H. M. Marhoon, H. M. Ridha, A. Ma’arif, and I. Suwarno, “Selection and evaluation of robotic arm based conveyor belts (RACBs) motions: NARMA (L2)-FO (ANFIS) PD-I based jaya optimization algorithm,” Int. J. Robot. Control Syst., vol. 4, no. 1, pp. 262–290, 2024. [Google Scholar][Crossref]