Adaptive Controller with PID, FOPID, and NPID Compensators for Tracking Control of Electric – Wind Vehicle
Abstract
This paper presents a new combination between the Model Reference Adaptive Control (MRAC) with several types of PID’s controllers (PID, Fractional order PID (FOPID), and Nonlinear PID (NPID)) optimized using a new Covid-19 algorithm. The proposed control techniques had been applied on a new model for an electric-wind vehicle, which can catch the wind that blows in the opposite direction of a moving vehicle to receive wind; a wind turbine is installed on the vehicle’s front. The generator converts wind energy into electricity and stores it into a backup battery to switch it when the primary battery is empty. The simulation results prove that the new model of electric–wind vehicles will save power and allow the vehicle to continue moving while the other battery charges. In addition, a comparative study between different types of control algorithms had been developed and investigated to improve the vehicle dynamic response. The comparison shows that the MRAC with the NPID compensator can absorb the nonlinearity (air resistance and wheel friction) where it has a minimum overshoot, rise time, and settling time (35 seconds) among other control techniques compensators (PID and FOPID).
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A. O. Kıyaklı and H. Solmaz, “Modeling of an Electric Vehicle with MATLAB/Simulink,” Int. J. Automot. Sci. Technol., vol. 2, no. 4, pp. 9–15, 2018, doi: 10.30939/ijastech.475477.
G. Wang, Y. Ji, L. Ren, H. Leng, and Y. Huang, “Performance analysis of a newly designed single air spring running gear for automated people mover (APM),” Veh. Syst. Dyn., vol. 59, no. 12, pp. 1963–1986, 2021, doi: 10.1080/00423114.2020.1798475.
S. S. Salins, A. A. Khan, K. Riyaz, I. Mahmoud, S. Naeem, and K. H. Sachidananda, “Fabrication and working of a compressed air vehicle,” J. Eur. des Syst. Autom., vol. 54, no. 1, pp. 97–103, 2021, doi: 10.18280/jesa.540111.
J. Niu, Y. Wang, F. Liu, and R. Li, “Numerical study on comparison of detailed flow field and aerodynamic performance of bogies of stationary train and moving train,” Veh. Syst. Dyn., vol. 59, no. 12, 2021, doi: 10.1080/00423114.2020.1794015.
F. N. Morgin Carlos, B. M. Fotso, R. C. Talawo, and M. Fogue, “Aerodynamic Analysis of an Electric Vehicle Equipped With Horizontal Axis Savonius Wind Turbines,” Int. J. Recent Trends Eng. Res., vol. 5, no. 6, pp. 17–26, 2019, doi: 10.23883/ijrter.2019.5057.lkaxl.
Z. Chen, “Relationship between track stiffness and dynamic performance of vehicle–track–bridge system,” Veh. Syst. Dyn., pp. 1–19, 2020, doi: 10.1080/00423114.2020.1792942.
Y. Zhu, M. Feng, X. Wang, and X. Xu, “Research on intelligent vehicle autonomous overtaking based on single neuron pid control,” in Proceeding of IEEE CCIS2012, 2012, pp. 2–5.
A. Dinc and M. Otkur, “Optimization of Electric Vehicle Battery Size and Reduction Ratio Using Genetic Algorithm,” in 2020 11th International Conference on Mechanical and Aerospace Engineering, 2020, pp. 281–285, doi: 10.1109/icmae50897.2020.9178899.
M. F. Hossain and N. Fara, “Integration of wind into running vehicles to meet its total energy demand,” Energy, Ecol. Environ., vol. 2, no. 1, pp. 35–48, 2017, doi: 10.1007/s40974-016-0048-1.
M. R. Awal, M. Jusoh, M. N. Sakib, F. S. Hossain, M. R. Che Beson, and S. A. Aljunid, “Design and implementation of Vehicle Mounted Wind Turbine,” ARPN J. Eng. Appl. Sci., vol. 10, no. 19, pp. 8699–8706, 2015.
Z.-J. Guo and X.-Y. Kang, “Modeling and Analysis of Vehicle with Wind-solar Photovoltaic Hybrid Generating System,” in 4th International Conference on Sustainable Energy and Environmental Engineering, 2016, pp. 566–570, doi: 10.2991/icseee-15.2016.95.
S. P. Venkatesan, J. K. Soni, and A. Burugpalli, “Increasing efficiency of a wind turbine using a convergent nozzle in combination with a flanged diffuser,” Int. J. Appl. Eng. Res., vol. 10, no. 11, pp. 10234–10240, 2015.
Y. Cao, X. Li, G. Wu, X. Chen, and X. Tian, “Design and optimization of vertical axis wind turbine,” Appl. Mech. Mater., vol. 150, pp. 148–153, 2012, doi: 10.4028/www.scientific.net/AMM.150.148.
M. Shamseldin, M. A. Ghany, and Y. Hendawey, “Optimal Nonlinear PID Speed Control Based on Harmony Search for An Electric Vehicle Optimal Nonlinear PID Speed Control Based on Harmony Search for An Electric,” Futur. Eng. J., vol. 2, no. 1, 2021.
A. Gaurav and A. Gaur, “Modelling of Hybrid Electric Vehicle Charger and Study the Simulation Results,” in 2020 International Conference on Emerging Frontiers in Electrical and Electronic Technologies (ICEFEET), 2020, pp. 1–6, doi: 10.1109/icefeet49149.2020.9187007.
S. S. Salins, A. Hashim, K. A. M. Ansar, M. Hafeez, M. J. Saleem, C. P. Selvan M. “Design and Fabrication of Wind Powered Vehicle,” Glob. J. Adv. Eng. Technol., vol. 7, no. 1, 2018.
Y. Gong, Y. Liu, and Z. Tang, “Path tracking of unmanned vehicle based on parameters self-tuning fuzzy control,” 2013 IEEE Int. Conf. Cyber Technol. Autom. Control Intell. Syst. IEEE-CYBER 2013, pp. 52–57, 2013, doi: 10.1109/CYBER.2013.6705419.
T. Y. Kim and S. H. LEE, “Combustion and Emission Characteristics of Wood Pyrolysis Oil-Butanol Blended Fuels in a Di Diesel Engine,” International Journal of Automotive Technology, vol. 13, no. 2, pp. 293–300, 2012, doi: 10.1007/s12239.
U. H. Rathod, V. Kulkarni, and U. K. Saha, “On the application of machine learning in savonius wind turbine technology: An estimation of turbine performance using artificial neural network and genetic expression programming,” J. Energy Resour. Technol. Trans. ASME, vol. 144, no. 6, pp. 1–16, 2022, doi: 10.1115/1.4051736.
Z. Bitar, S. Al Jabi, and I. Khamis, “Modeling and simulation of series DC motors in electric car,” Energy Procedia, vol. 50, pp. 460–470, 2014, doi: 10.1016/j.egypro.2014.06.056.
M. A. Shamseldin, “Optimal Coronavirus Optimization Algorithm Based PID Controller for High Performance Brushless DC Motor,” algorithms Artic., vol. 14, p. 17, 2021.
A. Rehman Khan, A. Tamoor Khan, M. Salik, and S. Bakhsh, “An Optimally Configured HP-GRU Model Using Hyperband for the Control of Wall Following Robot,” Int. J. Robot. Control Syst., vol. 1, no. 1, pp. 66–74, 2021, doi: 10.31763/ijrcs.v1i1.281.
A. Ouda and A. Mohamed, “Autonomous Fuzzy Heading Control for a Multi-Wheeled Combat Vehicle,” Int. J. Robot. Control Syst., vol. 1, no. 1, pp. 90–101, 2021, doi: 10.31763/ijrcs.v1i1.286.
R. Boucetta, W. Abdallah, and S. Bel Hadj Ali, “An Adaptive Control for the Path Tracking of an Active Leg Prosthesis,” Int. J. Robot. Control Syst., vol. 1, no. 2, pp. 159–176, 2021, doi: 10.31763/ijrcs.v1i2.350.
X. Wei-hong, C. Li-jia, and Z. Chun-lai, “Review of Aerial Manipulator and its Control,” Int. J. Robot. Control Syst., vol. 1, no. 3, pp. 308–325, 2021, doi: 10.31763/ijrcs.v1i3.363.
A. N. Kadjie and E. B. T. Tchuisseu, “A Multifunction Robot Based on the Slider-Crank Mechanism: Dynamics and Optimal Configuration for Energy Harvesting,” Int. J. Robot. Control Syst., vol. 1, no. 3, pp. 269–284, 2021.
E. Rahimi khoygani, M. R. Rahimi khoygani, and R. Ghasemi, “Intelligent Observer-Based Controller Design for Nonlinear Type-1 Diabetes Model via Adaptive Neural Network Method,” Int. J. Robot. Control Syst., vol. 1, no. 3, pp. 338–354, 2021, doi: 10.31763/ijrcs.v1i3.442.
E. S. Rahayu, A. Ma’arif, and A. Çakan, “Particle Swarm Optimization (PSO) Tuning of PID Control on DC Motor,” Int. J. Robot. Control Syst., vol. 2, no. 2, pp. 435–447, 2022.
M. Tahmasebi, M. Gohari, and A. Emami, “An Autonomous Pesticide Sprayer Robot with a Color-based Vision System,” Int. J. Robot. Control Syst., vol. 2, no. 1, pp. 115–123, 2022, doi: 10.31763/ijrcs.v2i1.480.
Y. Zahraoui, M. Akherraz, and A. Ma’arif, “A Comparative Study of Nonlinear Control Schemes for Induction Motor Operation Improvement,” Int. J. Robot. Control Syst., vol. 2, no. 1, pp. 1–17, 2021, doi: 10.31763/ijrcs.v2i1.521.
A. K. Ali and M. M. Mahmoud, “Methodologies and Applications of Artificial Intelligence in Systems Engineering,” Int. J. Robot. Control Syst., vol. 2, no. 1, pp. 201–229, 2022, doi: 10.31763/ijrcs.v2i1.532.
H. A. Hefny and S. S. Azab, “Chaotic particle swarm optimization,” INFOS2010 - 2010 7th Int. Conf. Informatics Syst., vol. 1, no. 4, pp. 523–533, 2010.
A. W. L. Yao and H. C. Chen, “An Intelligent Color Image Recognition and Mobile Control System for Robotic Arm,” Int. J. Robot. Control Syst., vol. 2, no. 1, pp. 97–104, 2022, doi: 10.31763/ijrcs.v2i1.557.
M. H. H. Rosman et al., “Real-Time Underground Plastic Pipeline Water Leakage Detection and Monitoring System,” Int. J. Robot. Control Syst., vol. 2, no. 2, pp. 424–434, 2022.
M. Maaruf, M. S. Mahmoud, A. Ma'arif, “A Survey of Control Methods for Quadrotor UAV,” Int. J. Robot. Control Syst., vol. 2, no. 4, pp. 652–664, 2022.
M. S. Mahmoud and A. H. AlRamadhan, “Optimizing the Parameters of Sliding Mode Controllers for Stepper Motor through Simulink Response Optimizer Application,” Int. J. Robot. Control Syst., vol. 1, no. 2, pp. 209–225, 2021.
M. I. Faiq Hatta and N. Satya Widodo, “Robot Operating System (ROS) in Quadcopter Flying Robot Using Telemetry System,” Int. J. Robot. Control Syst., vol. 1, no. 1, pp. 54–65, 2021, doi: 10.31763/ijrcs.v1i1.247.
D. S. Febriyan and R. Dwi Puriyanto, “Implementation of DC Motor PID Control On Conveyor for Separating Potato Seeds by Weight,” Int. J. Robot. Control Syst., vol. 1, no. 1, pp. 15–26, 2021, doi: 10.31763/ijrcs.v1i1.221.
M. H. Iqbal and W. S. Aji, “Wall Following Control System with PID Control and Ultrasonic Sensor for KRAI 2018 Robot,” Int. J. Robot. Control Syst., vol. 1, no. 1, pp. 1–14, 2021, doi: 10.31763/ijrcs.v1i1.206.
M. A. Shamseldin et al., “A New Design Identification and Control Based on GA Optimization for an Autonomous Wheelchair,” Robotics, vol. 11, no. 5, p. 101, 2022.
L. M. El-Τehewy, M. Α. Shamseldin, M. Sallam, and Α. M. Abdel Ghany, “A Modified Model Reference Adaptive Control for High-Performance Pantograph Robot Mechanism,” Wseas Trans. Appl. Theor. Mech., vol. 16, pp. 193–203, 2021, doi: 10.37394/232011.2021.16.22.
M. A. Shamseldin, “Optimal Covid-19 Based PD/PID Cascaded Tracking Control for Robot Arm driven by BLDC Motor,” Wseas Trans. Syst., vol. 20, pp. 217–227, 2021, doi: 10.37394/23202.2021.20.24.
E. Emad, O. Alaa, M. Hossam, M. Ashraf, and M. A. Shamseldin, “Design and Implementation of a Low-Cost Microcontroller-Based an Industrial Delta Robot,” Wseas Trans. Comput., vol. 20, pp. 289–300, 2021, doi: 10.37394/23205.2021.20.32.
M. A. Ghany and M. A. Shamseldin, “Sliding Mode Self-Tuned Single Neuron PID Controller for Power System Stabilizer,” Wseas Trans. Comput., vol. 20, pp. 309–320, 2021, doi: 10.37394/23205.2021.20.34.
X. Xi, A. Poo, and G. Hong, “Tracking error-based static friction compensation for a bi-axial CNC machine,” Precis. Eng., vol. 34, no. 3, pp. 480–488, 2010, doi: 10.1016/j.precisioneng.2009.12.003.
V. Nguyen and C. Lin, “Adaptive PD Networks Tracking Control with Full- State Constraints for Redundant Parallel Manipulators,” in IFSA-SCIS 2017, 2017, no. 4, pp. 0–4.
S. Wen, T. Wang, Z. Ma, and X. Li, “Dynamics Modeling and Fuzzy PD Control of Humanoid Arm,” in Proceedings of the 36th Chinese Control Conference, 2017, no. 3, pp. 616–621.
A. Bennaoui, S. Saadi, and A. Ameur, “Performance Comparison of MFO and PSO for Optimal Tuning the fractional order fuzzy PID Controller for A DC-DC Boost Converter,” 2020 Int. Conf. Electr. Eng. ICEE 2020, 2020, doi: 10.1109/ICEE49691.2020.9249778.
M. A. Abdel Ghany, M. A. Shamseldin, and A. M. Abdel Ghany, “A novel fuzzy self tuning technique of single neuron PID controller for brushless DC motor,” Int. J. Power Electron. Drive Syst., vol. 8, no. 4, 2017, doi: 10.11591/ijpeds.v8i4.pp1705-1713.
J. C. Shen and C. S. Ye, “Precision Fuzzy Sliding-mode Tracking Control with DNLRX Model Based Friction,” in 2018 SICE International Symposium on Control Systems (SICE ISCS), pp. 27-32 2018.
A. A. El-samahy and M. A. Shamseldin, “Brushless DC motor tracking control using self-tuning fuzzy PID control and model reference adaptive control,” Ain Shams Eng. J., 2016, doi: 10.1016/j.asej.2016.02.004.
A. Franchi and A. Mallet, “Adaptive Closed-loop Speed Control of BLDC Motors with Applications to Multi-rotor Aerial Vehicles,” in 2017 IEEE International Conference on Robotics and Automation (ICRA) Singapore., 2017, no. 978, pp. 5203–5208.
W. Netto, R. Lakhani, and S. M. Sundaram, “Design and performance comparison of different adaptive control schemes for pitch angle control in a Twin-Rotor-MIMO-System,” Int. J. Electr. Comput. Eng., vol. 9, no. 5, pp. 4114–4129, 2019, doi: 10.11591/ijece.v9i5.pp4114-4129.
L. Yang, Z. Q. Zhu, B. Shuang, and H. Bin, “Adaptive Threshold Correction Strategy for Sensorless High-Speed Brushless DC Drives Considering Zero-Crossing-Point Deviation,” IEEE Trans. Ind. Electron., vol. 67, no. 7, pp. 5246–5257, 2020, doi: 10.1109/TIE.2019.2931501.
P. Swarnkar, “Effect of Adaptation Gain in Model Reference Adaptive Controlled Second Order System,” Eng. Technol. Appl. Sci. Res., vol. 1, no. 3, pp. 70–75, 2011.
R. Madiouni, “Robust PID Controller Design based on Multi-Objective Particle Swarm Optimization Approach,” in ICEMIS2017, 2017, pp. 1–7.
C. Sun, G. Gong, F. Wang, H. Yang, and X. Ouyang, “Single Neuron Adaptive PID Control for Hydro-viscous Drive Clutch,” in 12th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications (MESA), 2016, no. 3, pp. 3–6.
A. M. Khalid, H. M. Hamza, S. Mirjalili, and K. M. Hosny, " BCOVIDOA: A Novel Binary Coronavirus Disease Optimization Algorithm for Feature Selection," Knowledge-Based Systems, vol. 248, 2022.
F. Martínez-Álvarez et al., “Coronavirus Optimization Algorithm: A Bioinspired Metaheuristic Based on the COVID-19 Propagation Model,” Big Data, vol. 8, no. 4, pp. 308–322, 2020, doi: 10.1089/big.2020.0051.
S. A. Alanazi, M. M. Kamruzzaman, M. Alruwaili, N. Alshammari, S. A. Alqahtani, and A. Karime, “Measuring and Preventing COVID-19 Using the SIR Model and Machine Learning in Smart Health Care,” J. Healthc. Eng., vol. 2020, 2020, doi: 10.1155/2020/8857346.
DOI: https://doi.org/10.18196/jrc.v3i5.15855
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