Abstract
Quadcopters are four propellers unmanned aerial vehicles (UAVs) which have various applications such as rescue, remote sensing, and surveying. Providing stability and reliable tracking performance are among important criteria in the controller designs for these systems. Proportional integral derivative (PID) controller is one of the commonly used schemes to create a stable movement for UAVs. Utilizing this controller requires a precise tuning and initialization of its parameters. An optimized tuning of PID controller coefficients leads to an appropriate performance trajectory for quadcopter. In this paper, optimal tuning of quadcopter’s PID controller gains is investigated, which is previously performed by classic methods such as Ziegler-Nichols (ZN) and primary metaheuristic algorithms like Genetic Algorithm (GA), the Crow Search Algorithm (CSA), and Particle swarm Optimization (PSO). An improved Biogeography-Based Optimization (BBO) algorithm is proposed to design a PID controller and stabilize the movements of quadcopters. Numerical results indicate that the controller is stable and effective.
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References
Obias, K.C.U., Say, M.F.Q., Fernandez, E.A.V., Chua, A.Y., Sybingco, E.: A study of the interaction of proportional-integral-derivative (PID) control in a quadcopter unmanned aerial vehicle (UAV) using design of experiment. In: 2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), pp. 1–4. IEEE (2019)
Vamsi, D.S., Tanoj, T.S., Krishna, U.M., Nithya, M.: Performance analysis of PID controller for path planning of a quadcopter. In: 2019 2nd International Conference on Power and Embedded Drive Control (ICPEDC), pp. 116–121. IEEE (2019)
Bao, N., Ran, X., Wu, Z., Xue, Y., Wang, K.: Research on attitude controller of quadcopter based on cascade PID control algorithm. In: 2017 IEEE 2nd Information Technology, Networking, Electronic and Automation Control Conference (ITNEC), pp. 1493–1497. IEEE (2017)
Castillo-Zamora, J.J., Camarillo-GóMez, K.A., PéRez-Soto, G.I., RodrÃGuez-ReséNdiz, J.: Comparison of PD, PID and sliding-mode position controllers for V–tail quadcopter stability. IEEE Access 6, 38086–38096 (2018)
Lukmana, M.A., Nurhadi, H.: Preliminary study on unmanned aerial vehicle (UAV) quadcopter using PID controller. In: 2015 International Conference on Advanced Mechatronics, Intelligent Manufacture, and Industrial Automation (ICAMIMIA), 2015: IEEE, pp. 34–37
Sahul, M., Chander, V.N., Kurian, T.: A novel method on disturbance rejection PID controller for quadcopter based on optimization algorithm. IFAC Proceedings Volumes 47(1), 192–199 (2014)
Katiar, A., Rashdi, R., Ali, Z., Baig, U.: Control and stability analysis of quadcopter. In: 2018 International Conference on Computing, Mathematics and Engineering Technologies (iCoMET), pp. 1–6. IEEE (2018)
Sheta, A., Braik, M., Maddi, D.R., Mahdy, A., Aljahdali, S., Turabieh, H.: Optimization of PID controller to stabilize quadcopter movements using meta-heuristic search algorithms. Appl. Sci. 11(14), 6492 (2021)
Sulila, M.S., Riyadi, M.A.: Particle swarm optimization (PSO)-based self tuning proportional, integral, derivative (PID) for bearing navigation control system on quadcopter. In: 2017 4th International Conference on Information Technology, Computer, and Electrical Engineering (ICITACEE), pp. 181–186. IEEE (2017)
Yazid, E., Garrat, M., Santoso, F.: Optimal PD tracking control of a quadcopter drone using adaptive PSO algorithm. In: 2018 International Conference on Computer, Control, Informatics and its Applications (IC3INA), pp. 146–151. IEEE (2018)
Say, M.F.Q., Sybingco, E., Bandala, A.A., Vicerra, R.R.P., Chua, A.Y.: A genetic algorithm approach to PID tuning of a quadcopter UAV model. In: 2021 IEEE/SICE International Symposium on System Integration (SII), pp. 675–678. IEEE (2021)
Siti, I., Mjahed, M., Ayad, H., El Kari, A.: New trajectory tracking approach for a quadcopter using genetic algorithm and reference model methods. Appl. Sci. 9(9), 1780 (2019)
El Gmili, N., Mjahed, M., El Kari, A., Ayad, H.: Particle swarm optimization and cuckoo search-based approaches for quadrotor control and trajectory tracking. Appl. Sci. 9(8), 1719 (2019)
Salem, A.S., Elias, C.M., Shehata, O.M., Morgan, E.I.: Investigation of various optimization algorithms in tuning fuzzy logic-based trajectory tracking control of quadcopter. In: 2020 8th International Conference on Control, Mechatronics and Automation (ICCMA), pp. 82–87. IEEE (2020)
Simon, D.: Biogeography-based optimization. IEEE Trans. Evol. Comput. 12(6), 702–713 (2008)
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Ziamanesh, S., Tavaana, A., Ghavifekr, A.A., Farzamnia, A., Salimi, H. (2022). Optimizing PID Controller Coefficients Using an Improved Biogeography-Based Optimization to Stabilize Movements of Quadcopters. In: Wahab, N.A., Mohamed, Z. (eds) Control, Instrumentation and Mechatronics: Theory and Practice. Lecture Notes in Electrical Engineering, vol 921. Springer, Singapore. https://doi.org/10.1007/978-981-19-3923-5_11
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DOI: https://doi.org/10.1007/978-981-19-3923-5_11
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