Abstract
The article presents 3D crane control of all three axes (XYZ) and both angles (\(\alpha \) and \(\beta \)). PID controllers and their fractional counterparts - FOPID controllers, which have two additional parameters, were used. Previous research focused on a direct comparison of the two types of controllers. This time, the authors used various combinations to check which part of the system influences the quality of control the most. The model and simulations were implemented in the Matlab/Simulink environment. Grey-Wolf Optimizer was used to optimize the controller coefficients. Several combinations of PID and FOPID controllers were compared (e.g. 2 PID controllers on the XY axes and 3 FOPID controllers on the Z axis and \(\alpha \) and \(\beta \) angles).
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Samin, R.E., Jie, L.M., Zawawi, M.A.: PID implementation of heating tank in mini automation plant using Programmable Logic Controller (PLC). In: International Conference on Electrical, Control and Computer Engineering 2011 (InECCE), pp. 515–519 (2011)
Cortes, F., Linares, D., Patino, D., Melo, K.: A distributed model predictive control (D-MPC) for modular robots in chain configuration. In: IX Latin American Robotics Symposium and IEEE Colombian Conference on Automatic Control, pp. 1–6. IEEE (2011)
Dubois, O., Nicolas, J., Billat, A.: Adaptive neural network control of the temperature in an oven. In: IEE Colloquium on Advances in Neural Networks for Control and Systems, pp. 8/1–8/3 (1994)
Puchalski, B., Rutkowski, T.A., Duzinkiewicz, K.: Implementation of the FOPID algorithm in the PLC controller - PWR thermal power control case study. In: 23rd International Conference on Methods and Models in Automation and Robotics (MMAR), pp. 229–234 (2018)
Anbumani, K., Ranihemamalini, R., Pechinathan, G.: GWO based tuning of PID controller for a heat exchanger process. In: Third International Conference on Sensing, Signal Processing and Security (ICSSS), pp. 417–421 (2017)
Agarwal, S., Singh, A.P., Anand, N.: Evaluation performance study of Firefly algorithm, particle swarm optimization and artificial bee colony algorithm for non-linear mathematical optimization functions. In: Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT), pp. 1–8 (2013)
Machado, J.T., Kiryakova, V., Mainardi, F.: Recent history of fractional calculus. Commun. Nonlinear Sci. Numer. Simul. 16(3), 1140–1153 (2011)
Veisi, A., Delavari, H.: Adaptive fractional order control of photovoltaic power generation system with disturbance observer. In: 7th International Conference on Control, Instrumentation and Automation (ICCIA), pp. 1–5 (2021)
Feng, P., Lu, L., Xue, D.: Compensation for network data dropouts based on modified fractional-order Kalman filter. In: The 27th Chinese Control and Decision Conference (2015 CCDC), pp. 348–352 (2015)
Żegleń-Włodarczyk, J., Dziedzic, K.: Optimization of the FOPID parameters of the 3D crane control system by using GWO. In: 25th International Conference on Methods and Models in Automation and Robotics (MMAR 2021), pp. 13–18 (2021)
Dziedzic, K.: Identification of fractional order transfer function model using biologically inspired algorithms. In: Szewczyk, R., Zieliński, C., Kaliczyńska, M. (eds.) AUTOMATION 2019. AISC, vol. 920, pp. 47–57. Springer, Heidelberg (2019). https://doi.org/10.1007/978-3-030-13273-6_5
Żegleń-Włodarczyk, J., Dziedzic, K.: Optimization of the FOPID parameters of the 3D crane control system by using GWO. Paper Accepted to be Published in Proceedings of the International Conference on Fractional Differentiation and its Applications (ICFDA’21) (2021)
Oustaloup, A., Levron, F., Mathieu, B., Nanot, F.M.: Frequency-band complex noninteger differentiator: characterization and synthesis. IEEE Trans. Circuits Syst. I Fundam. Theory Appl. 47(1), 25–39 (2000)
Mirjalili, S., Mirjalili, S.M., Lewis, A.: Grey wolf optimizer. Adv. Eng. Softw. 69, 46–61 (2014). https://doi.org/10.1016/j.advengsoft.2013.12.007
Pauluk, M., Korytowski, A., Turnau, A., Szymkat, M.: Time optimal control of 3D crane. In: MMAR 2001 : Proceedings of the 7th IEEE International Conference on Methods and Models in Automation and Robotics: Miedzyzdroje 28–31 August 2001, Robotics; Marine automation; Control engineering; Identification and Signal Processing, vol. 2, pp. 927–932 (2001)
INTECO: 3D Crane User’s Manual. http://www.inteco.com.pl/Docs/3DCrane_um.pdf. Accessed 31 Mar 2021
INTECO: 3D Crane - Laboratory model of industrial gantry crane controlled from PC. http://www.inteco.com.pl/products/3d-crane/. Accessed 24 Oct 2021
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Żegleń-Włodarczyk, J., Wajda, K. (2022). PID and FOPID Controllers Combinations During Control of 3D Crane Optimized with GWO Algorithm. In: Szewczyk, R., Zieliński, C., Kaliczyńska, M. (eds) Automation 2022: New Solutions and Technologies for Automation, Robotics and Measurement Techniques. AUTOMATION 2022. Advances in Intelligent Systems and Computing, vol 1427. Springer, Cham. https://doi.org/10.1007/978-3-031-03502-9_6
Download citation
DOI: https://doi.org/10.1007/978-3-031-03502-9_6
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-03501-2
Online ISBN: 978-3-031-03502-9
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)