Abstract
Designing effective PID controllers for gimbal payload systems (GPS) in naval applications poses inherent challenges due to the dynamic nature of these systems. The gimbal system requires precise control to stabilize its line of sight (LOS) for accurate target tracking in electro-optical systems. Conventional PID controllers often struggle to address the complex dynamics and nonlinearities inherent in gimbal systems, resulting in suboptimal performance. Therefore, in this study, we introduce a novel control design framework for the gimbal payload system (GPS) employed in naval applications. A more effective PID controller is developed by utilizing the hunting mechanism of the antlion optimization technique. This controller precisely manages and stabilizes the LOS of the GPS, ensuring seamless target tracking in electro-optical systems. Furthermore, we assess the robustness of the proposed controller by varying system parameters, including moment of inertia (± 20%) and motor resistance (+ 10%). The results demonstrate robust target tracking even in the presence of changes within the system. Additionally, the gimbal system exhibits zero overshoot, and the achieved high values of gain and phase margins outperform other techniques such as genetic algorithm, particle swarm optimization, and classical methods.










Similar content being viewed by others
Data Availability
Not Applicable.
References
Masten, M. K. (2008). Inertially stabilized platforms for optical imaging systems. IEEE Control Systems Magazine, 28(1), 47–64.
Miller, R., Mooty, G., & Hilkert, J. M. (2013). Gimbal system configurations and line-of-sight control techniques for small UAV applications. Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications X, 8713, 871308.
Basilio, J. C., & Matos, S. R. (2002). Design of PI and PID controllers with transient performance specification. IEEE Transactions on Education, 45(4), 364–370.
Alcántara, S., Vilanova, R., & Pedret, C. (2013). PID control in terms of robustness/performance and servo/regulator trade-offs: A unifying approach to balanced autotuning. Journal of Process Control, 23(4), 527–542.
Roshdy, A. A., Su, C., Mokbel, H. F., & Wang, T. (2012). Design a robust PI controller for line of sight stabilization system. International Journal of Modern Engineering Research, 2(2), 144–148.
Habashi, A., Ashry, M. M., Mabrouk, M. H., & Elnashar, G. A. (2015). Controller design for line of sight stabilization system. International Journal of Engineering Research and Technology, 4(11), 650–658.
Rajesh, R. J., & Kavitha, P. (2015). ‘Camera gimbal stabilization using conventional PID controller and evolutionary algorithms’, In: 2015 IEEE International Conference on Computer, Communication and Control, pp. 1-6.
Baskin, M., & Leblebicioğlu, M. K. (2017). Robust control for line-of-sight stabilization of a two-axis gimbal system. Turkish Journal of Electrical Engineering & Computer Sciences, 25(5), 3839–3853.
Aggarwal, S., Joshi, A., & Kamal, S. (2017). ‘Line of sight stabilization of two-dimensional gimbal platform’, In 2017 IEEE International Conference on Power, Control, Signals and Instrumentation Engineering (ICPCSI), pp. 2553-2558.
Koh, E., Lee, J., Park, J., Lim, J., & Kim, D. (2019). Gimbal tracking control with delayed feedback of target information. Journal of Electrical Engineering & Technology, 14(4), 1723–1731.
Huynh, T., & Kim, Y. B. (2021). A study on gimbal motion control system design based on super-twisting control method. Journal of the Korean Society for Precision Engineering, 38(2), 115–122.
Mirjalili, S. (2015). The ant lion optimizer. Advances in Engineering Software, 83, 80–98.
Cong Danh, N. (2021). The stability of a two-axis gimbal system for the camera. The Scientific World Journal, 2021, 1–8.
Zhuang, M., & Atherton, D. P. (1993). Automatic tuning of optimum PID controllers. IEE Proceedings D (Control Theory and Applications), 140(3), 216–224.
Rahimi, K., & Famouri, P. (2014). ‘Assessment of Automatic Generation Control performance index criteria’, In 2014 IEEE PES T &D Conference and Exposition, pp. 1-5.
Zhuang, Guangming, Xia, Jianwei, Feng, Jun-e, Wang, Yanqian, & Chen, Guoliang. (2023). Dynamic compensator design and H-infi admissibilization for delayed singular jump systems via Moore-Penrose generalized inversion technique. Nonlinear Analysis: Hybrid Systems, 49, 101361.
Li, Z., Zhang, Z.-H., Wang, J.-S., Wang, K.-T., Guo, X.-Q., Fan, D.-H., & Sun, H.-X. (2023). Compensator design of permanent magnet synchronous linear motor control system based on load disturbance observer. Journal of Electrical Engineering & Technology, 18, 1–12.
Bai, Y., & Wang, D. (2011). Dynamic modelling of the laser tracking gimbal used in a laser tracking system. International Journal of Modelling, Identification and Control, 12(1/2), 149–159.
Abro, G. E. M., Bin Mohd Zulkifli, S. A., & Asirvadam, V. S. (2023). Dual-loop single dimension fuzzy-based sliding mode control design for robust tracking of an underactuated quadrotor craft. Asian Journal of Control, 25(1), 144–169.
Abro, G. E. M., Zulkifli, S. A. B. M., Ali, Z. A., Asirvadam, V. S., & Chowdhry, B. S. (2022). Fuzzy based backstepping control design for stabilizing an underactuated quadrotor craft under unmodelled dynamic factors. Electronics, 11(7), 999.
Abro, G. E. M., Zulkifli, S. A. B. M., Asirvadam, V. S., & Ali, Z. A. (2021). Model-free-based single-dimension fuzzy SMC design for underactuated quadrotor UAV. Actuators, 10(8), 191.
Mustafa Abro, G. E., Ali, Z. A., Zulkifli, S. A., & Asirvadam, V. S. (2021). Performance evaluation of different control methods for an underactuated quadrotor unmanned aerial vehicle (QUAV) with position estimator and disturbance observer. Mathematical Problems in Engineering, 2021, 1–22.
Abro, G. E., Zulkifli, S. A., & Asirvadam, V. S. (2021). ’Performance evaluation of Newton Euler & quaternion mathematics-based dynamic models for an underactuated quadrotor UAV.’ In 2021 11th IEEE International Conference on Control System, Computing and Engineering (ICCSCE), IEEE, pp. 142-147.
Saini, P., & Thakur, P. (2022). H-infinity based robust temperature controller design for a non-linear systems. Wireless Personal Communications, 126(1), 305–333.
Sikander, A., Dheeraj, Ajay, Chatterjee, A., & Ahamad, N. (2022). Control design approach for improved voltage stability in microgrid energy storage system. Microsystem Technologies, 28(12), 2821–2828.
Samir, M., Singh, G., & Ahamad, Nafees. (2022). Tilt integral derivative controller optimized by battle royale optimization for wind generator connected to grid. Indonesian Journal of Electrical Engineering and Informatics (IJEEI), 10(2), 302–316.
Chhetri, A., Ahamad, N., & Saklani, M., (2024). ’Review on controlling of BLDC motor via optimization techniques for renewable energy applications’, In Sustainable Energy Solutions with Artificial Intelligence, Blockchain Technology, and Internet of Things, CRC Press, pp. 129-143.
Ahamad, N., Singh, G., Khan, S., & Sikander, A. (2017). ’Design and performance analysis of optimal reduced order H-infinity controller: L1 norm based genetic algorithm technique’, In 2017 International Conference on Power and Embedded Drive Control (ICPEDC), IEEE, pp. 8-13 .
Uniyal, S., & Sikander, Afzal. (2018). A novel design technique for brushless DC motor in wireless medical applications. Wireless Personal Communications, 102, 369–381.
Funding
The authors have not disclosed any funding.
Author information
Authors and Affiliations
Contributions
The authors confirm contribution to the paper as follows: Nafees Ahamad: Conceptualization, formal analysis, investigation, methodology, software, validation, visualization, writing—original draft. Afzal Sikander: Investigation, methodology, resources, software, supervision, validation, visualization, writing—original draft, writing—review and editing. Pankaj Kumar: Methodology, resources, software, visualization, writing—review and editing
Corresponding author
Ethics declarations
Conflict of interest
The authors have not disclosed any Conflict of interest.
Ethical Approval
Not Required.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Ahamad, N., Sikander, A. & Jha, P.K. A New Optimal Control Design Framework and Stabilization of a Gimbal Payload System Using Meta-heuristic Algorithm. Wireless Pers Commun 135, 899–917 (2024). https://doi.org/10.1007/s11277-024-11083-6
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11277-024-11083-6