Simulation And Control Of Autonomous Underwater Vehicle (AUV) Dynamics With Bio Inspired Optimization using Fractional Order PID Controller
Keywords:
Autonomous Underwater Vehicles (AUVs), Fractional Order Proportional-Integral-Derivative (FOPID) controller, Improved Zebra optimization Algorithm (IZOA), hydrodynamic coefficients and thruster dynamics
Abstract
Autonomous Underwater Vehicles (AUVs) are pivotal in marine exploration, enabling tasks like resource utilization, surveillance, and environmental monitoring in challenging underwater environments. However, their performance is often constrained by non-linear dynamics, hydrodynamic uncertainties, and actuator limitations. This study presents an advanced control framework for AUVs by integrating a Fractional Order Proportional-Integral-Derivative (FOPID) controller with an Improved Zebra Algorithm (IZOA). The proposed IZOA enhances convergence speed and optimization precision compared to existing bio-inspired methods. The mathematical modeling of AUV dynamics, including hydrodynamic coefficients and thruster dynamics, was undertaken to develop accurate control strategies. Simulations conducted in MATLAB Simulink validated the superior performance of the IZOA-tuned FOPID controller, showcasing improved trajectory tracking, reduced overshoot, and faster settling times under varying operational scenarios. This research demonstrates the feasibility of IZOA as a robust optimization method for enhancing AUV dynamics and control, laying the foundation for its application in complex underwater missions.
References
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[37] T. I. Fossen, “Handbook of marine craft hydrodynamics and motion control,” John Willy Sons Ltd, 2011.
[2] T. K. Podder and N. Sarkar, “Fault-tolerant control of an autonomous underwater vehicle under thruster redundancy,” Rob. Auton. Syst., vol. 34, no. 1, pp. 39–52, 2001.
[3] K. Tanakitkorn, P. A. Wilson, S. R. Turnock, and A. B. Phillips, “Depth control for an over-actuated, hover-capable autonomous underwater vehicle with experimental verification,” Mechatronics, vol. 41, pp. 67–81, 2017.
[4] T. Liu, Y. Hu, H. Xu, Q. Wang, and W. Du, “A novel vectored thruster based on 3-RPS parallel manipulator for autonomous underwater vehicles,” Mech. Mach. Theory, vol. 133, pp. 646–672, 2019.
[5] B. Xin, L. Xiaohui, S. Zhaocun, and Z. Yuquan, “A vectored water jet propulsion method for autonomous underwater vehicles,” Ocean Eng., vol. 74, pp. 133–140, 2013.
[6] T. Liu, Y. Hu, H. Xu, Z. Zhang, and H. Li, “Investigation of the vectored thruster AUVs based on 3SPS-S parallel manipulator,” Appl. Ocean Res., vol. 85, pp. 151–161, 2019.
[7] R. Panish, “Dynamic control capabilities and developments of the Bluefin robotics AUV fleet,” in Proc. 16th International Symposium on Unmanned Untethered Submersible Technology, 2009.
[8] D. W. Caress et al., “High-resolution multibeam, sidescan, and subbottom surveys using the MBARI AUV D. Allan B,” Mar. habitat Mapp. Technol. Alaska, pp. 47–69, 2008.
[9] P. S. Londhe, M. Santhakumar, B. M. Patre, and L. M. Waghmare, “Task space control of an autonomous underwater vehicle manipulator system by robust single-input fuzzy logic control scheme,” IEEE J. Ocean. Eng., vol. 42, no. 1, pp. 13–28, 2016.
[10] B. M. Patre, P. S. Londhe, L. M. Waghmare, and S. Mohan, “Disturbance estimator based non-singular fast fuzzy terminal sliding mode control of an autonomous underwater vehicle,” Ocean Eng., vol. 159, pp. 372–387, 2018.
[11] P. Herman, “Decoupled PD set-point controller for underwater vehicles,” Ocean Eng., vol. 36, no. 6–7, pp. 529–534, 2009.
[12] T. I. Fossen, “Guidance and control of ocean vehicles,” Univ. Trondheim, Norway, Print. by John Wiley Sons, Chichester, England, ISBN 0 471 94113 1, Dr. Thesis, 1999.
[13] S. Miyamaoto et al., “Maneuvering control system design for autonomous underwater vehicle,” in MTS/IEEE Oceans 2001. An Ocean Odyssey. Conference Proceedings (IEEE Cat. No. 01CH37295), IEEE, 2001, pp. 482–489.
[14] P. Sarhadi, A. R. Noei, and A. Khosravi, “Model reference adaptive PID control with anti-windup compensator for an autonomous underwater vehicle,” Rob. Auton. Syst., vol. 83, pp. 87–93, 2016.
[15] A. Malerba and G. Indiveri, “Complementary control of the depth of an underwater robot,” IFAC Proc. Vol., vol. 47, no. 3, pp. 8971–8976, 2014.
[16] G. Antonelli, S. Chiaverini, N. Sarkar, and M. West, “Adaptive control of an autonomous underwater vehicle: experimental results on ODIN,” IEEE Trans. Control Syst. Technol., vol. 9, no. 5, pp. 756–765, 2001.
[17] J.-H. Li and P.-M. Lee, “Design of an adaptive nonlinear controller for depth control of an autonomous underwater vehicle,” Ocean Eng., vol. 32, no. 17–18, pp. 2165–2181, 2005.
[18] B. K. Sahu and B. Subudhi, “Adaptive tracking control of an autonomous underwater vehicle,” Int. J. Autom. Comput., vol. 11, no. 3, pp. 299–307, 2014.
[19] G. Antonelli, “On the use of adaptive/integral actions for six-degrees-of-freedom control of autonomous underwater vehicles,” IEEE J. Ocean. Eng., vol. 32, no. 2, pp. 300–312, 2007.
[20] C. Barbalata, V. De Carolis, M. W. Dunnigan, Y. R. Petillot, and D. M. Lane, “An adaptive controller for autonomous underwater vehicles.,” in IROS, 2015, pp. 1658–1663.
[21] R. Rout and B. Subudhi, “Inverse optimal self-tuning PID control design for an autonomous underwater vehicle,” Int. J. Syst. Sci., vol. 48, no. 2, pp. 367–375, 2017.
[22] H. Wang, Y., Karimi, H. R., Lam, H. K., & Yan, “Fuzzy output tracking control and filtering for nonlinear discrete-time descriptor systems under unreliable communication links.,” 2019.
[23] D. Healey, A. J., & Lienard, “Multivariable sliding mode control for autonomous diving and steering of unmanned underwater vehicle.
[24] B. Salgado-Jimenez, T., & Jouvencel, “Using a high order sliding modes for diving control a torpedo autonomous underwater vehicle. In Oceans 2003. Celebrating the Past... Teaming Toward the Future (IEEE Cat. No. 03CH37492) (Vol. 2, pp. 934-939). IEEE.,” 2003.
[25] S. Liang, X., Wan, L., Blake, J. I., “Path following of an underactuated AUV based on fuzzy backstepping sliding mode control. International Journal of Advanced Robotic Systems, 13(3), 122.,” 2016.
[26] N. F. Zain, Z. M., & Harun, “Backstepping control strategy for an underactuated x4-auv. Jurnal Teknologi, 74(9).,” 2015.
[27] A. L. V. Steenson, A. B. Phillips, E. Rogers, M. E. Furlong and S. R, “Turnock, ‘Experimental verification of a depth controller using model predictive control with constraints onboard a thruster actuated auv,’ IFAC Proceedings Volumes,” no. vol. 45, 5, pp. 275–280, 2012., 2012.
[28] B. Shen, C., Shi, Y., & Buckham, “Model predictive control for an AUV with dynamic path planning. In 2015 54th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE) (pp. 475-480). IEEE.,” 2015.
[29] N. Liu, Y. C., Liu, S. Y., & Wang, “Fully-tuned fuzzy neural network based robust adaptive tracking control of unmanned underwater vehicle with thruster dynamics. Neurocomputing, 196, 1-13.,” 2016.
[30] and D. P. V. De Ven, C. Flanagan, “‘Neural network control of underwater vehicles,’ Engineering Applications of Artificial Intelligence,” no. vol. 18, 5, pp. 533–547, 2005., 2005.
[31] K. Shojaei, “‘Neural network formation control of under_actuated autonomous underwater vehicles with saturating actuators,’ Neurocomputing,” vol. 194, 2016.
[32] and Y. L. F. Wang, Y. Xu, L. Wan, “‘Real-time control of autonomous underwater vehicles based on fuzzy neural network,’ in Proceedings of the 2009 International Workshop on Intelligent Systems and Applications, IEEE, pp. 1–5, Wuhan, China, May 2009,” 2009.
[33] et al. Zhang, Jialei, “‘Approach-angle-based three-dimensional indirect adaptive fuzzy path following of under-actuated AUV with input saturation.’ Applied Ocean Research 107 (2021): 102486.,” 2021.
[34] K. Shojaei, “‘(ree-dimensional neural network tracking control of a moving target by underactuated autonomous underwater vehicles,’ Neural Computing and Applications,” vol. 31, n, 2019.
[35] and C. K. A. Z. Zhong, Y. Zhu, “‘Reachable set estimation for takagi-sugeno fuzzy systems against unknown output delays with application to tracking control of auvs,’ ISA Transactions,” vol. 78, p, 2018.
[36] G. Che and Z. Yu, “‘Neural-network estimators based fault_tolerant tracking control for auv via adp with rudders faults and ocean current disturbance,’ Neurocomputing, vol. 411, pp. 442–454, 2020.,” 2020.
[36] O. Elhaki and K. Shojaei, “‘A robust neural network ap_proximation-based prescribed performance output-feedback controller for autonomous underwater vehicles with actuators saturation,’ Engineering Applications of Artificial Intelligence,” vol. 88, p, 2020.
[37] T. I. Fossen, “Handbook of marine craft hydrodynamics and motion control,” John Willy Sons Ltd, 2011.
Published
2025-02-16
How to Cite
Shiva Bhatnagar, & Sachin Puntambekar. (2025). Simulation And Control Of Autonomous Underwater Vehicle (AUV) Dynamics With Bio Inspired Optimization using Fractional Order PID Controller. Revista Electronica De Veterinaria, 25(1), 3694-3709. https://doi.org/10.69980/redvet.v25i1.1689
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