A hybrid acoustic-RF communication framework for networked control of autonomous underwater vehicles: design and cosimulation

A hybrid acoustic-RF communication framework for networked control of autonomous underwater vehicles: design and cosimulation

Underwater control applications, especially ones using autonomous underwater vehicles (AUVs) have become very popular for industrial and military underwater exploration missions. This has led to the requirement of establishing a high data rate communication link between base stations and AUVs, while underwater systems mostly rely on acoustic communications. However, limited data rate and considerable propagation delay are the major challenges for employing acoustic communication in missions requiring high control gains. In this paper, we propose a hybrid acoustic and RF communication framework for establishing a networked control system, in which, for long distance communication and control the acoustic link is used, and in the short range, the RF link is employed. Our scenario for testing implements a docking maneuver application, where a docking station determines the positions of the AUVs via acoustic or RF communication, and different medium access schemes are used for coordinating the transmission of the nodes according to the communication mode. Considering the full dynamics of the entire system for controlling the AUVs, the real-time behavior of the underwater networked control system is evaluated realistically using our proposed integrated cosimulation environment, which includes different simulators. Our performance results indicate that under calm water conditions, our proposed hybrid system reduces the docking time by 33% compared to the acoustic-only

___

  • [1] Zhang X-M, Han Q-L, Yu X. Survey on recent advances in networked control systems. IEEE Transactions on Industrial Informatics 2016; 12 (5): 1740–52. doi: 10.1109/TII.2015.2506545
  • [2] Heidemann J, Stojanovic M, Zorzi M. Underwater sensor networks: applications, advances and challenges. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 2012; 370 (1958): 158-175. doi: 10.1098/rsta.2011.0214
  • [3] Chitre M, Potter J, Heng OS. Underwater acoustic channel characterisation for medium-range shallow water communications. In: Oceans ’04 MTS/IEEE Techno-Ocean ’04 (IEEE Cat. No.04CH37600); 2004. pp. 40-45. doi: 10.1109/OCEANS.2004.1402892
  • [4] Farooq W, Ali T, Shaf A, UMAR M, Yasin S. Atomic-shaped efficient delay and data gathering routing protocol for underwater wireless sensor networks. Turkish Journal of Electrical Engineering & Computer Sciences 2019; 27 (5): 3454–3469. doi: 10.3906/elk-1808-26
  • [5] Akyildiz IF, Pompili D, Melodia T. State-of-the-art in protocol research for underwater acoustic sensor networks. In: Proceedings of the 1st ACM international workshop on Underwater networks; 2006. pp. 7–16. doi: 10.1145/1161039.1161043
  • [6] Che X, Wells I, Dickers G, Kear P, Gong X. Re-evaluation of RF electromagnetic communication in underwater sensor networks. IEEE Communications Magazin 2010; 48 (12): 143–51. doi: 10.1109/MCOM.2010.5673085
  • [7] Qureshi U, Shaikh F, Aziz Z, Shah SMZS, Sheikh AA et al. RF path and absorption loss estimation for underwater wireless sensor networks in different water environments. Sensors 2016; 16 (6): 890. doi: 10.3390/s16060890
  • [8] Jiang S, Georgakopoulos S. Electromagnetic wave propagation into fresh water. Journal of Electromagnetic Analysis and Applications 2011; 3 (7): 261-266. doi: 10.4236/jemaa.2011.37042
  • [9] Li J, Toulgoat M, Déziel M, Yu FR, Perras S. Propagation modeling and MAC-layer performance in EM-based underwater sensor networks. In: Proceedings of the fourth ACM international symposium on Development and analysis of intelligent vehicular networks and applications; 2014. pp. 111-117. doi: 10.1145/2656346.2656359
  • [10] Campagnaro F, Signori A, Zorzi M. Wireless Remote Control for Underwater Vehicles. Journal of Marine Science and Engineering 2020; 8 (10): 736. doi: /10.3390/jmse8100736
  • [11] Campagnaro F, Guerra F, Favaro F, Calzado VS, Forero P et al. Simulation of a multimodal wireless remote control system for underwater vehicles. In: Proceedings of the 10th International Conference on Underwater Networks & Systems; 2015. p. 1–8. doi: 10.1145/2831296.2831298
  • [12] Morgado M, Oliveira P, Silvestre C. Design and experimental evaluation of an integrated USBL/INS system for AUVs. In: Robotics and Automation (ICRA), 2010 IEEE International Conference on Robotics and Automation; Anchorage, AK, USA; 2010. pp. 4264–4269. doi: 10.1109/ROBOT.2010.5509597.
  • [13] Astrom KJ, Wittenmark B. Computer-controlled systems: theory and design. NJ, USA : Prentice Hall, Courier Corporation, 2013.
  • [14] Ahn J, Syed A, Krishnamachari B, Heidemann J. Design and analysis of a propagation delay tolerant ALOHA protocol for underwater networks. Ad Hoc Networks 2011; 9 (5): 752–66. doi: 10.1016/j.adhoc.2010.09.007
  • [15] Burrowes G, Khan JY. Short-range underwater acoustic communication networks. In: Cruz N (editor). Autonomous Underwater Vehicles. InTech Open Press, 2011, p. 100–105.
  • [16] Hattab G, El-Tarhuni M, Al-Ali M, Joudeh T, Qaddoumi N. An underwater wireless sensor network with realistic radio frequency path loss model. International Journal of Distributed Sensor Networks 2013; 9 (3):508708. doi: 10.1155/2013/508708
  • [17] Manhaes MMM, Scherer SA, Douat LR, Voss M, Rauschenbach T. Use of simulation-based performance metrics on the evaluation of dynamic positioning controllers. In: IEEE OCEANS 2017; Aberdeen, Scotland; 2017. p. 1–8. doi: 10.1109/OCEANSE.2017.8084658
  • [18] Robot simulation Environment [online]. Website http://www.gazebosim.org [Accessed 01 January 2021].
  • [19] Manhães MMM, Scherer SA, Voss M, Douat LR, Rauschenbach T. UUV simulator: A Gazebo-based package for underwater intervention and multi-robot simulation. In: OCEANS 2016 MTS/IEEE; Monterey, CA, USA; 2016, pp. 1-8. doi: 10.1109/OCEANS.2016.7761080
  • [20] Fossen TI. Handbook of marine craft hydrodynamics and motion control. John Wiley & Sons, 2011.
  • [21] Robot Operating System [online]. Website http://www.ros.org [Accessed 01 January 2021].
Turkish Journal of Electrical Engineering and Computer Sciences-Cover
  • ISSN: 1300-0632
  • Yayın Aralığı: Yılda 6 Sayı
  • Yayıncı: TÜBİTAK
Sayıdaki Diğer Makaleler

Missing samples reconstruction using an efficient and robust instantaneous frequency estimation algorithm

Sadiq Ali, Nabeel Ali Khan

A novel fault detection approach based on multilinear sparse PCA: application on the semiconductor manufacturing processes

Riadh TOUMI, Yahia KOURD, Dimitri LEFEBVRE

A novel crimping technique approach for high power white good plugs

Ömer BOSTAN, Ömer Cihan KIVANÇ, Okan ÖZGÖNENEL, Şahin GÜZEL, Mert DEMİRSOY

Learning target class eigen subspace (LTC-ES) via eigen knowledge grid

Sanjay Kumar Sonbhadra, Sonali Agarwal, P. Nagabhushan

Interval observer-based supervision of nonlinear networked control systems

Afef Najjar, Messaoud Amairi, Thach Ngoc Dinh, Tarek Raissi

A hybrid acoustic-RF communication framework for networked control of autonomous underwater vehicles: design and cosimulation

Mehrullah SOOMRO, Özgur GÜRBÜZ, Saeed NOURIZADEH AZAR, Oytun ERDEMİR, Ahmet ONAT

A survey on organizational choices for microservice-based software architectures

Burak BİLGİN, Hüseyin ÜNLÜ, Onur DEMİRÖRS

BLMDP: A new bi-level Markov decision process approach to joint bidding and task-scheduling in cloud spot market

Mehdi Dehghan Takht Fooladi, Mona Naghdehforoushh, Mohammad Hossein Rezvani, Mohammad Mehdi Gilanian Sadeghi

Dual-polarized elliptic-H slot-coupled patch antenna for 5G applications

Emre A. MİRAN, Mehmet ÇİYDEM

Residential energy management system based on integration of fuzzy logic and simulated annealing

Suat BAYSAN, Ramazan Nejat TUNCAY, Ömer Cihan KIVANÇ, Salih Barış ÖZTÜRK, Bekir Tevfik AKGÜN, Semih BİLGEN