Skip to main content
Erschienen in: Cluster Computing 4/2019

16.02.2018

Low-level control technology of micro autonomous underwater vehicle based on intelligent computing

verfasst von: Lanyong Zhang, Lei Zhang, Sheng Liu, Jiajia Zhou, Christos Papavassiliou

Erschienen in: Cluster Computing | Sonderheft 4/2019

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

Based on the modeling of a micro autonomous underwater vehicle, an improved control structure and underlying control method are proposed for some parameters such as the automatic orientation, automatic depth, height, and speed of the micro autonomous underwater vehicle. A cascade double closed-loop control structure is proposed to control the horizontal plane by controlling properties such as the automatic depth, height, positioning, the response speed and adjustment precision of the control are improved. The parameters of the proportional-integral-derivative (PID) control method can be optimized by using particle swarm optimization (PSO), and the fuzzy controller is designed to compare with the PID control of the autonomous underwater vehicles. Compared with the traditional PID control, the control effect of PSO–PID controller is stronger than that of the tranditional PID controller. Due to the uncertainty of the micro autonomous underwater vehicle mathematical model, the position control of PID controller is weaker than the fuzzy controller. The simulation results show that the proposed method has fast dynamic response and acceptable robustness.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literatur
1.
Zurück zum Zitat Allotta, B., Costanzi, R., Fanelli, F., Monni, N., Ridolfi, A.: Single axis fog aided attitude estimation algorithm for mobile robots. Mechatronics 30, 158–173 (2015)CrossRef Allotta, B., Costanzi, R., Fanelli, F., Monni, N., Ridolfi, A.: Single axis fog aided attitude estimation algorithm for mobile robots. Mechatronics 30, 158–173 (2015)CrossRef
2.
Zurück zum Zitat Cheng, R., Jin, Y.: A social learning particle swarm optimization algorithm for scalable optimization. Inf. Sci. 291(6), 43–60 (2015)MathSciNetCrossRef Cheng, R., Jin, Y.: A social learning particle swarm optimization algorithm for scalable optimization. Inf. Sci. 291(6), 43–60 (2015)MathSciNetCrossRef
3.
Zurück zum Zitat Esmin, A.A.A., Coelho, R.A., Matwin, S.: A review on particle swarm optimization algorithm and its variants to clustering high-dimensional data. Artif. Intell. Rev. 44(1), 23–45 (2015)CrossRef Esmin, A.A.A., Coelho, R.A., Matwin, S.: A review on particle swarm optimization algorithm and its variants to clustering high-dimensional data. Artif. Intell. Rev. 44(1), 23–45 (2015)CrossRef
4.
Zurück zum Zitat Elmokadem, T., Zribi, M., Youcef-Toumi, K.: Terminal sliding mode control for the trajectory tracking of underactuated autonomous underwater vehicles. Ocean Eng. 129, 613–625 (2016)CrossRef Elmokadem, T., Zribi, M., Youcef-Toumi, K.: Terminal sliding mode control for the trajectory tracking of underactuated autonomous underwater vehicles. Ocean Eng. 129, 613–625 (2016)CrossRef
5.
Zurück zum Zitat Kukulya, A., Plueddemann, A., Austin, T., Stokey, R., Purcell, M., Allen, B., et al.: Under-ice operations with a REMUS-100 AUV in the Arctic. Autonomous Underwater Vehicles 12, 1–8 (2010) Kukulya, A., Plueddemann, A., Austin, T., Stokey, R., Purcell, M., Allen, B., et al.: Under-ice operations with a REMUS-100 AUV in the Arctic. Autonomous Underwater Vehicles 12, 1–8 (2010)
6.
Zurück zum Zitat Khan, S.U., Yang, S., Wang, L., Liu, L.: A modified particle swarm optimization algorithm for global optimizations of inverse problems. IEEE Trans. Magn. 52(3), 1–4 (2016)CrossRef Khan, S.U., Yang, S., Wang, L., Liu, L.: A modified particle swarm optimization algorithm for global optimizations of inverse problems. IEEE Trans. Magn. 52(3), 1–4 (2016)CrossRef
7.
Zurück zum Zitat Liesk, T., Nahon, M., Boulet, B.: Design and experimental validation of a nonlinear low-level controller for an unmanned fin-less airship. IEEE Trans. Control Syst. Technol. 21(1), 149–161 (2013)CrossRef Liesk, T., Nahon, M., Boulet, B.: Design and experimental validation of a nonlinear low-level controller for an unmanned fin-less airship. IEEE Trans. Control Syst. Technol. 21(1), 149–161 (2013)CrossRef
8.
Zurück zum Zitat Liu, Y.J., Tong, S., Chen, C.L.P.: Adaptive fuzzy control via observer design for uncertain nonlinear systems with unmodeled dynamics. IEEE Trans. Fuzzy Syst. 21(2), 275–288 (2013)CrossRef Liu, Y.J., Tong, S., Chen, C.L.P.: Adaptive fuzzy control via observer design for uncertain nonlinear systems with unmodeled dynamics. IEEE Trans. Fuzzy Syst. 21(2), 275–288 (2013)CrossRef
9.
Zurück zum Zitat Lu, Y., Yan, D., Levy, D.: Parameter estimation of vertical takeoff and landing aircrafts by using a PID controlling particle swarm optimization algorithm. Appl. Intell. 44(4), 793–815 (2016)CrossRef Lu, Y., Yan, D., Levy, D.: Parameter estimation of vertical takeoff and landing aircrafts by using a PID controlling particle swarm optimization algorithm. Appl. Intell. 44(4), 793–815 (2016)CrossRef
10.
Zurück zum Zitat Marinaki, M., Marinakis, Y., Stavroulakis, G.E.: Fuzzy control optimized by a multi-objective differential evolution algorithm for vibration suppression of smart structures. Comput. Struct. 147, 126–137 (2015)CrossRef Marinaki, M., Marinakis, Y., Stavroulakis, G.E.: Fuzzy control optimized by a multi-objective differential evolution algorithm for vibration suppression of smart structures. Comput. Struct. 147, 126–137 (2015)CrossRef
11.
Zurück zum Zitat Rout, R., Subudhi, B.: Inverse optimal self-tuning pid control design for an autonomous underwater vehicle. Int. J. Syst. Sci. 48(2), 367–375 (2016)MathSciNetCrossRef Rout, R., Subudhi, B.: Inverse optimal self-tuning pid control design for an autonomous underwater vehicle. Int. J. Syst. Sci. 48(2), 367–375 (2016)MathSciNetCrossRef
12.
Zurück zum Zitat Smith, S.M., Rae, G.J.S., Anderson, D.T.: Applications of fuzzy logic to the control of an autonomous underwater vehicle. In: IEEE International Conference on Fuzzy Systems, vol. 2, pp. 1099–1106 (1993) Smith, S.M., Rae, G.J.S., Anderson, D.T.: Applications of fuzzy logic to the control of an autonomous underwater vehicle. In: IEEE International Conference on Fuzzy Systems, vol. 2, pp. 1099–1106 (1993)
13.
Zurück zum Zitat Sun, J., Wu, X., Palade, V., Fang, W., Shi, Y.: Random drift particle swarm optimization algorithm: convergence analysis and parameter selection. Mach. Learn. 101(1), 345–376 (2015)MathSciNetCrossRef Sun, J., Wu, X., Palade, V., Fang, W., Shi, Y.: Random drift particle swarm optimization algorithm: convergence analysis and parameter selection. Mach. Learn. 101(1), 345–376 (2015)MathSciNetCrossRef
14.
Zurück zum Zitat Tanakitkorn, K., Wilson, P.A., Turnock, S.R., Phillips, A.B.: Depth control for an over-actuated, hover-capable autonomous underwater vehicle with experimental verification. Mechatronics 41, 67–81 (2017)CrossRef Tanakitkorn, K., Wilson, P.A., Turnock, S.R., Phillips, A.B.: Depth control for an over-actuated, hover-capable autonomous underwater vehicle with experimental verification. Mechatronics 41, 67–81 (2017)CrossRef
15.
Zurück zum Zitat Wang, H., Chen, B., Liu, X., Liu, K., Lin, C.: Robust adaptive fuzzy tracking control for pure-feedback stochastic nonlinear systems with input constraints. IEEE Trans. Cybern. 43(6), 2093–2104 (2013)CrossRef Wang, H., Chen, B., Liu, X., Liu, K., Lin, C.: Robust adaptive fuzzy tracking control for pure-feedback stochastic nonlinear systems with input constraints. IEEE Trans. Cybern. 43(6), 2093–2104 (2013)CrossRef
16.
Zurück zum Zitat Liu, Y., Yang, Z., Ning, T., Wu, H.: Efficient quality-of-service (QoS) support in mobile opportunistic networks. IEEE Trans. Veh. Technol. 63(9), 4574–4584 (2014)CrossRef Liu, Y., Yang, Z., Ning, T., Wu, H.: Efficient quality-of-service (QoS) support in mobile opportunistic networks. IEEE Trans. Veh. Technol. 63(9), 4574–4584 (2014)CrossRef
17.
Zurück zum Zitat Yang, L.: Multi-copy data dissemination with probabilistic delay constraint in mobile opportunistic device-to-device networks. In: Proceedings of the IEEE 17th International Symposium on World of Wireless, Mobile and Multimedia networks (WoWMoM), pp. 1–9 (2016) Yang, L.: Multi-copy data dissemination with probabilistic delay constraint in mobile opportunistic device-to-device networks. In: Proceedings of the IEEE 17th International Symposium on World of Wireless, Mobile and Multimedia networks (WoWMoM), pp. 1–9 (2016)
Metadaten
Titel
Low-level control technology of micro autonomous underwater vehicle based on intelligent computing
verfasst von
Lanyong Zhang
Lei Zhang
Sheng Liu
Jiajia Zhou
Christos Papavassiliou
Publikationsdatum
16.02.2018
Verlag
Springer US
Erschienen in
Cluster Computing / Ausgabe Sonderheft 4/2019
Print ISSN: 1386-7857
Elektronische ISSN: 1573-7543
DOI
https://doi.org/10.1007/s10586-018-1909-5

Weitere Artikel der Sonderheft 4/2019

Cluster Computing 4/2019 Zur Ausgabe