nach oben

Neural Computing and Applications

Erschienen in:

01.11.2015 | Original Article

A bioinspired neural dynamics-based approach to tracking control of autonomous surface vehicles subject to unknown ocean currents

verfasst von: Changzhong Pan, Xuzhi Lai, Simon X. Yang, Min Wu

Erschienen in: Neural Computing and Applications | Ausgabe 8/2015

Einloggen

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

search-config

KI-gestützte Suche

Aus

Abstract

This paper addresses the trajectory tracking control problem of an autonomous surface vehicle (ASV) subject to unknown ocean currents, where smooth and continuous velocity commands are desirable for safe and effective operation. A novel bioinspired approach is proposed by integrating three neural dynamics models into the conventional Lyapunov synthesis. The tracking controller is derived from the error dynamics analysis of the ASV and the stability analysis of the control system. A simple observer is proposed to estimate the unknown ocean currents, which only requires the position of the ASV. The overall control system under the controller and observer is rigorously proved to be asymptotically stable by a Lyapunov stability theory for cascaded systems. The most contribution is that the proposed tracking controller is capable of eliminating the sharp velocity jumps due to sudden tracking error changes and generating smooth and continuous control signals. In addition, it can deals with the situation with unknown ocean currents. The effectiveness and efficiency of the proposed approach are demonstrated through simulation and comparison studies.

Vorheriger Artikel Designing evolutionary feedforward neural networks using social spider optimization algorithm

Nächster Artikel Topological Q-learning with internally guided exploration for mobile robot navigation

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

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!

Jetzt informieren

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!

Jetzt informieren

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!

Jetzt informieren

Fossen TI (1994) Guidance and control of ocean vehicles. Wiley, Chichester

Manley JE (2008) Unmanned surface vehicles, 15 years of development. In: Proceedings of oceans 2008. Quebec City pp 1–4

Ashrafiuon H, Muske KR, McNinch LC, Soltan RA (2008) Sliding-mode tracking control of surface vessels. IEEE Trans Ind Electron 55(11):4004–4012CrossRef

Lin CM, Chen CH (2006) Adaptive RCMAC sliding mode control for uncertain nonlinear systems. Neural Comput Appl 15(3–4):253–267CrossRef

McNinch LC, Ashrafiuon H (2011) Predictive and sliding mode cascade control for unmanned surface vessels. In: Proceedings of 2011 American Control Conference, San Francisco, USA, pp 184–189

Sira-Ramirez H (2002) Dynamic second-order sliding mode control of the hovercraft vessel. IEEE Trans Control Syst Technol 10(6):860–865CrossRef

Ghommam J, Mnif F, Derbel N (2010) Global stabilisation and tracking control of underactuated surface vessels. IET Control Theory Appl 4(1):71–88MathSciNetCrossRef

Pettersen KY, Nijmeijer H (1999) Global practical stabilization and tracking for an underactuated ship—a combined averaging and backstepping approach. Model Identif Control 20(4):189–199CrossRef

Zhang G, Yu L, Meng X, Zhang L (2011) Tracking control of underactuated ship based on partial state feedback scheme. In: Proceedings of 2011 IEEE/ICME international conference on complex medical engineering, Harbin pp 678–683

10.

Jagannathan S, Galan G (2003) One-layer neural-network controller with preprocessed inputs for autonomous underwater vehicles. IEEE Trans Veh Technol 52(5):1342–1355CrossRef

11.

Sutton R, Craven PJ (1998) The ANFIS approach applied to AUV autopilot design. Neural Comput Appl 7(2):131–140MATHCrossRef

12.

Zhang LJ, Jia HM, Qi X (2011b) NNFFC-adaptive output feedback trajectory tracking control for a surface ship at high speed. Ocean Eng 38:1430–1438CrossRef

13.

Lin CM, Tai CF, Chung CC (2014) Intelligent control system design for UAV using a recurrent wavelet neural network. Neural Comput Appl. doi:10.1007/s00521-012-1242-5

14.

Chen M, Ge SS, Cui R (2010) Adaptive NN tracking control overactuated ocean surface vessels. In: Proceedings of the 8th world congress on intelligent control and automation. Jinan pp 548–553

15.

Guerrero-González A, Garcia-Córdova F, Gilabert J (2011) A biologically inspired neural network for navigation with obstacle avoidance in autonomous underwater and surface vehicles. In: Proceedings of 2011 IEEE-Spain Oceans. Santander

16.

Bi FY, Wei YJ, Zhang JZ, Cao W (2010) Position-tracking control of underactuated autonomous underwater vehicles in the presence of unknown ocean currents. IET Control Theory Appl 11(11):2369–2380MathSciNetCrossRef

17.

Haghi P, Naraghi M, Vanini SAS (2007) Adaptive position and attitude tracking of an auv in the presence of ocean currents disturbances. In: Proceedings of 16th IEEE international conference on control applications, Singapore, pp 741–746

18.

Zhu D, Huang H, Yang SX (2013) Dynamic task assignment and path planning of multi-AUV system based on an improved self-organizing map and velocity synthesis method in three-dimensional underwater workspace. IEEE Trans Cybern 43(2):504–514CrossRef

19.

Yang Y, Du J, Guo C, Li G (2011) Trajectory tracking control of nonlinear full actuated ship with disturbances. In: Proceedings of 2011 International conference on soft computing and pattern recognition. Dalian, pp 318–323

20.

Tee KP, Ge SS (2006) Control of fully actuated ocean surface vessels using a class of feedforward approximators. IEEE Trans Control Syst Technol 14(4):750–756CrossRef

21.

Ghommam J, Mnif F, Benali A, Poisson G (2007) Observer design for euler lagrange systems: application to path following control of an underactuated surface vessel. In: Proceedings of IEEE/RSJ international conference on intelligent robots and systems. San Diego, pp 2883–2888

22.

Radke A, Gao Z (2006) A survey of state and disturbance observers for practitioners. In: Proceedings of American control conference. Minneapolis, pp 5183–5188

23.

Khalil HK (2008) High-gain observers in nonlinear feedback control. In: Proceedings of international conference on control, automation and systems, Seoul, pp xlvii-lvii

24.

Batista P, Silvestre C, Oliveira P (2009) Position and velocity navigation systems for unmanned vehicles. IEEE Trans Control Syst Technol 17(3):707–715CrossRef

25.

Jaffre FM, Austin TC, Allen BG, Stokey R, Von Alt CJ (2005) Ultra short baseline acoustic receiver/processor. In: Proceedings of ocean-Europe, pp 1382–1385

26.

Hodgkin AL, Huxley AF (1952) A quantitative description of membrane current and its application to conduction and excitation in nerve. J Physiol 117:500–554CrossRef

27.

Grossberg S (1988) Nonlinear neural networks: principles, mechanisms, and architecture. Neural Netw 1:17–61CrossRef

28.

Öğmen H, Gagné S (1990) Neural network architectures for motion perception and elementary motion detection in the fly visual system. Neural Netw 3:487–505CrossRef

29.

Willms AR, Yang SX (2008) Real-time robot path planning via a distance-propagating dynamic system with obstacle clearance. IEEE Trans Syst Man Cybern B Cybern 38(3):884–893CrossRef

30.

Yang SX, Meng MQH (2001) Neural network approaches to dynamic collision-free trajectory generation. IEEE Trans Syst Man Cybern B Cybern 31(3):302–318MathSciNetCrossRef

31.

Yang SX, Zhu A, Yuan G, Meng MH (2012) A bioinspired neurodynamics based approach to tracking control of mobile robots. IEEE Trans Ind Electron 59(8):3211–3220CrossRef

32.

Luo C, Yang SX (2008) A bioinspired neural network for real-time concurrent map building and complete coverage robot navigation in unknown environments. IEEE Trans Neural Netw 19(7):1279–1298CrossRef

33.

Yuan X, Yang SX (2007) Multi-robot-based nanoassembly planning with automated path generation. IEEE/ASME Trans Mechatron 12(3):352–356CrossRef

34.

Yang SX, Meng MQH (2001b) Neural network approaches to dynamic collision-free trajectory generation. IEEE Trans Syst Man Cybern B Cybern 31(3):302–318MathSciNetCrossRef

35.

Sun B, Zhu D, Yang SX (2014) A bioinspired filtered backstepping tracking control of 7000-m manned submarine vehicle. IEEE Trans Ind Electron 61(7):3682–3693CrossRef

36.

Panteley E, Lefeber E, Lorıa A, Nijmeijer H (1998) Exponential tracking control of a mobile car using a cascaded approach. In: Proceedings of IFAC workshop on motion control. Grenoble, pp 221–226

Titel: A bioinspired neural dynamics-based approach to tracking control of autonomous surface vehicles subject to unknown ocean currents
verfasst von: Changzhong Pan
Xuzhi Lai
Simon X. Yang
Min Wu
Publikationsdatum: 01.11.2015
Verlag: Springer London
Erschienen in: Neural Computing and Applications / Ausgabe 8/2015
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-015-1839-6

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

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

Springer Professional "Wirtschaft"

Springer Professional "Technik"

Springer Professional "Wirtschaft+Technik"

Weitere Artikel der Ausgabe 8/2015

Spiking neural network-based target tracking control for autonomous mobile robots

Fusing hierarchical multi-scale local binary patterns and virtual mirror samples to perform face recognition

Photovoltaic energy production forecast using support vector regression

Application of fuzzy cognitive maps in precision agriculture: a case study on coconut yield management of southern India’s Malabar region

A hybrid FAM–CART model and its application to medical data classification

Designing evolutionary feedforward neural networks using social spider optimization algorithm