Conceptual Basis of Adaptive Autopilots
Keywords:Adaptive ship motion control, Adaptive gyropilot, Ship model parameters identification
Background. The paper is devoted to critical analysis of literature that covers the major aspects of adaptive ship motion control systems.
Objective. The objective of a study is identifying the promising areas of research in the field of adaptive ship motion control.
Methods. The analysis of existing approaches to ship model parameters identification (including identification during zig-zag motion, during circulation and identification using Kalman filtering) is done; advantages and disadvantages of those methods are determined. The methods mentioned can be used as a basis for creating adaptive gyropilots. A critical review of approaches to ship control by means of classical and modern methods of automatic control, including the parametric adjustment of classic PID regulators, switching of regulators, use of nonlinear regulators – linear-quadratic (LQ), sliding mode regulators, and artificial intelligence – neural networks, fuzzy logic and hybrid approaches, is done. Separately, in the survey analysis of papers of Ukrainian authors, which are devoted to the development of adaptive gyropilots and adaptive ship motion control, is presented.
Results. As a result of literature survey, prospective areas of studies in the field of adaptive ship control are determined.
Conclusions. Most promising research areas are:
1) development of novel approaches to the identification of the vessel model parameters and disturbances acting on it;
2) application of artificial intelligence, including fuzzy logic and neural networks, to adaptive ship control methods;3) development of adaptive nonlinear systems for ship motion control.
G.N. Roberts, “Trends in marine control systems”, Ann. Rev. Control, vol. 32, pp. 263–269, 2008.
Yu.I. Yudin et al., “Method of ship model parameters estimation”, Vestnik MGTU, vol. 12, no.1, pp. 5–9, 2009 (in Russian).
A.E. Pelevin, “Identification of maritime mobile object model parameters during periodic movement with active control”, Giroskopija i Navigatsija, no. 4 (63), pp. 29–44, 2008 (in Russian).
A.B. Phillips et al., “Evaluation of manoeuvring coefficients of a self-propelled ship using a blade element momentum propeller model coupled to a Reynolds averaged Navier Stokes flow solver”, Ocean Eng., vol. 36, pp. 1217–1225, 2009.
H.K. Yoon and K.P. Rhee, “Identification of hydrodynamic coefficients in ship maneuvering equations of motion by Estimation-Before-Modeling technique”, Ocean Eng., vol. 30, pp. 2379–2404, 2003.
M.H. Casados and R. Ferreiro, “Identification of the nonlinear ship model parameters based on the turning test trial and the backstepping procedure”, Ocean Eng., vol. 32, pp. 1350–1369, 2005.
A. Banazadeh and M.T. Ghorbani, “Frequency domain identification of the Nomoto model to facilitate Kalman filter estimation and PID heading control of a patrol vessel”, Ocean Eng., vol. 72, pp. 344–355, 2013.
G.H. Elkaim, “System identification-based control of an unmanned autonomous wind-propelled catamaran”, Control Eng. Practice, vol. 17, pp. 158– 169, 2009.
S.P. Dmitriev and A.E. Pelevin, Navigation and Control Problems during Ship Stabilization on its Trajectory. St. Petersburg, Russia: GNZ RF-CNII “Electropribor”, 2004, 160 p. (in Russian).
A.K. Sheykhot, “Improvement of control systems of marine mobile objects on the basis of identification and adaptation”, Ph.D. theses,AdmiralG.I.NevelskoyMaritimeStateUniversity,Vladivostok,Russian Federation, 2008 (in Russian).
S.V. Ivanov et al., “Identification of ship model and disturbance parameters using spectral analysis”, J. Chinese Inertial Technol., is. 3, pp. 341–346, 2013.
E.A. Poselionov, “Study and development of adaptive algorithm for control of river displacement-type ship on shallow water”, Ph.D. theses,VolgaStateMaritimeAcademy,Nizhniy Novgorod,Russian Federation, 2010 (in Russian).
H. Saari and M. Djemai, “Ship motion control using multi-controller structure”, Ocean Eng., vol. 55, pp. 184–190, 2012.
M. Tomera, “Ant colony optimization algorithm applied to ship steering control”, Procedia Computer Sci., vol. 35, pp. 83–92, 2014.
S.D. Lee et al., “Design and experiment of a small boat track-keeping autopilot”, Ocean Eng., vol. 37, pp. 208–217, 2010.
N. Mizuno et al., “Minimum time ship maneuvering method using neural network and nonlinear model predictive compensator”, Control Eng. Practice, vol. 15, pp. 757–765, 2007.
C.-Z. Pan et al., “An efficient neural network approach to tracking control of an autonomous surface vehicle with unknown dynamics”, Expert Syst. Applicat., vol. 40, pp. 1629–1635, 2013.
Z. Shen et al., “General fuzzified CMAC based reinforcement learning control for ship steering using recursive least-squares algorithm”, Neurocomputing, vol. 73, pp. 700–706, 2010.
G. Lee et al., “Algorithms to control the moving ship during harbour entry”, Appl. Math. Modelling, vol. 33, pp. 2474–2490, 2009.
W. Naeem et al., “An integrated multi-sensor data fusion algorithm and autopilot implementation in an uninhabited surface craft”, Ocean Eng., vol. 39, pp. 43–52, 2012.
G. Rigatos and S. Tzafestas, “Adaptive fuzzy control for the ship steering problem”, Mechatronics, vol. 16, pp. 479–489, 2006.
T. Cimen and S.P. Banks, “Nonlinear optimal tracking control with application to super-tankers for autopilot design”, Automatica, vol. 40, pp. 1845–1863, 2004.
M.-C. Fang and J.-H. Luo, “The nonlinear hydrodynamic model for simulating a ship steering in waves with autopilot system”, Ocean Eng., vol. 32, pp. 1486–1502, 2005.
L.P. Perera and S.C. Guedes, “Pre-filtered sliding mode control for nonlinear ship steering associated with disturbances”, Ocean Eng., vol. 51, pp. 49–62, 2012.
L.P. Perera and S.C. Guedes, “Lyapunov and Hurwitz based controls for input–output linearization applied to nonlinear vessel steering”, Ocean Eng., vol. 66, pp. 58–69, 2013.
E.R. Herrero et al., “Iterative lead compensation control of nonlinear marine vessels manoeuvring models”, Appl. Ocean Res., vol. 48, pp. 266–276, 2014.
N.E. Kahveci and P.A. Ioannou, “Adaptive steering control for uncertain ship dynamics and stability analysis”, Automatica, vol. 49, pp. 685–697, 2013.
Zhen Li et al., “Design, analysis and experimental validation of a robust nonlinear path following controller for marine surface vessels”, Automatica, vol. 45, pp. 1649–1658, 2009.
A.V. Vasilenko et al., “About two approaches to the problem of ship course control system synthesis: time optimal system vs PID regulator”, Systemy Upravlinnya, Navigatcii ta Zvyazku, is. 3 (11), pp. 80–85, 2009 (in Russian).
V.P. Garam “Relay control algorithms for marine ship gyropilot”, Systemy Upravlinnya, Navigatcii ta Zvyazku, is. 4 (12), pp. 7–10, 2009 (in Ukrainian).
V.E. Lvov and A.S. Maltsev, “Method of improvement of compensation capabilities of ship course control system”, Sudovozhdeniye, is. 15, pp. 99–104, 2008 (in Russian).
V.P. Konovalov and V.A. Savchenk, “Mathematical model of ship control”, Sudovozhdeniye, is. 15, pp. 84–90, 2008 (in Russian).
V.A. Golikov and V.E. Lvov, “Comparative simulation modeling of ships motion on predetermined course with different control principles”, Sudovozhdeniye, is. 18, pp. 68–77, 2010 (in Russian).
V.I. Bogdanov and S.A. Podporin, “Optimization of ship’s PID controller with the use of a genetic algorithm”, Optimizatsija Proizvodstvennyh Processov, is. 7, pp. 184–89, 2004 (in Russian).
V.I. Bogdanov and S.A. Podporin, “Use of a fuzzy logic in order to icrease ship course control quality”, Sbornik Nauchnukh Trudov SVMI im. P.S. Nakhimova, is. 2 (8), pp. 89–97, 2005 (in Russian).
V.I. Bogdanov and S.A. Podporin, “Adaptive gyropilot with parameter adjustment based on neural network”, Sudovozhdeniye, is. 13, pp. 13–21, 2007 (in Russian).
S.A. Podporin, “Development of methods for intellectual ship course control”, Ph.D. theses, Odesa National Maritime Academy, Odesa, 2009 (in Ukrainian).
S.A. Podporin and A.M. Oleynikov. (2007). Perspeftives of use of neuro-fuzzy and hybrid technologies in maritime control systems [Online]. Available: http://paep2007.abacus.ua/ default.aspx?id=paep_show_doc&doc=9733 (in Russian).
LicenseCopyright (c) 2017 NTUU KPI Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under CC BY 4.0 that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work