13 research outputs found
Rudder roll stabilization for ships
This paper describes the design of an autopilot for rudder roll stabilization for ships. This autopilot uses the rudder not only for course keeping but also for reduction of the roll. The system has a series of properties which make the controller design far from straightforward: the process has only one input (the rudder angle) and two outputs (the heading and the roll angle); the transfer from rudder to roll is non-minimum-phase; because large and high-frequency rudder motions are necessary, the non-linearities of the steering machine cannot be disregarded; the disturbances caused by the waves vary considerably in amplitude and frequency spectrum.\ud
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In order to solve these problems a new approach to the LQG method has been developed. The control algorithms were tested by means of computer simulations, scale-model experiments and full-scale trials at sea. The results indicate that a rudder roll stabilization system is able to reduce the roll as well as a conventional fin stabilization system, while it requires less investments. Based on the results obtained in this project the Royal Netherlands Navy has decided to implement rudder roll stabilization on a series of ships under construction at this moment
A MRAS-based Learning Feed-forward Controller
Inspired by learning feed–forward control structures, this paper considers the adaptation of the parameters of a model–reference based learning feed–forward controller that realizes an inverse model of the process. The actual process response is determined by a setpoint generator. For linear systems it can be proved that the controlled system is asymptotically stable in the sense of Liapunov. Compared with more standard model reference configurations this system has a superior performance. It is fast, robust and relatively insensitive for noisy measurements. Simulations with an arbitrary second–order process and with a model of a typical fourth–ordermechatronics process demonstrate this
Perancangan Sistem Stabilisasi Rudder Roll pada Kapal Perang Kelas SIGMA dengan Kontrol Logika Fuzzy
Kapal perang membutuhkan maneuverability yang baik saat beroperasi di laut. Maneuverability dipengaruhi oleh sistem kemudi kapal. Kemudi menggunakan rudder berpengaruh terhadap stabilitas rolling kapal. Stabilitas rolling adalah kemampuan kapal kembali ke keadaan normal dalam merespon gangguan. Gerakan roll yang besar dapat menurunkan performansi kapal dan efektivitas awak kapal. Rudder roll merupakan konsep rudder berfungsi mengendalikan heading hingga gerakan roll berkurang. Tujuan dari penelitian ini adalah merancang sistem stabilisasi rudder roll pada kapal perang kelas SIGMA dengan kontrol logika fuzzy. Perancangan sistem dilakukan berdasarkan spesifikasi kapal PKR KRI Diponegoro Kelas SIGMA. Perancangan dilakukan secara simulasi menggunakan Simulink Matlab dan kontrol logika fuzzy Sugeno-Takagi. Gangguan yang digunakan adalah gangguan linier gelombang laut state satu sampai tujuh. Semakin tinggi tingkatan gangguan, maka semakin lama waktu stabilitas rolling mencapai steady state. Performansi kestabilan sistem stabilisasi rudder roll telah sesuai dengan parameter kestabilan yang ada. Performansi maneuver sistem stabilisasi rudder roll memiliki jarak advanced diameter dan tactical diameter yang sama yaitu sebesar 2.48 Lpp dan telah sesuai dengan standar IMO (International Maritime Organization).
Optimal Universal Controllers for Roll Stabilization
Roll stabilization is an important problem of ship motion control. This
problem becomes especially difficult if the same set of actuators (e.g. a
single rudder) has to be used for roll stabilization and heading control of the
vessel, so that the roll stabilizing system interferes with the ship autopilot.
Finding the "trade-off" between the concurrent goals of accurate vessel
steering and roll stabilization usually reduces to an optimization problem,
which has to be solved in presence of an unknown wave disturbance. Standard
approaches to this problem (loop-shaping, LQG, -control etc.)
require to know the spectral density of the disturbance, considered to be a
\colored noise". In this paper, we propose a novel approach to optimal roll
stabilization, approximating the disturbance by a polyharmonic signal with
known frequencies yet uncertain amplitudes and phase shifts. Linear quadratic
optimization problems in presence of polyharmonic disturbances can be solved by
means of the theory of universal controllers developed by V.A. Yakubovich. An
optimal universal controller delivers the optimal solution for any uncertain
amplitudes and phases. Using Marine Systems Simulator (MSS) Toolbox that
provides a realistic vessel's model, we compare our design method with
classical approaches to optimal roll stabilization. Among three controllers
providing the same quality of yaw steering, OUC stabilizes the roll motion most
efficiently
Simulation studies relating to rudder roll stabilization of a container ship using neural networks
RRS (Rudder Roll Stabilization) of Ships is a difficult problem because of its associated non-linear dynamics, coupling effects and complex control requirements. This paper proposes a solution of this stabilization problem that is based on an ANN (Artificial Neural Network) controller. The controller has been trained using supervised learning. The simulation studies have been carried out using MATLAB and a non-linear model of a container ship. It has been demonstrated that the proposed controller regulates heading and also controls roll angle very successfully
Simulation Studies Relating to Rudder Roll Stabilization of a Container Ship Using Neural Networks
International audienceRRS (Rudder Roll Stabilization) of Ships is a difficult problem because of its associated non-linear dynamics, coupling effects and complex control requirements. This paper proposes a solution of this stabilization problem that is based on an ANN (Artificial Neural Network) controller. The controller has been trained using supervised learning. The simulation studies have been carried out using MATLAB and a non-linear model of a container ship. It has been demonstrated that the proposed controller regulates heading and also controls roll angle very successfully
Simulation Studies Relating to Rudder Roll Stabilization of a Container Ship Using Neural Networks
RRS (Rudder Roll Stabilization) of Ships is a difficult problem because of its associated non-linear dynamics, coupling effects and complex control requirements. This paper proposes a solution of this stabilization problem that is based on an ANN (Artificial Neural Network) controller. The controller has been trained using supervised learning. The simulation studies have been carried out using MATLAB and a non-linear model of a container ship. It has been demonstrated that the proposed controller regulates heading and also controls roll angle very successfully
Active-Varying Sampling-Based Fault Detection Filter Design for Networked Control Systems
This paper is concerned with fault detection filter design for continuous-time networked control systems considering packet dropouts and network-induced delays. The active-varying sampling period method is introduced to establish a new discretized model for the considered networked control systems. The mutually exclusive distribution characteristic of packet dropouts and network-induced delays is made full use of to derive less conservative fault detection filter design criteria. Compared with the fault detection filter design adopting a constant sampling period, the proposed active-varying sampling-based fault detection filter design can improve the sensitivity of the residual signal to faults and shorten the needed time for fault detection. The simulation results illustrate the merits and effectiveness of the proposed fault detection filter design
Autonomous sea craft for search and rescue operations : marine vehicle modelling and analysis.
Thesis (M.Sc.Eng.)-University of KwaZulu-Natal, Durban, 2011.Marine search and rescue activities have been plagued with the problem of risking the lives of rescuers in
rescue operations. With increasing developments in sensor technologies, it became a necessity in the
marine search and rescue community to develop an autonomous marine craft to assist in rescue
operations. Autonomy of marine craft requires a robust localization technique and process. To apply
robust localization to marine craft, GPS technology was used to determine the position of the marine craft
at any given point in time. Given that the operational environment of the marine was at open air, river, sea
etc. GPS signal was always available to the marine craft as there are no obstructions to GPS signal.
Adequate cognizance of the current position and states of an unmanned marine craft was a critical
requirement for navigation of an unmanned surface vehicle (USV). The unmanned surface vehicle uses
GPS in conjunction with state estimated solution provided by inertial sensors. In the absence of the GPS
signal, navigation is resumed with a digital compass and inertial sensors to such a time when the GPS
signal becomes accessible.
GPS based navigation can be used for an unmanned marine craft with the mathematical modelling of the
craft meeting the functional requirements of an unmanned marine craft. A low cost GPS unit was used in
conjunction with a low cost inertial measurement unit (IMU) with sonar for obstacle detection. The use of
sonar in navigation algorithm of marine craft was aimed at surveillance of the operational environment of
the marine craft to detect obstacles on its path of motion. Inertial sensors were used to determine the
attitude of the marine craft in motion