H∞ robust control design for dynamic ship positioning

Katebi, M.R.; Grimble, M.J.; Zhang, Y.

doi:10.1049/ip-cta:19971030

Cited by 84 publications

(38 citation statements)

References 6 publications

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“…Conventional control strategies like PID control can no longer satisfy the requirement of navigation, guidance and control of ships. During recent decades, many advanced control schemes have been developed and successfully applied to ship motion control, including sliding mode variable structure control [2,3]; parameter adaptive control [4,5]; H-infinity robust control [6,7]; neural-network control [8,9]; fuzzy control [10,11]; neuro-fuzzy control [12,13]; line-of-sight based model control [14,15], etc.…”

Section: Introductionmentioning

confidence: 99%

Control for Ship Course-Keeping Using Optimized Support Vector Machines

Luo

Cong

2016

Algorithms

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Support vector machines (SVM) are proposed in order to obtain a robust controller for ship course-keeping. A cascaded system is constructed by combining the dynamics of the rudder actuator with the dynamics of ship motion. Modeling errors and disturbances are taken into account in the plant. A controller with a simple structure is produced by applying an SVM and L2-gain design. The SVM is used to identify the complicated nonlinear functions and the modeling errors in the plant. The Lagrangian factors in the SVM are obtained using on-line tuning algorithms. L2-gain design is applied to suppress the disturbances. To obtain the optimal parameters in the SVM, then particle swarm optimization (PSO) method is incorporated. The stability and robustness of the close-loop system are confirmed by Lyapunov stability analysis. Numerical simulation is performed to demonstrate the validity of the proposed hybrid controller and its superior performance over a conventional PD controller.

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Section: Introductionmentioning

confidence: 99%

Control for Ship Course-Keeping Using Optimized Support Vector Machines

Luo

Cong

2016

Algorithms

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“…Some of the other implementations of RANS code can be found in [25,26,27]. There are many research papers reported in the area of the underactuated controller design for the USVs that utilize 3 DOF simplified models which neglect the rolling, pitching, and heaving motions [28,29,30,31,32,33]. Strip theory is mainly used for slowly moving slender geometries [34,35,36].…”

Section: Fluid-rigid Body Interaction Simulationmentioning

confidence: 99%

GPU based generation of state transition models using simulations for unmanned surface vehicle trajectory planning

Thakur

Švec

Gupta

2012

Robotics and Autonomous Systems

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This paper describes GPU based algorithms to compute state transition model for unmanned surface vehicles (USVs) using 6 degree of freedom (DOF) dynamics simulations of vehicle-wave interaction. State transition model is a key component of Markov Decision Process (MDP), which is a natural framework to formulate the problem of trajectory planning under motion uncertainty. USV trajectory planning problem is characterized by the presence of large and somewhat stochastic forces due to ocean waves, which can cause significant deviations in their motion. Feedback controllers are often employed to reject disturbances and get back on the desired trajectory. However, the motion uncertainty can be significant and must be considered in the trajectory planning to avoid collisions with the surrounding obstacles. In case of USV missions, state transition probabilities need to be generated on-board, to compute trajectory plans that can handle dynamically changing USV parameters and environment (e.g., changing boat inertia tensor due to fuel consumption, variations in damping due to changes in water density, variations in sea-state, etc.). The 6 DOF dynamics simulations reported in this paper are based on potential flow theory. We also present a model simplification algorithm based on temporal coherence and its GPU implementation to accelerate simulation computation performance. Using the techniques discussed in this paper we were able to compute state transition probabilities in less than 10 minutes. Computed transition probabilities are subsequently used in a stochastic dynamic programming based approach to solve the MDP to obtain trajectory plan. Using this approach, we are able to generate dynamically feasible trajectories for USVs that exhibit safe behaviors in high sea-states in the vicinity of static obstacles.

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“…Substantial roll reduction may be achieved providing an increase in the speed of the rudder, which is too expensive; however, the use of the rudder to assist fin stabilisers can further improve roll reduction. The control design using a 2 H / ∞ H approach for ship models can be found in Katebi, et al (1997) and Roberts et al (1997), and by using various controllers as has been shown in Van Amerongen, (1991) and Perez (2003).…”

Section: Introductionmentioning

confidence: 99%

“…To stabilize the roll of a ship system, various control algorithms have been proposed such as PID (Minorsky, 1947), optimal control (Fossen, 1995b) and 2 H / ∞ H (Katebi, et al, 1997).…”

Section: Introductionmentioning

confidence: 99%

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Sliding Mode and Pid Controllers for Ship Roll Stabilisation: A Comparative Simulation Study

Koshkouei

Law

Burnham

2005

IFAC Proceedings Volumes

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This paper addresses the sliding mode control design for roll reduction of a ship. The sliding mode control (SMC) technique yields the appropriate control with significant roll reduction compared with other controllers such as PID. The system comprises of three different controllers, roll-fin, roll-rudder and autopilot. Therefore, for each situation along the ship trajectory, the triple controllers should be designed. It is not necessary to have the same controller structure for all three subsystems. This paper compares SMC controllers individually with PID controllers for each subsystem, and demonstrates the results of the implementation of controllers with different structures when applied to the entire system.

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H∞ robust control design for dynamic ship positioning

Cited by 84 publications

References 6 publications

Control for Ship Course-Keeping Using Optimized Support Vector Machines

Control for Ship Course-Keeping Using Optimized Support Vector Machines

GPU based generation of state transition models using simulations for unmanned surface vehicle trajectory planning

Sliding Mode and Pid Controllers for Ship Roll Stabilisation: A Comparative Simulation Study

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