Abstract
Dynamic positioning (DP) control system is an essential module used in offshore ships for accurate maneuvering and maintaining of ship’s position and heading (fixed location or pre-determined track) by means of thruster forces being generated by controllers. In this paper, an interconnection and damping assignment-passivity based control (IDA-PBC) controller is developed for DP of surface ships. The design of the IDA-PBC controller involves a dynamic extension utilizing the coordinate transformation which adds damping to some coordinates to ensure asymptotic stability and adds integral action to enhance the robustness of the system against disturbances. The particle swarm optimization (PSO) technique is one of the the population-based optimization methods that has gained the attention of the control research communities and used to solve various engineering problems. The PSO algorithm is proposed for the optimization of the IDA-PBC controller. Numerical simulations results with comparisons illustrate the effectiveness of the new PSO-tuned dynamic IDA-PBC controller.
Highlights
Marine vessels and ships have been widely used for offshore exploration, deep-sea mining, military operations, rigs-drilling and offshore wind farm constructions [1]. For such activities to be operated under safe and stable conditions, the vessels need to be equipped with advanced motion-control systems [2]. This has led to increasing demands for dynamic positioning (DP) systems to regulate the vessels’ plane motions in order to maintain its position and heading
A dynamic interconnection and damping assignment-passivity based control (IDA-Passivity-based control (PBC)) controller has been proposed for the dynamic positioning of surface ships
The tuning of the gains of the IDA-PBC controller based on the particle swarm optimization (PSO) method has been discussed
Summary
Marine vessels and ships have been widely used for offshore exploration, deep-sea mining, military operations, rigs-drilling and offshore wind farm constructions [1]. Enhancement in control performance of the DP systems can be achieved deploying this method due to its systematic way in handling various (inputs, outputs and states) constraints [24], its model/performance optimization capabilities as well as its robustness against external disturbances and unmodeled dynamics [1,4]. Considering uncertain environmental disturbances, measurement errors and partially measured states, two robust control methods based on MPC and using a simple Luenberger observer for DP systems control problem of autonomous surface vessels have been discussed in [4]. Focusing on enhancement of the control performance, optimization techniques have been widely used and applied They provide systematic procedure for designing of controllers, tuning the parameters and gains, and online estimation/calibration for unknown parameters caused by environmental changes or disturbances [21,28].
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