The fuzzy particle swarm optimization algorithm design for dynamic positioning system under unexpected impacts

Abstract

The vessel motion is a nonlinear and complicated in practical applications. The factors which affect vessel motion, mainly come from environmental influences. In this paper, we develop a fuzzy particle swarm optimization algorithm that applies to dynamic positioning system for stabilizing a vessel motion under unexpected impacts. The structure parameter of fuzzy system is calibrated by particle swarm optimization method. The coverage domain width and the overlap degree influence of membership function are adjusted dynamically from system errors. Thereby optimizing the control signal and enhancing the dynamic positioning system quality. Simulation studies with comparisons on a supply vessel are carried out. The proposed in a better response compared to other method such as fuzzy that proved effective of the proposed controller.

An improved control rod selection algorithm for core power control at TRIGA PUSPATI Reactor

“…In order to obtain the reactivity value, the step input shown in Figure 12 is assumed to be the control rod velocity determined by the controller to control the reactivity insertion rate in the reactor core which is Multiple-Inputs-Single-Output (MISO) system [44]. The conventional CRSA and SCAR algorithm will translate the control rod velocity to control rod height parameter (control rod distance travel movement) and assigned as the first input in rod worth curve block.…”

Robust Adaptive Fuzzy Control Using Genetic Algorithm for Dynamic Positioning System

“…Amongst the evolutionary algorithms, the revolution in the study of natural algorithms applied in theory control is still in the process of intense racing by researchers. The most common algorithms that can be named Genetic Algorithm (GA) [32], Ant Colony Optimized (ACO) [33], Artificial Bee Colony Algorithm (ABCA) [34], and Particle Swarm Optimization (PSO) [35], among them GA is one of the most widely used algorithm for estimating fuzzy weights and obtaining good shape of the membership function, that is the way to make adaptive fuzzy control systems increasing quality and performance of control process. Adaptive Fuzzy Control based on GA, structure provides a feasible approach for DP nonlinear systems with unexpected impacts due to the fuzzy's ability to approximate a nonlinear function.…”

Particle Swarm Optimization of a Passivity-Based Controller for Dynamic Positioning of Ships

“…Fuzzy-logic and neural network algorithm methods have the ability to reduce the complex nonlinear characteristics of the DP system controller (by means of approximation of nonlinear function) without heavy/tedious online computation requirements [20,21]. This enables online estimation with time-saving in case of dynamics variations of the DP systems due to ex.…”

“…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]. In the literature, various optimization algorithms have been developed to improve the quality of the closed-loop system such as Artificial Bee Colony (ABC) algorithm [29], Ant Colony Optimization (ACO) algorithm [30], Bacterial Foraging Optimization (BFO) algorithm [31], Multi-Verse Optimization (MVO) algorithm [32] and Gravitational Search Algorithm (GSA) [33].…”

“…Particle Swarm Optimization (PSO) is one of the effective optimization methods that has been successfully used in tuning PID controllers as in [34], for quadrotor stabilization based on integral backstepping control design [35], for tuning the parameters of fuzzy PD controller with minimization of integral square error cost function in [36], to improve the performance of an ultrasonic transducer [28]. For the control of DP systems, authors in [21] have deployed the PSO method to optimize the fuzzy function/parameters to enhance the quality and performance of the DP system of the ship.…”