A NONLINEAR UNIFIED STATE-SPACE MODEL FOR SHIP MANEUVERING AND CONTROL IN A SEAWAY

2005 ◽  
Vol 15 (09) ◽  
pp. 2717-2746 ◽  
Author(s):  
THOR I. FOSSEN
Keyword(s):  
State Space ◽  
Transfer Functions ◽  
State Space Model ◽  
Low Frequency ◽  
Ship Maneuvering ◽  
Frequency Model ◽  
Space Model ◽  
Classic Theory ◽  
Space Formulation ◽  
And Control

This article presents a unified state-space model for ship maneuvering, station-keeping, and control in a seaway. The frequency-dependent potential and viscous damping terms, which in classic theory results in a convolution integral not suited for real-time simulation, is compactly represented by using a state-space formulation. The separation of the vessel model into a low-frequency model (represented by zero-frequency added mass and damping) and a wave-frequency model (represented by motion transfer functions or RAOs), which is commonly used for simulation, is hence made superfluous.

Motion Response Control of the DWSC Spar Based on State-Space Model

2012 ◽  
Author(s):  
Xiaochuan Yu ◽  
Jeffrey Falzarano
Keyword(s):  
State Space ◽  
Transfer Functions ◽  
State Space Model ◽  
Development Program ◽  
Naval Research ◽  
Hydrodynamic Coefficients ◽  
Time Step ◽  
Response Control ◽  
Motion Response ◽  
Space Model

In 2007, the Office of Naval Research (ONR) started a technology development program called STLVAST (Small to Large Vessel At-Sea Transfer), in order to develop ‘enabling capabilities’ in the realm of logistic transfer (i.e. stores, equipment, vehicles) between a large transport vessel and a smaller T-craft ship, using a Deep Water Stable Crane (DWSC) spar between them. In this paper, the equation of motions of the single DWSC spar is initially expressed as the standard state-space model. Then the ODE solver of Matlab is directly employed to obtain the motion responses at each time step. Two levels of approximation of hydrodynamic coefficients are considered in this study. One is the Constant Coefficient Method (CCM), and the other one is the Impulse Response Function (IRF) method, with fluid memory effects considered. WAMIT software is used to calculate the hydrodynamic coefficients, including the added mass, radiation damping, IRF, the first order and second order waves loads transfer functions, etc. The motion response control is achieved by assuming the thrusters can provide the optimal feedback force derived from Linear Quadratic Regulator (LQR) method.

ASSESSING PRE-CRISIS FUNDAMENTALS IN SELECTED ASIAN STOCK MARKETS

2005 ◽  
Vol 50 (02) ◽  
pp. 175-196 ◽  
Author(s):  
EE LENG LAU ◽  
G. K. RANDOLPH TAN ◽  
SHAHIDUR RAHMAN
Keyword(s):  
Kalman Filter ◽  
Emerging Markets ◽  
State Space ◽  
Stock Prices ◽  
Stock Markets ◽  
Bubble Formation ◽  
State Space Model ◽  
Space Model ◽  
Rational Bubbles ◽  
Space Formulation

In the folklore of emerging markets, there is a popular belief that bubbles are inevitable. In this paper, our objective is to estimate a state-space model for rational bubbles in selected Asian economies with the aid of the Kalman Filter. For each economy, we derive a possible picture of the bubble formation process that is implied by the state-space formulation. The estimation is based on the rational valuation formula for stock prices. Our results provide a possible way of defining the presence of rational bubbles in the stock markets of Taiwan, Singapore, Korea, and Malaysia.

scholarly journals A state-space model and control of a full-range PMSG wind turbine for real-time simulations

2018 ◽  
Vol 100 (4) ◽  
pp. 2177-2191 ◽  
Author(s):  
Agustín Tobías-González ◽  
Rafael Peña-Gallardo ◽  
Jorge Morales-Saldaña ◽  
Aurelio Medina-Ríos ◽  
Olimpo Anaya-Lara
Keyword(s):  
Wind Turbine ◽  
State Space ◽  
Real Time ◽  
Full Range ◽  
State Space Model ◽  
Space Model ◽  
And Control ◽  
Real Time Simulations

Numerical Study on the Maneuvering of a Ship in Waves Based on Unified State Space Model

2016 ◽  
Author(s):  
Rameesha Thayale Veedu ◽  
Parameswaran Krishnankutty
Keyword(s):  
State Space ◽  
Numerical Study ◽  
State Space Model ◽  
Container Ship ◽  
Regular Waves ◽  
Ship Maneuvering ◽  
Space Model ◽  
Water Conditions ◽  
Calm Water ◽  
Early Design Stages

Ship maneuvering performance is usually predicted in calm water conditions, which provide valuable information about ship’s turning ability and its directional stability in the early design stages. Investigation of maneuvering simulation in waves is more realistic since the ship usually sails through waves. So it is important to study the effect of waves on the turning ability of a ship. This paper presents the maneuvering simulation for a container ship in presence of regular waves based on unified state space model for ship maneuvering. Standard maneuvers like turning circle and zigzag maneuver are simulated for the head sea condition and the same are compared with calm water maneuvers. The present study shows that wave significantly affects the maneuvering characteristics of the ship and hence cannot be neglected.

Modeling and Control of Biochemical Reactor

2013 ◽  
Vol 791-793 ◽  
pp. 818-821
Author(s):  
Shi Li ◽  
Xi Ju Zong ◽  
Yan Hu
Keyword(s):  
Transfer Function ◽  
State Space ◽  
State Space Model ◽  
Internal Model Control ◽  
Transfer Function Model ◽  
Function Model ◽  
Modeling And Control ◽  
Space Model ◽  
Biochemical Reactor ◽  
And Control

This paper is concerns with the study of modeling and control of biochemical reactor. Firstly, a mathematical model is established for a typical biochemical reactor, the mass balance equations are established individually for substrate concentration and biomass concentration. Then, the model is linearized at the steady-state point, two linear models are derived: state space model and transfer function model. The transfer function model is used in internal model control (IMC), where the filter parameter is selected and discussed. The state space model is applied in model predictive control (MPC), where controller parameters of control prediction horizon length and constraint of control variable variation are discussed.

Method of Identifying Key Quality Characteristics in Multistage Manufacturing Process Based on PLSR

2012 ◽  
Vol 217-219 ◽  
pp. 2580-2584 ◽  
Author(s):  
Ning Wang ◽  
Ji Chao Xu ◽  
Jian Feng Yang
Keyword(s):  
State Space ◽  
Manufacturing Process ◽  
State Space Model ◽  
Quality Characteristics ◽  
The State ◽  
Quality Analysis ◽  
Least Squares Regression ◽  
Space Model ◽  
Multistage Manufacturing ◽  
And Control

To improve the existing methods of identifying the key quality characteristics in multistage manufacturing process, the partial least squares regression (PLSR) method is combined with the state space model that a new method of identifying the key quality characteristics in multistage manufacturing process based on PLSR is proposed. According to the feature of multistage manufacturing process, the state space model is introduced to build the key quality characteristics identifying model for multistage manufacturing process, using the PLSR method to solve the problem of the quality characteristics such as multicollinearity, do model analyzing and identify the key quality characteristics. At last, the cigarette production process is presented as an example to introduce the application of this method. The result shows that this method can not only identify the key quality characteristics in multistage manufacturing process, but also establish the model of output quality effecting of all levels on the final product quality and its quality characteristics relationship, which reflect the structure of the multistage manufacturing process and causal relationship between quality characteristics at all process levels, provide the basis for quality analysis and control in multistage manufacturing process.

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