Underwater Glider Modelling And Analysis For Variable Control Parameters

Underwater glider is a type of autonomous underwater vehicle that can glide by controlling their buoyancy and attitude using internal actuators. By changing the vehicle’s buoyancy intermittently, forward motion can be achieved. Deriving the mathematical model directly from the system can be too complicated due to time constraints in prototyping development processes. This thesis presents the early development of the USM underwater glider platform consist of prototype development involves vehicle concept design using SolidworksTM, vehicle simulations by Computational Fluid Dynamics (CFD) and alternative way of modelling known as system identification in order to obtain the underwater glider system model. The appropriate control parameters for underwater glider control were determined by selecting the ballast rate as the input. Three aspects of the dynamics of a glider will be observed, i.e. net buoyancy, depth of the glider and pitching angle. The best three parametric models that are able to estimate the system correctly are chosen, and the fit between measured and estimated outputs is presented in order to get an optimal underwater glider vehicle model for USM underwater glider platform

Modeling And Identification Of An Underwater Glider.

Underwater gliders are type of autonomous underwater vehicle that glide by controlling their buoyancy and attitude using internal actuators

A U-MODEL BASED NONLINEAR ADAPTIVE CONTROL FOR UNDERACTUATED MULTIVARIABLE UNMANNED MARINE VEHICLES

In this study, underactuated coupled nonlinear adaptive control for multivariable unmanned marine vehicles platform were studied, designed, developed, and tested. Designing a controller that is suitable for both surface and underwater unmanned marine vehicle is challenging tasks due to unstructured marine environment, highly nonlinear due to the hydrodynamics and parameters interaction plus with the external disturbances. Coupled nonlinear adaptive control using U-Model based internal model control (IMC) approach can be implemented to overcomes these challenges. IMC approach offer a good disturbances rejection capability. The method implements coupled nonlinear identification via U-Model which able to model the system with minimum error. Then, the controller is formularised using Newton Raphson method as a representation of the inverse of the U-Model

Data compression for underwater glider system using frequency sampling filters

227-235Data acquisition from underwater glider system yields large amounts of data. This may lead to a long computational time during the identification process. The raw data may also contain complex system disturbance information which may require a sophisticated optimization algorithm to achieve desirable results. In this paper, frequency sampling filters approach is used as a tool to compress the data and obtain meaningful parameter that describes the empirical model of the system. The use of finite impulse response model and the maximum likelihood method will play a role in eliminating the bias and noise effects of the glider data systems. By performing this procedure, the compressed, cleaned and unbiased data will be obtained, in which, it can be further used to develop a model of the glider system, also to analyze and observe for optimization and controller design purposes

Underactuated nonlinear adaptive control approach using U-Model incorporated with RBFNN for multivariable underwater glider control parameters

2482-2492Underwater glider platform represents the maturing technology with a large cost saving over current underwater sampling process. It can survey and monitor the sea environment cost-effective manner combining survey capabilities, simultaneous water sampling and environmental data gathering capacities. It can perform a wide range of fully automated monitoring data measurement over an extended period of time. This paper will focus on the design of multivariable underactuated nonlinear adaptive control using U-model methodologies. Underwater glider control, modelling and identification approach was reviewed in order to formulate the design, development and control approach of underwater glider development using multivariable adaptive U-model nonlinear control approach. U-model methodology simplifies the control synthesis with the influence of the uncertainties and external disturbances by selecting appropriate control structures. Most of the autonomous underwater vehicle (AUV) neglected the coupling effect of the dynamics during process modelling while U-model enables to include the coupling effect using the inverse Jacobian matrix. U-model incorporated with RBFNN enhance the adaptive nonlinear control synthesis. Thus contributes towards the underactuated nonlinear adaptive control development and process modelling