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In this study a safe and smooth path planning containing the slightest risk is considered for an Unmanned Underwater Vehicle (UUV). To do so, three smooth and continues functions resembling the three dimensional path are introduced and then their parameters are optimized using the particle swarm optimization method to find the safest possible path. For each point in space a numeric value is considered as vulnerability and the objective function is the integral of the vulnerability over the path produced. This path forms controlling signals which through a TSK fuzzy controller, the UUV is guided. The new arrangement of the propulsion vehicle subsurface was modeled. Since for the design of the controller, the parameters of the Under Water Vehicle dynamic system not used, so the control system is robust with respect to parameter Uncertainties. In the last section three environments with different complexities are considered to illustrate the creating process’s performance of the path and it is concluded that this method demonstrates desired performance in the development of a safe and smooth path through a harmful environment and the design of an adequate controller.

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In this paper the effect of horizontal control surfaces (stern fins) angle on the drag force of the Subsea R&D Autonomous Underwater Vehicle (AUV) is investigated using both experimental fluids dynamic and numerical fluids dynamic methods. The experiments were conducted in the Subsea R&D towing tank using a 1:1 scale model of the AUV, at various stern angles and in a speed range of 1 to 3 m/s. A pair of Naca shaped struts was used to connect the AUV to the carriage dynamometer. The stern drag force was experimentally calculated at various stern angles and towing speeds. The results obtained by experimental method compared with those obtained numerically by commercial computational fluid dynamics CFX code. Both experimental and numerical results showed that as the stern angle increases, the total AUV drag force increases, and the drag force coefficient can be estimated by a second order polynomial. The results showed that, at a speed of 1.5m/s, as the stern angle increases to 45 degree, the drag coefficient increases up to 174 percent It was also observed that at a specific stern angle, the drag force due to stern fin increases with the AUV speed. Variation of axial force as a function of stern angle was determined by using both experimental and numerical methods. The results obtained by both methods showed that the expensive experiments conducted in towing tanks can be replaced by numerical simulations.

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A nonlinear model for Autonomous Underwater Vehicles is proposed. In order to describe a more precise dynamic behavior, the nonlinear model for both Lateral and Longitudinal subsystems is derived based on all applied forces and moments. The proposed model can be explained as an extended linear model for AUV in depth and azimuth motions where some nonlinearities are taken into account. Due to some practical issues as well as the form of proposed model, the identification problem based on Least Square method is formulated to achieve the system parameters. By considering unstable dynamic of system, the open loop system cannot be excited. In this case, the PID regulators with simple tuning parameters are proposed in both Lateral and Longitudinal subsystems and the identification problem by utilizing sinusoidal inputs is followed within a feedback loop. Based on measurable variables i.e. linear moments, angular velocities and Euler angles, and utilizing some dynamic filters, the Least Square method is then applied to estimate the model parameters. The effectiveness of proposed nonlinear model as well as the parameter identification approach are finally demonstrated through some numerical simulations.

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Guidance of an underwater vehicle in the wake of target due to the complexity of guidance in water and also sensor limitations, is still the most important homing guidance method. Disadvantages of wake guidance can be mentioned as zigzag motion for rediscovering the wake in its path which according to the decreasing linear speed of approaching the target, sometime it doesn't reach the target and collision fails. Therefore various ideas, with both positive and negative aspects, have been introduced to improve movement in the wake path. According to complexity of the wake model and also its instability in order to extract its parameters, makes it a very nonlinear phenomenon and guidance in it is a problematic in underwater vehicle. Since the wake detection area by the sensor is not enough widespread, wake is just discovered in the near of itself. Hence the real wake path is not detectable and therefore advanced guidance method is not available. For this reason, it is suggested to use a method of unknown path tracking for the wake guidance. This guidance law consists of two parts of path estimation and nonlinear guidance. The estimation method is performed using particle filter that has the ability to estimate nonlinear paths. The stability proof of nonlinear guidance method is done by Lyapunov.

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Currently, hovering type autonomous underwater vehicles (HAUV’s) are very noteworthy, due to theirs unique capabilities and features. Appropriate maneuverability and controllability is the most important feature for a HAUV that, make it better than other AUV’s. In order to increase stability and controllability of robot, the ballast tank is applied for a HAUV. Using of ballast tank in HAUV was not common before. In this paper a new underwater vehicle is presented, including three ballast tanks and three thrusters. In this underwater vehicle, the number of thrusters is less than original robot. In this paper, dynamics modeling and tracking control of this new underwater vehicle is investigated. The results show that the heave and pitch DOF’s can be reachable by using of the ballast tanks and we don’t need to use extra thrusters for these degrees of freedoms.

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In this paper, a constrained predictive controller is designed using Laguerre functions to control the depth and steering of an autonomous underwater vehicle considering underwater disturbances. Due to under-actuated nonlinear coupled dynamics, parameters uncertainty, external underwater disturbances autonomous underwater vehicles are complicated. Moreover, the underwater autonomous vehicle investigated in this study includes constraints on actuators leading a more complex problem. In this study, first, the nonlinear dynamics of the autonomous underwater vehicle utilized for the controller design has been modeled. Then, Laguerre orthogonal functions were used in the constrained predictive controller design for reducing computational time and accelerating optimization process. Optimized, online, high precision, implementation capability, consider constraints purposefully and robust properties against disturbances can be mentioned as the most important advantages of designed controller. In addition, predictive control method is robust against disturbances. To monitor the methods’ performance, the autonomous underwater vehicle was modeled and then a comparison between the controller's calculation time with and without the Laguerre functions was also represented. At the end, the simulation results obtained from this controller, using Laguerre functions, showed the efficiency and effectiveness of the proposed solution.