Hd Nguyen

Development and Control of a Low-Cost, Three-Thruster, Remotely Operated Underwater Vehicle

This paper presents the development of a low cost Remotely Operated Vehicle (ROV) which consists of open source hardware and has three thrusters. First, the hardware of the vehicle, including the actuators, sensors, and control structure, is described. Second, to study the relationship between the thrust forces and the performance of the ROV, a mathematical model of the vehicle in the form of a kinematic and kinetic model is established. Next, a hybrid control algorithm consisting of two components, namely model-based and PID algorithms, is proposed for surge speed, depth, and heading control. The effectiveness of the hybrid control algorithm is then verified by the ROV mathematical model-based simulations. Finally, free running tests for depth control are conducted to verify the robustness and reliability of the control structure and proposed algorithms.

Predictor-based model reference adaptive control of an unmanned underwater vehicle

Unmanned Underwater Vehicles (UUVs) are being deployed in advanced applications that require precise manoeuvring close to complex underwater structures such as oilrigs and subsea installations or moving objects such as ships and submarines. The effect of vehicles hydrodynamic parameter variations is significant in such scenarios and in extreme conditions the UUV may experience loss of control. In addition, external disturbances and actuator failures degrade the performance of the UUV. Adaptive control has been identified as a promising solution that can improve the performance in such situations. However, adaptive control is not widely used in UUVs mainly due to the trade-off between fast learning and smooth control signals. The latter can be guaranteed at low learning rates but require additional input to improve learning. The Predictor Model Reference Adaptive Control (PMRAC) is one such method that uses a prediction error to improve learning. In this paper, the performance of PMRAC in UUV applications is investigated and compared to standard Model Reference Adaptive Control (MRAC) at low learning rates under normal operational conditions, partial actuator failure, and under the influence of external disturbances. Simulation results show that PMRAC significantly reduces the tracking error compared to MRAC. In addition, PMRAC is less affected and recovers quickly from actuator failure and external disturbances, while generating smooth control signals with less oscillation compared to MRAC.

Haptic driving system for surge motion control of underwater remotely operated vehicles

This paper presents the development of a haptic driving system for underwater Remotely Operated Vehicles (ROVs). Unlike conventional ROV driving systems, which only transmit commands from the pilots to the vehicle controller, the proposed haptic device has the ability to provide information about the working environment back to the operator via tactile sensing. In this paper, the drag force generated by the fluid interaction is chosen as the feedback objective for the haptic control. Hence, the haptic device helps the operator to sense the drag force via feedback through the joystick. A one degree of freedom (1-DOF) haptic joystick was developed to first control the surge motion of a simulated ROV model, with future work aimed at evaluation on an actual vehicle. The results of the haptic controller linked to the simulation model proved the feedback ability of the controller and identified areas of improvement, especially with regard to noise filtering.

Computational fluid dynamics re-mesh method to generating hydrodynamic models for maneuvering simulation of two submerged bodies in relative motion

An Autonomous Underwater Vehicle (AUV) operating closer to a larger vessel experiences significant hydrodynamic forces requiring an adaptive control mechanism to maintain acceptable trajectory. It is therefore important that the designer understands the hydrodynamic characteristics of the vehicle in this scenario in order to develop appropriate control algorithms to deal with its dynamic behaviour. This requires developing simulations of the vehicles behaviour close to the larger vessel, the control algorithms, and the dynamic interface between the two. This paper presents a method to generate a complete hydrodynamic model of underwater vehicles using the Computational Fluid Dynamics (CFD) code ANSYS CFX, which can then be interfaced with the vehicles control algorithms within a simulation environment. The essential aspect of the method is the re-mesh approach, where the mesh deforms locally around the bodies using an Arbitrary Lagrangian-Eulerian form of the governing fluid equations and re-meshes when the deformation significantly compromises the quality of the mesh. This overcomes the motion limitations imposed by a pure deforming mesh approach. Preliminary work to validate the method is based on two smooth spheres moving relative to each other. It shows that this method is able to adequately simulate the fluid behaviour around the bodies. The paper also describes the future work focused on a 6 degrees-of-freedom (6-DOF) AUV modelled in CFD to obtain its hydrodynamic behaviour to be interfaced to the control system within MATLAB.

Command governor adaptive control for an unmanned underwater vehicle

This paper presents the design and simulation of a command governor based adaptive controller (CGAC) for a remotely operated underwater vehicle. The command governor modification is applied for the first time to an underwater vehicle simulation of the actual vehicle for improved transient performance and disturbance rejection. The vehicle dynamics are assumed to be decoupled thus allowing for the design of separate heading and depth controllers. The results show that in contrast to standard adaptive controllers, command governor based adaptive controllers are able to produce better transient performance as well as improve the overall response even at low learning rates. Furthermore, simulation results verify the disturbance rejection capability of the command governor based adaptive controller, which is necessary to effectively and safely operate an unmanned underwater vehicle in real environments.

Design, modelling and simulation of a remotely operated vehicle – Part 1

Continuing the previously published study [4], this paper focuses on hardware and Virtual Reality (VR) model development of a three-thruster Remotely Operated Vehicle (ROV). The paper included setting up an on-board electronic system with the associated suite of sensors and the required communication protocol. This system utilises a master-slave structure, which consists of an onshore station computer and an on-board open source microcontroller. To improve the controllability of the driving system, a VR model of the ROV is designed to reflect the altitude and attitude of the physical vehicle. By using the feedback signals from the sensors, the VR model operates in a similar manner to the actual vehicle. Hence, it provides the operator with the capability to monitor the ROV operation within a virtual environment and enables the operator to control the ROV based on the visual inputs and feedback. Finally, real time simulations are presented to validate the interaction between the ROV operator and the VR model. To provide realistic operational conditions, the effects of sensor noise and water current disturbances are included to the simulation programme. The results show that the performance of the VR ROV is stable even with these disturbances.

Modelling of a surface vessel from free running test using low cost sensors

Identification of hydrodynamic coefficients and accessibility of accurate mathematical model to predict actual responses of vessels has practical significance to design computer-based simulators and apply new control algorithms, thus effective methods and proper devices should be investigated to do the modelling. The aim of this study was to estimate hydrodynamic coefficients of a surface vessel from the free running test using an experimental modelling method. Working as the embedded platform and data acquisition card, myRIO was utilized to control the scaled model, namely ‘P&O Nedlloyd Hoorn’, and measure her motion states using low cost sensors including a Global Positioning System (GPS) receiver, accelerometer, gyroscope and digital compass. System identification was conducted utilizing the processed experimental data with Kalman filter to estimate the hydrodynamic coefficients of a mathematical model in four degree of freedom (DOF) including surge, sway, yaw and roll. The developed mathematical model of the scaled model was validated through the comparison between the experimental data and simulation results. It has demonstrated that the proposed low cost hardware and system identification algorithm is capable of estimating hydrodynamic coefficients of the proposed mathematical model of the scaled surface vessel.

Experimental study of command governor adaptive control for unmanned underwater vehicles

The control of unmanned underwater vehicles (UUV) is a complex problem mainly due to the nonlinear dynamics, uncertainty in model parameters, and external disturbances. Adaptive control is a promising solution to address these issues. Nevertheless, its full potential is yet to be realized, especially in underwater vehicle applications, mainly due to the compromise between the transient performance and a smooth control signal. The addition of a new command governor with standard model reference adaptive control (MRAC) named as a command governor adaptive control (CGAC) has been proposed as a promising solution to this trade-off. Nevertheless, the suitability of CGAC in underwater vehicle applications and its performance are yet to be verified. This paper fills this knowledge gap and experimentally validates the suitability and performance of CGAC in underwater vehicle applications. The standard MRAC is used as the baseline for performance comparison. Experimental results showed that CGAC achieves a low frequency control signal through low gain values and improves transient performance through modifications to the command signal. In addition, the ability of CGAC to overcome disturbances such as tether forces, and tolerate faults such as partial thruster failure was confirmed. Another interesting feature observed in these experiments is the ability of CGAC to operate despite the thruster dead zone, which standard MRAC is unable to perform without a dead-zone inverse. Therefore, according to the results CGAC performs better than standard MRAC and thus is a promising solution for future underwater vehicle applications.

Artificial potential field for remotely operated vehicle haptic control in dynamic environments

This article presents the development of a novel artificial potential field technique for a haptic controller of an underwater remotely operated vehicle to assist the pilot to avoid obstacles. The artificial potential field technique is used to replicate potential risks presented by underwater obstacles in the vicinity of the remotely operated vehicle. A risk avoidance vector is calculated based on the artificial potential field then transmitted to a haptic joystick to generate the tactile feedback, which enables the remotely operated vehicle pilot to be alerted to potential dangers due to surrounding obstacles and prompt the pilot through the joystick to avoid the dangers and safely navigate the vehicle. The novel artificial potential field technique can deal with both stationary and moving obstacles as it is combined with an obstacle motion detection algorithm based on fuzzy C-means and Kalman filter algorithms. These algorithms are applied to process raw data from the scanning sensor to identify the relative positions and velocities between the remotely operated vehicle and the obstacles, which are employed within the artificial potential field calculations. To validate the proposed technique, the haptic joystick and the novel artificial potential field formula were applied to control a simulated remotely operated vehicle within a virtual reality environment.

Performance Evaluation of an Underwater Vehicle Equipped with a Collective and Cyclic Pitch Propeller

This paper presents modelling and simulation of an underwater vehicle equipped with a collective and cyclic propeller (CCPP). A CCPP has been applied in helicopters and it generates both axial and side thrusts that move a helicopter in all directions. If axial and side thrusts of the CCPP are controlled as desired it is possible to apply the CCPP to an underwater vehicle. A new CCPP has been designed and fabricated for a torpedo shaped underwater vehicle. Captive experiments were conducted to quantify the performance of the CCPP. The paper reports recent development of an underwater vehicle equipped with the CCPP including design and fabrication of the experimental facility, conduct of experiments, modeling, performance of the CCPP and simulation of the vehicle propelled by the CCPP.