ALBERT

Description: This paper presents a robust cascaded control strategy to underwater robot thrust. The dynamics of surge motion, of propeller axial flow, of propeller shaft, and of electrically driven circuit in the motor constitute a cascaded system with respect to propeller thrust. Instead of the usual parameter perturbation, generalized modeling errors are considered in the plant, which may be parametric errors, ignored high-order modes, or some unmodeled dynamics in the underwater thrust system. External disturbances are also taken into account, which may be the random noises from mechanical or electrical equipment, or the environmental forces possibly induced by nonuniform currents, ocean internal wave, or cable tension. Combined with state feedback control, an online neural network (NN) compensator is introduced to identify the modeling errors, while L2-gain design is used to suppress the externally continuous or instantaneous disturbances. The Lyapunov's second method is applied to instruct the controller design, which guarantees the uniformly ultimately bounded (UUB) stability of the error system. By analyzing the tracking errors, it is recommended how to properly select the controller parameters. Good tracking performance and reasonable control inputs are illustrated by numerical simulations.

Description: Real-time 3-D acoustical imaging technique is a key advance to broaden the scope and enhance the feasibility of underwater missions. In this paper, a real-time 3-D underwater acoustical imaging system to handle the actual tasks under a narrowband excitation is presented. The system consists of three parts: a transmitter, a receiving hydrophone array, and a signal processor. In this system, a distributed and parallel subarray (DPS) beamforming algorithm is proposed to process the acquired signals from a scene placed in the far field. The DPS beamforming algorithm is an approximate method for the sonar signal processing with an advantageous computational efficiency. The direct method (DM) and fast Fourier transform (FFT) beamforming are compared with DPS beamforming for the memory and computational requirements. Based on this algorithm, a prototype was developed, which has been extensively employed in the lake and sea trials. The trials demonstrate that the system can achieve the 3-D imaging of the scene and meet the real-time requirement of the underwater operations.

Description: This paper addresses the modeling and experimental identification of six different six degree-of-freedom (6-DOF) coupled nonlinear second-order plant models. We report a comparative experimental evaluation of six different candidate plant models whose unknown plant parameters are estimated from data obtained in free-motion vehicle trials. The parameter estimation methodologies of ordinary least squares (OLS), total least squares (TLS), and underdetermined TLS were employed to identify experimentally the unknown plant model parameters. We evaluate the performance of each of the six different 6-DOF coupled nonlinear finite-dimensional plant models of an underwater vehicle estimated by OLS and the plant model identified by TLS by comparing the mean absolute error between the experimentally observed vehicle velocities and the velocities obtained by a numerical simulation of the identified plant models. We also report a cross validation which evaluates the performance of a plant model to accurately reproduce observed plant velocities for experimental trials differing from the trials from which the plant model parameters were estimated. We conclude that: 1) plant models identified by TLS generally perform better (i.e., more accurately reproduce observed experimental behavior) than models identified by OLS; and 2) plant models including fully parametrized coupled quadratic drag terms perform best overall in cross validation. This study has the following contributions: it is the first reported experimental 6-DOF fully coupled plant model identification and cross validation of a low-speed, fully actuated, and neutrally buoyant underwater vehicles; it is the first experimental 6-DOF plant model identification for this same class of underwater vehicles during free-flight experiments; and it is the first reported use of TLS to perform 6-DOF plant model identification of an underwater vehicle.

Description: Dead-reckoning (DR) navigation is used when Global Positioning System (GPS) reception is not available or its accuracy is not sufficient. At sea, DR requires the use of inertial sensors, usually a gyrocompass and an accelerometer, to estimate the orientation and distance traveled by the tracked object with respect to a reference coordinate system. In this paper, we consider the problem of DR navigation for vessels located close to or on the sea surface, where motion is caused by ocean waves. In such cases, the vessel pitch angle is fast time varying and its estimation by direct measurements of orientation is prone to drifts and noises of the gyroscope. Regarding this problem, we propose a method to compensate for the vessel pitch angle using a single acceleration sensor. Using a constraint expectation–maximization (EM) algorithm, our method classifies acceleration measurements into states of similar pitch angles. Subsequently, for each class, we project acceleration measurements into the reference coordinate system along the vessel heading direction, and obtain distance estimations by integrating the projected measurements. Results in both simulated and actual sea environments demonstrate that, by using only acceleration measurements, our method achieves accurate results.

Description: In this paper, the authors study the problem of robust adaptive path-following control for underactuated ships with model uncertainties and nonzero-mean time-varying disturbance. A concise adaptive neural network (NN)-based control scheme is proposed using backstepping, feedforward approximations, dynamic surface control, and minimal learning parameter techniques. In addition, to tackle the strong couplings among state variables (including the underactuated state variable) and underactuated characteristics, much effort is put into guaranteeing semiglobal uniform ultimate boundedness of the ship motion control system. The outstanding advantage of this scheme is that the control law has a concise form and is easy to implement in practice due to a smaller computational burden, with only two online parameters being tuned to tackle the uncertainties. The simulation results demonstrate the effectiveness of the proposed algorithm, especially including the experiment in the simulated marine environment.

Description: Plankton image classification is an important, yet challenging, problem in marine biology. This challenge can be attributed to: 1) large within-class variations; 2) large between-class similarity; and 3) large noise. To mitigate these problems, we propose a novel subspace classification framework, called pairwise nonparametric discriminant analysis for binary plankton image recognition. In this framework, first we decompose the multiclass recognition into a combination of pairwise binary classes, then train an appropriate classifier for each class pair using the nonparametric discriminant analysis technique (a newly developed subspace analysis technique) to effectively remove unwanted information (such as the within-class variations and the noise) and extract discriminant information (such as the boundary structural information), and, finally, combine all the pairwise classifiers using an efficient fusion rule for real-time classification. Extensive experiments are conducted on a large data set to show the improvement obtained by our new approach over the state-of-the-art ones.

Description: A novel and fully automatic rigid fish cage system has recently been developed for deployment in the waters of Korea. The cage structure has 12 sides, incorporating a steel framework with a diameter and depth of 5.92 and 2.91 m, respectively. Attached to the steel framework is a housing for motor valves controlling variable ballast tanks, eight housings for two air compressors, a main control system, four batteries, a reserve air tank, four high air pressure tanks, 12 variable ballast tanks, and a seawater pump housing. The net of the fish cage is tightened across the frame to minimize volume reduction due to currents. The cage is outfitted with a control station located above the valve housing. With the control system, the buoyancy can be adjusted by utilizing compressed air stored in the four high air pressure tanks. The mechanical components of the ballast systems are operated by automated software that incorporates control and monitoring algorithms. The software initiates control of the ballasting components so the fish cage system can submerge if a preselected sea state occurs. The automatic control station incorporates a wind gauge, wireless communication printed circuit boards (PCBs), and a transmitting antenna. During operation, it monitors the wind speed, so the cage can be submerged before extreme sea states and then surfaced after the weather has passed and the conditions are considered safe. The control station also regulates the flow of air and seawater to and from the variable ballast tanks in response to the surface environmental conditions. Control can also be done remotely by a facility operator. In the development process, in situ tests were conducted to assess the performance of the submersion mechanism and the reliability of the automatic control system with a 1/4 size fish cage of similar construction. During the tests, the vertical position and inclination of the fish cage in the water column were measured. During the tests, the clo- e/open states of the motor valves that control the 12 variable ballast tanks were also assessed during descent and ascent operations. The successful performance of the 1/4 size fish cage during the tests showed promise that such a system could possibly be used on a much larger scale to avoid the rigors of the environment in support of commercial level offshore aquaculture.