Autonomous Underwater Vehicle Depth Research Articles

Interval Type-2 Fuzzy-Model-Based Sampled-Data Control of an AUV Depth System with Input Saturation

This paper proposes a sampled-data fuzzy controller design technique for an autonomous underwater vehicle (AUV) depth system represented by an interval type-2 (IT-2) fuzzy model, considering input saturation. In the Takagi–Sugeno (T–S) fuzzy model of an AUV depth system, surge velocity is chosen as a premise variable. To address the associated uncertainty with this variable, we employ the IT-2 fuzzy modeling technique. Also, the controller proposed in this paper utilizes time-varying gains, ensuring superior exponential stability compared with traditional fixed gain approaches. Furthermore, a membership function-dependent (MFD) H∞ criterion is employed to enhance robustness for each subsystem individually. Taking into account the mentioned aspects, the controller design condition is derived in the form of linear matrix inequalities (LMIs). Finally, the effectiveness of the proposed method is validated through simulation examples.

The depth-keeping performance of autonomous underwater vehicle advancing in waves integrating the diving control system with the adaptive fuzzy controller

This study aims to develop an experimental-based adaptive fuzzy controller for the diving control system (DCS) of autonomous underwater vehicle (AUV) to ensure high stability and rapid integration. The DCS is designed with a depth sensor and an attitude and heading reference system (AHRS) to sense the attitude vector and the current depth of AUV in real-time as the control inputs of attitude close-loop and to calculate yaw and pitch controls of AUV. Therefore, the DCS can integrate depth-keeping and attitude stability controls into the AUV. To verify the robustness and adaptability of the DCS with adaptive fuzzy control, the DCS with universal fuzzy control (A-type DCS), improved fuzzy control (B-type DCS), and adaptive fuzzy control (C-type DCS) have been analyzed. The experimental analysis indicates that the C-type DCS features higher robustness to external force interference than the other types of DCS. The present study establishes an adaption function based on depth-keeping control experiments and demonstrates robustness of the adaptive fuzzy control DCS to environmental disturbances. Consequently, the proposed adaptive fuzzy control DCS is a model-free design that resolves the problem of depth-keeping and attitude stability controls of AUV with unknown hydrodynamic coefficients, rudder dynamics and time-varying external forces.

Autonomous Underwater Vehicle Depth and Pitch Trajectory Tracking Using Fiber-Reinforced Elastomer Bladders for Buoyancy Control

This article presents a variable buoyancy system that uses cephalopod-inspired, fiber-reinforced elastomer membranes as bladders to enable model-based depth and pitch control of an autonomous underwater vehicle. The fiber reinforcement allows for a single measurement of each membrane to fully define the geometry of the membrane, regardless of the membrane’s orientation or level of inflation. This allows for precise control of each bladder’s enclosed water mass and center of mass by adjusting the differential pressure between the inside of the bladder and the vehicle’s cabin using water from the environment as the working fluid. Positioning bladders at the fore and aft of the vehicle enables control of both the vehicle’s density and center of mass while minimizing center of mass disturbances due to sloshing in and gravitational loads on the membranes. A nonlinear, adaptive, backstepping, trajectory-tracking controller is presented and proven to be asymptotically stable with Lyapunov stability analysis. The advantages of the proposed variable buoyancy system and controller are demonstrated through simulation and validated with 2 degree of freedom depth and pitch step and trajectory-tracking experiments in a large water tank. We evaluate the performance of the bladders and controller on the CephaloBot, an autonomous underwater vehicle designed and built by our group.

Saturation Based Nonlinear FOPD Motion Control Algorithm Design for Autonomous Underwater Vehicle

The application of Autonomous Underwater Vehicle (AUV) is expanding rapidly, which drives the urgent need of its autonomy improvement. Motion control system is one of the keys to improve the control and decision-making ability of AUVs. In this paper, a saturation based nonlinear fractional-order PD (FOPD) controller is proposed for AUV motion control. The proposed controller is can achieve better dynamic performance as well as robustness compared with traditional PID type controller. It also has the advantages of simple structure, easy adjustment and easy implementation. The stability of the AUV motion control system with the proposed controller is analyzed through Lyapunov method. Moreover, the controlled performance can also be adjusted to satisfy different control requirements. The outperformed dynamic control performance of AUV yaw and depth systems with the proposed controller is shown by the set-point regulation and trajectory tracking simulation examples.

Design and experimental realization of a backstepping nonlinear H∞ control for an autonomous underwater vehicle using a nonlinear matrix inequality approach

This paper focuses on the development of a nonlinear [Formula: see text] control (NHC) algorithm for an autonomous underwater vehicle (AUV) in the vertical plane. A three-degree-of-freedom AUV depth model is developed in terms of a nonlinear affine form which is used to design the control algorithm. The depth is controlled using a backstepping technique which generates a desired pitch angle for the NHC algorithm. The nonlinear control is designed using the [Formula: see text]-gain analysis which is transformed into a Hamilton–Jacobi–Isaacs (HJI) inequality. Further, the HJI inequality is presented in terms of a nonlinear matrix inequality structure in order to find a solution for the NHC problem using the concept of convex optimization. Hence, we desire to test the convex property of the nonlinear system before the realization of the control algorithm. The robust behaviour of the NHC algorithm is realized by ensuring the performance of the proposed control algorithm in the face of model and parameter uncertainties. A comparison between the NHC algorithm and the state-dependent Riccati equation is made in order to show the efficacy of the developed control algorithm. Furthermore, an experimental study of the proposed control scheme has been pursued to analyse the effectiveness of the developed control algorithm.

Moth-inspired chemical plume tracing on an autonomous underwater vehicle

This paper presents a behavior-based adaptive mission planner (AMP)to trace a chemical plume to its source and reliably declare the source location. The proposed AMP is implemented on a REMUS autonomous underwater vehicle (AUV)equipped with multiple types of sensors that measure chemical concentration,the flow velocity vector, and AUV position, depth, altitude, attitude, and speed. This paper describes the methods and results from experiments conducted in November 2002 on San Clemente Island, CA, using a plume of Rhodamine dye developed in a turbulent fluid flow (i.e., near-shore ocean conditions). These experiments demonstrated chemical plume tracing over 100 m and source declaration accuracy relative to the nominal source location on the order of tens of meters. The designed maneuvers are divided into four behavior types: finding a plume,tracing the plume, reacquiring the plume, and declaring the source location. The tracing and reacquiring behaviors are inspired by male moths flying up wind along a pheromone plume to locate a sexually receptive female. All behaviors are formulated by perception and action modules and translated into chemical plume-tracing algorithms suitable for implementation on a REMUS AUV. To coordinate the different behaviors, the subsumption architecture is adopted to define and arbitrate the behavior priorities. AUVs capable of such feats would have applicability in searching for environmentally interesting phenomena, unexploded ordnance, undersea wreckage, and sources of hazardous chemicals or pollutants.

Absolute Positioning of an Autonomous Underwater Vehicle Using GPS and Acoustic Measurements

Kinematic global positioning system (GPS) positioning and underwater acoustic ranging can combine to locate an autonomous underwater vehicle (AUV) with an accuracy of /spl plusmn/30cm (2-/spl sigma/) in the global International Terrestrial Reference Frame 2000 (ITRF2000). An array of three precision transponders, separated by approximately 700 m, was established on the seafloor in 300-m-deep waters off San Diego. Each transponder's horizontal position was determined with an accuracy of /spl plusmn/8 cm (2-/spl sigma/) by measuring two-way travel times with microsecond resolution between transponders and a shipboard transducer, positioned to /spl plusmn/10 cm (2-/spl sigma/) in ITRF2000 coordinates with GPS, as the ship circled each seafloor unit. Travel times measured from AUV to ship and from AUV to transponders to ship were differenced and combined with AUV depth from a pressure gauge to estimate ITRF2000 positions of the AUV to /spl plusmn/1 m (2-/spl sigma/). Simulations show that /spl plusmn/30 cm (2-/spl sigma/) absolute positioning of the AUV can be realized by replacing the time-difference approach with directly measured two-way travel times between AUV and seafloor transponders. Submeter absolute positioning of underwater vehicles in water depths up to several thousand meters is practical. The limiting factor is knowledge of near-surface sound speed which degrades the precision to which transponders can be located in the ITRF2000 frame.