Omni-Directional Intelligent Navigator Research Articles

Neural Adaptive Intermittent Output Feedback Control for Autonomous Underwater Vehicles With Full-State Quantitative Designs.

In this article, a neural adaptive intermittent output feedback control is investigated for autonomous underwater vehicles (AUVs) with full-state quantitative designs (FSQDs). To achieve the prespecified tracking performance determined by quantitative indices (e.g., overshoot, convergence time, steady-state accuracy, and maximum deviation) at both kinematic and kinetic levels, FSQDs are designed by transforming constrained AUV model into an unconstrained model via one-sided hyperbolic cosecant boundaries and nonlinear mapping functions. An intermittent sampling-based neural estimator (ISNE) is devised to reconstruct the matched and mismatched lumped disturbances as well as immeasurable velocity states of transformed AUV model, where only system outputs after intermittent sampling are required. Using the estimations of ISNE and the system outputs after triggering, an intermittent output feedback control law incorporated with hybrid threshold event-triggered mechanism (HTETM) is designed to achieve ultimately uniformly bounded (UUB) results. Simulation results are provided and analyzed to validate the effectiveness of the studied control strategy with application to an omnidirectional intelligent navigator (ODIN).

Event-Triggered Saturation-Tolerant Control for Autonomous Underwater Vehicles With Quantitative Transient Behaviors

This paper proposes an event-triggered saturation-tolerant solution to the problem of trajectory tracking control with application to autonomous underwater vehicles (AUVs) considering quantitative transient behaviors. To prespecify the transient tracking behaviors quantitatively and avoid the possible violation of behavioral functions induced by input saturation, a saturation quantitative prescribed performance control (SQPPC) is proposed, where auxiliary subsystems are devised to monitor the input saturation and modify the behavioral boundaries, such that SQPPC can automatically adapt to the input saturation without transgressing the exact output constraints. Intermittent measurement-based uncertainty and disturbance estimator (IMUDE) is devised to reconstruct the lumped disturbances with reduced communication resource usage. Building upon the estimation results obtained from IMUDE, an event-triggered control law is designed, attaining ultimately uniformly bounded (UUB) results, where a relative threshold-based event-triggered mechanism (RTETM) is constructed to reduce the communication resource dissipation along the controller-to-actuator channel. To validate the effectiveness of the proposed control strategy in controlling an omni directional intelligent navigator, simulation results are provided and analyzed.

Finite-time circular formation around a moving target with multiple underactuated ODIN vehicles

In this paper, we present a framework for achieving circular formation of a two-dimensional moving target using a team of underactuated Omni-Directional Intelligent Navigator (ODIN) vehicles. The main goal is to ensure uniform circumnavigation of the moving target with prescribed radius, velocity and inter-vehicle spacing. In the formation, part of vehicle group is capable of obtaining information from the moving target. Distributed adaptive control laws are developed for the group of vehicles by merging the techniques of command filter and backstepping control. A robust controller is designed to compensate for the effect of non-smooth actuator saturation. With the proposed control, the convergence to a circular formation performance can be ensured in a finite time. Finally, numerical simulations are presented to show the effectiveness of the proposed formation scheme.

Double-Loop Integral Terminal Sliding Mode Tracking Control for UUVs With Adaptive Dynamic Compensation of Uncertainties and Disturbances

This paper focuses on the trajectory tracking control of unmanned underwater vehicles (UUVs) in the presence of dynamic uncertainties and time-varying external disturbances. Two adaptive integral terminal sliding mode control schemes, namely, adaptive integral terminal sliding mode control (AITSMC) scheme and adaptive fast integral terminal sliding mode control (AFITSMC) scheme are proposed for UUVs based on integral terminal sliding mode (ITSM) and fast ITSM (FITSM), respectively. Each control scheme is double-looped: composed of a kinematic controller and a dynamic controller. First, a kinematic controller is designed for each of the two control schemes. The two kinematic controllers are based on ITSM and FITSM, respectively. These kinematic controllers yield local finite-time convergence of the position tracking errors to zero meanwhile avoid the singularity problem in the conventional terminal sliding mode control (TSMC). Then, using the output of the kinematic controller as a reference velocity command, a dynamic controller is developed for each of the two control schemes. The two dynamic controllers are also based on ITSM and FITSM, respectively. An adaptive mechanism is introduced to estimate the unknown parameters of the upper bound of the lumped system uncertainty which consists of dynamic uncertainties and time-varying external disturbances so that the prior knowledge of the upper bound of the lumped system uncertainty is not required. The estimated parameters are then used as controller parameters to eliminate the effects of the lumped system uncertainty. The convergence rate of the integral terminal sliding variable vector is investigated and the local finite-time convergence of the velocity tracking errors to zero in the ITSM or FITSM is obtained. Finally, based on the designed kinematic and dynamic controllers, the finite-time stability of the full closed-loop cascaded system is shown. The two proposed control schemes improve the tracking accuracy over the existing globally finite-time stable tracking control (GFTSTC) and adaptive nonsingular TSMC schemes, and enhance the robustness against parameter uncertainties and external disturbances over the GFTSTC scheme. Compared with the conventional adaptive integral sliding mode control (AISMC) scheme, the two proposed control schemes offer faster convergence rate and stronger robustness against dynamic uncertainties and time-varying external disturbances for the trajectory tracking control of UUVs due to involving the fractional integrator. Comparative numerical simulations are performed on the dynamic model of the Omni Directional Intelligent Navigator UUV for two trajectory tracking cases. The convergence rate and robustness to uncertainties and disturbances are quantified as the convergent time and bounds of the steady-state position and velocity tracking errors, respectively. The results show that the two proposed control schemes improve at least 20s in convergence rate and enhance about 2% robustness in position tracking and 20% robustness in velocity tracking over the AISMC scheme.

Neural network-based nonlinear sliding-mode control for an AUV without velocity measurements

ABSTRACTFor an autonomous underwater vehicle (AUV), a nonlinear sliding-mode control based on linear-in-parameter neural network (NSMC-NN) is proposed to deal with the unknown dynamics and the external environmental disturbances and a first-order robust exact differentiator is introduced considering unknown velocities of an AUV. The sliding-mode surfaces of NSMC-NN can enter into the boundary layers after a period that depends on the design parameters. To demonstrate the feasibility of the proposed controller, simulation studies applying Omni-Directional Intelligent Navigator (ODIN) are carried out, compared with proportional–integral–derivative (PID) and the modified sliding-mode control (MSMC). The simulation results show that the presented control method can achieve the effective control performance.

Robust adaptive tracking control of underactuated ODINs under stochastic sea loads

Although environmental loads induced by waves, wind, and ocean currents on marine vessels are naturally stochastic, all existing works on controlling these vehicles treat these loads as deterministic. This treatment deteriorates the control performance in a practical implementation. This paper presents a method to design controllers that force an underactuated omni-directional intelligent navigator (ODIN), a spherical underwater vehicle, to track a reference trajectory in two-dimensional space. Motivated by the vehicle’s steering practice, the yaw angle regarded as a virtual control plus the surge thrust force are used to force the position of the vehicle to globally track its reference trajectory. The control design is based on several recent results developed for stability and control of stochastic systems, potential projection functions, and backstepping and Lyapunov’s direct methods. Simulations are included to illustrate the effectiveness of the proposed results.

Control of fully actuated ocean vehicles under stochastic environmental loads in three dimensional space

Although environmental loads induced by waves, wind, and ocean currents on ocean vehicles are naturally stochastic, all existing works on controlling these vehicles treat the loads as deterministic. This treatment deteriorates the control performance or even results in an unstable closed loop system in a practical implementation. This paper presents a method to design controllers that force a fully actuated ocean vehicle under stochastic environmental loads to track a reference trajectory in three dimensional space. The control design is based on several recent results developed for stability and control of stochastic systems, and backstepping and Lyapunov׳s direct methods. The modified Rodrigues parameters are used for the attitude representation of the vehicle to reduce singularities in comparison with the use of Euler-angles and Rodrigues parameters. Simulations on an omni-directional intelligent navigator illustrate the results.

Global inverse optimal tracking control of underactuated omni-directional intelligent navigators (ODINs)

This paper presents a design of optimal controllers with respect to a meaningful cost function to force an underactuated omni-directional intelligent navigator (ODIN) under unknown constant environmental loads to track a reference trajectory in two-dimensional space. Motivated by the vehicle’s steering practice, the yaw angle regarded as a virtual control plus the surge thrust force are used to force the position of the vehicle to globally track its reference trajectory. The control design is based on several recent results developed for inverse optimal control and stability analysis of nonlinear systems, a new design of bounded disturbance observers, and backstepping and Lyapunov’s direct methods. Both state- and output-feedback control designs are addressed. Simulations are included to illustrate the effectiveness of the proposed results.

ADAPTIVE OUTPUT FEEDBACK CONTROL FOR TRAJECTORY TRACKING OF AUV IN WAVE DISTURBANCE CONDITION

This paper develops an adaptive output feedback controller that forces an autonomous underwater vehicle (AUV), named Omni-Directional Intelligent Navigator (ODIN), to track a desired trajectory with bounded errors in wave disturbance condition. An adaptive controller is introduced based on a nonlinear model whose measurable output is corrupted by wave disturbances. Thus an observer is built to reconstruct the full states including wave velocity, wave motion displacement, vehicles velocity, position and rotation angle information which are used in the output feedback controller. Ultimate boundedness of the error signals is shown through Lyapunovs direct method. Finally, simulation studies for ODIN illustrate the effectiveness of the proposed control scheme.

Global tracking control of underactuated ODINs in three-dimensional space

This article presents a method to design controllers that force an underactuated omni-directional intelligent navigator (ODIN), a spherical underwater vehicle, to track a reference trajectory in three-dimensional space. The vehicle under consideration has only four thrusters but six degrees of freedom to be controlled. Motivated by the vehicle's steering practice, the roll and pitch angles regarded as virtual controls plus four actual control forces provided by the thrusters are used to force the position and yaw angle of the vehicle to globally and asymptotically track their reference trajectories. The control design is based on the one-step ahead backstepping method and Lyapunov's direct method. A combination of Euler angles and unit-quaternion for the attitude representation of the vehicle is used to obtain global tracking control results. Simulations illustrate the results.

시험용 자율 무인 잠수정, ODIN-III의 새로운 시스템 소프트웨어 구조의 설계와 구현 및 실험

As underwater robotic vehicles (URVs) become attractive for more sophisticated underwater tasks, the demand of high performance in terms of accuracy and dexterity has been increased. An autonomous underwater robotic vehicle, ODIN (Omni-Directional Intelligent Navigator) was designed and built at the Autonomous Systems Laboratory of the University of Hawaii in 1991. Since 1991, various studies were conducted on ODIN and have contributed to the advancement in underwater robotics. Its refurbished model ODIN II was based on VxWorks in VMEbus. Recently, ODIN was born again as a PC based system, ODIN III with unique features such as new vehicle system software architecture with an objective-oriented concept, a graphical user interface, and an independent and modular structure using a Dynamic Linking Library (DLL) based on the Windows operating system. ODIN III software architecture offers an ideal environment where various studies for advanced URV technology can be conducted. This paper describes software architecture of ODIN III and presents initial experimental results of fine motion control on ODIN III.

A global output-feedback controller for stabilization and tracking of underactuated ODIN: A spherical underwater vehicle

This paper presents a method to design an output-feedback controller that simultaneously solves global asymptotic stabilization and tracking of an underactuated omni-directional intelligent navigator—a spherical underwater vehicle moving in a horizontal plane (i.e. at a constant depth). The vehicle does not have a sway actuator and has only position and orientation measurements available. The control development is based on Lyapunov's direct method, backstepping technique and use of interconnected structure of the vehicle dynamics. Numerical simulations demonstrate the results.

Adaptive control of an autonomous underwater vehicle: experimental results on ODIN

This paper presents a six-degrees-of-freedom controller for autonomous underwater vehicles. The control algorithm is adaptive in the dynamic parameters that are poorly known and time-varying in the underwater environment. Moreover, the proposed control law adopts quaternions to represent attitude errors, and thus avoids representation singularities that occur when using instead Euler angles description of the orientation. The adaptive controller has been successfully implemented and experimentally validated on omnidirectional intelligent navigator (ODIN), an autonomous underwater vehicle that has been designed and built at the University of Hawaii. The experimental results demonstrate the good performance of the proposed controller within the constraints of the sensory system.

Fault-tolerant system design of an autonomous underwater vehicle ODIN: An experimental study

This paper describes the design and implementation of a fault-tolerant system for Omni-Directional Intelligent Navigator (ODIN), a six-degree-of-freedom autonomous underwater vehicle (AUV) designed at the University of Hawaii. A fault-tolerant system consists of three areas: fault detection, fault isolation and fault accommodation. Each area is described, and methods discussed in the literaturearebriefly reviewed. The presented design focuses on the thruster (or actuator) and sensor system failures in an AUV. Experimental results show that the presented approach is practical and effective when tolerable failures in actuators and sensors occur. This methodology and concept can be extended to fault-tolerant system design for various AUVs with hardware redundancy.

Experimental study on a learning control system with bound estimation for underwater robots

Underwater robotic vehicles (URVs) have become an important tool for numerous underwater tasks due to their greater speed, endurance, depth capability, and a higher factor of safety than human divers. However, most vehicle control system designs are based on simplified vehicle models and often result in poor vehicle performance due to the nonlinear and time-varying vehicle dynamics having parameter uncertainties. Conventional proportional-integral-derivative (PID) type controllers cannot provide good performance without fine-tuning the controller gains and may fail for sudden changes in the vehicle dynamics and its environment. Conventional adaptive control systems based on parameter adaptation techniques also fail in the presence of unmodeled dynamics. This paper describes a new vehicle control system using the bound estimation techniques, capable of learning, and adapting to changes in the vehicle dynamics and parameters. The control system was extensively “wet-tested” on the Omni-Directional Intelligent Navigator (ODIN)-a six degree-of-freedom, experimental underwater vehicle developed at the Autonomous Systems Laboratory, and its performance was compared with the performance of a conventional linear control system. The results showed the controller's ability to provide good performance in the presence of unpredictable changes in the vehicle dynamics and its environment, and it's capabilities of learning and adapting.

Development of the Omni Directional Intelligent Navigator

The Autonomous Systems Laboratory is in the midst of developing an advanced underwater robotic technology test platform. The platform consists of the Omni-Directional Intelligent Navigator (ODIN) and the Integrated Graphic Workstation (IGW). ODIN is a six degree-of-freedom (dof) underwater vehicle with dual operational modes (autonomous and tethered) and a single dof mechanical manipulator. IGW is a real-time, 3-dimensional graphic monitoring, testing, and evaluation workstation. This paper presents ODIN's mechanical and electrical specifications; its vehicle dynamics and depth control system; its recent simulation and experimental results; and IGW's specifications. >