T-S 퍼지 모델 기반 메모리 샘플치 제어를 통한 자율 무인 잠수정의 심도 제어

A practical design method is developed for path following and coordinated control of Autonomous Underwater Vehicles (AUVs). Each AUV is modeled by a system with time-varying parameters, unknown nonlinear dynamics and unknown disturbance. A robust adaptive distributed controller is designed for each AUV such that all AUVs ultimately synchronize to the desired paths with required formation. Moreover, these controllers are distributed in the sense that the controller design for each AUV only requires relative state in formation between itself and its neighbors. Finally, a simulation example demonstrates the effectiveness of the control method.

A tethered flight vehicle such as Subzero III can be a reliable test-bed for AUV control techniques provided that the tether effects be removed by feed-forward control. To achieve the composite control idea, a numerical scheme for prediction of tether effects has been proposed and assessed. We argue that the composite control scheme can also be applied to the control of an ROV during the deployment of the umbilical. The H∞ approach has been applied to the design of the autopilots for autonomous underwater vehicles. The autopilots developed have the following features: (1) they have simpler structures than conventional H∞ design and the performance degrada tion caused by the controller order reduction is negligible; (2) rate feedback is applied for heading and depth control to improve tracking performance; (3) the overshoot specification is considered in the design by choosing suitable weighting functions. The results of both nonlinear simulations and water trials in two different tanks show that the autopilots are robust to model uncertainty, external disturbances and varying dynamics of the vehicle and exhibit good tracking performance. Thus the effectiveness of robust control for AUVs appears promising.

The underwater environment severely constrains robotic navigation and communications, making the use of traditional multi-robot control and coordination schemes very difficult. These challenges are exacerbated on a new generation of low-cost autonomous underwater vehicles (AUVs) that lack a Doppler velocity log, acoustic modem, or high-end inertial sensors typically used for underwater robotic navigation and communications.This letter demonstrates multi-robot operations for low-cost AUVs via a novel and user-friendly operating paradigm that allows intuitive command and control of an AUV group. Each vehicle is equipped with a low-power and inexpensive acoustic system for navigation and receipt of operator commands. This system consists of a passive array of hydrophones and a timed acquisition and data processing stack that allows each AUV to self-localize relative to a time-synchronized acoustic beacon. Switching between different operational “modes” on the beacon causes it to broadcast different acoustic signals which, when received by the AUVs, result in the vehicles switching between different autonomous behaviors. These behaviors are defined in a beacon-centric coordinate system using pre-defined parameters unique to each vehicle; as a result, the movement of the beacon itself allows the operator to control the group-wide movement of all vehicles concurrently. This letter presents field experiments with three SandShark AUVs in which operational mode and beacon movement were controlled by an operator. However, by installing the beacon on an autonomous vehicle, this paradigm would provide a method for remote command and control of an arbitrarily large number of miniature, low-cost AUVs, without the need for sophisticated navigational sensors or acoustic modems.

This article presents a design method for the three-dimensional trajectory tracking control of an underactuated autonomous underwater vehicle with unknown current disturbances. To simplify the complexity of the controller and avoid the singular problem induced by initial state constraints, a novel nonlinear backstepping technique based on virtual control variables is employed to design the kinematics and dynamics controllers. The control law is developed by building virtual errors, which can solve the problem of differential explosion in the traditional backstepping. Specifically, an ocean current observer based on the kinematics model is proposed to estimate unknown current disturbances, where the estimation is integrated into the autonomous underwater vehicle kinematics and dynamics equations. The convergence of tracking errors and system stability are proven by using Lyapunov stable theory. Finally, the simulation studies were provided to illustrate the effectiveness and good performance of the above trajectory tracking strategy.

The growing interest in the preservation of environment leads several researchers to investigate the causes behind the high level of \({\text {CO}}_2\) and how to decrease it. This paper, deals with continuous time delay nonlinear systems (TDNS) stability conditions using the Takagi Sugeno Fuzzy Modeling. First a Nonlinear Carbon Dioxide Model is defined and transformed to a corresponding Fuzzy Takagi Sugeno (TS) multi-model. Then, by using the Lyapunov-Krasovskii Functionals (LK-F) and extending some linear time delay systems dependent delay stability technique to TS Fuzzy Modeling, a new relaxed stability conditions involving uncommon free matrices are addressed in Linear Matrix Inequalities (LMI). Finally a numerical simulation is also carried out to support the analytic results and to compare the conservativeness of the proven condition to other existing methods.KeywordsFuzzyTSTime DelayStabilityLK-F.

Describes applications of fuzzy logic to the control of an autonomous underwater vehicle (AUV). One application described here is a fuzzy logic six degree-of-freedom flight control system by the Ocean Voyager, an AUV currently under development. Heading, pitch, and depth are controlled simultaneously by three separate fuzzy logic controllers, each a function of setpoint error and error rate. An additional fuzzily constrained integrator compensates for frictional effects and setpoint error. The fuzzy controllers were tested and show good performance over a range of velocities. Another application described is a docking controller for the Ocean Voyager. This controller enables the AUV to dock with another underwater vehicle. Both moving and stationary targets are allowed. The fuzzy rule base recursively drives the vehicle toward intermediate fuzzy goals that become more precise as the final target is approached. The fuzzy goal approach does not rely on high accuracy maneuvers or waypoints. Docking proceeds as long as the AUV remains in a funnel of acceptable intermediate positions. Performance of the docking controller was tested by simulation. >

This paper is concerned with the security sliding mode-based leader-following control of multiple autonomous unmanned underwater vehicles (AUVs) system subject to stochastic DoS attacks. Firstly, a Bernoulli variable is used to describe the phenomenon of stochastic DoS attacks between controllers and actuators, and the attack probability is known for controller design. Secondly, the closed-loop system is established by taking the integral sliding mode control scheme and stochastic DoS attacks into account. Then, the conditions of stochastic stability for system are given by using the stochastic systems analysis method and the model decomposition technique. In the simulation part, a group of AUVs models is used to verify the validity of the proposed state consensus control scheme. The simulation example shows that all the state can achieve consensus even in presence of randomly launched DoS attack.

This paper describes research on remote monitoring and control of autonomous underwater vehicles (AUVs). This work is part of a larger effort to create autonomous ocean sampling networks (AOSN), a new concept for collecting synoptic oceanographic data. AOSN is based on the operation of small, low cost autonomous underwater vehicles (AUVs) within an array of moorings that provide communication and power-supply nodes. Critical to the realization of AOSN will be the ability to control these assets and monitor the data collection process remotely. During the time in which our AOSN partners have been developing acoustic communications, our laboratory has performed a variety of remote monitoring and control experiments to test different types of network distributed control software. Experimental results are presented for runs in the Charles River in which a radio modem towed on a float was used to monitor and control the vehicle from a workstation on the Internet. In addition, we have used our acoustic navigation system to send simple command messages to an Odyssey vehicle, achieving simultaneous control of multiple AUVs operating in a high current environment in the Haro Strait.

This paper presents an adaptive region tracking control for Autonomous Underwater Vehicle (AUV). The AUV is required to track a moving region to accomplish a given task. The desired target is specified as a region rather than a point so that the control effort used to track the region is minimal. In the applications where the accuracy is of utmost importance, the desired region can be chosen to be small so that the precision is not lost. The desired region can be scaled up or scaled down so that the AUV can adjust its position to suit the applications. A Lyapunov-like function is presented for the stability analysis. Simulation results on AUV with 6 degrees of freedom are presented to demonstrate the effectiveness of the proposed controller.

Design for three-dimensional stabilization control of underactuated autonomous underwater vehicles

In this paper, the problem of simultaneous fault detection and control (SFDC) for an autonomous unmanned underwater vehicle (AUV) is considered. An H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> formulation of the SFDC problem using a dynamic observer is developed. A single module designated as the detector/controller is designed where the detector is a dynamic observer and the controller is a state feedback controller based on the dynamic observer. The detector/controller module produces two signals, namely the detection and the control signals. Sufficient conditions for solvability of the problem are obtained in terms of linear matrix inequality (LMI) feasibility conditions. Simulation results for a Subzero III AUV illustrate the effectiveness of our proposed design methodology.

The Independent Administrative Corporation Japan Agency for Marine-Earth Science and Technology (JAMSTEC) has been developing light-and-small autonomous underwater vehicles (AUV), named “Marine Robot Experimental 1” (“MR-X1”). In this paper, the motion control problem of “MR-X1” is considered. Since the dynamics of “MR-X1” depends upon its own speed, the problem in question becomes a non-linear control problem. A new controller design method using linear matrix inequalities (LMIs) is proposed in order to adapt the problem in question. The algorithm, which gives a solution of a linear matrix inequality (LMI), can adapt to solve numerous LMIs simultaneously. LMIs can be obtained by substituting several speeds into the dynamics of “MR-X1”. The proposed controller, which can be derived from the solution of LMIs, becomes a stabilizing controller for all substituted speeds.

This paper addresses the issue of tracking the output of an activated sludge process using fuzzy integral control. First, the dynamics of the nonlinear process are modeled with a dynamic state space fuzzy model integrating the effect of external disturbances, and then an additional integral state of the output tracking error is introduced to obtain an augmented Takagi-Sugeno (TS) fuzzy model. The TS fuzzy model is able to describe the dynamics of complex nonlinear systems with an excellent degree of accuracy. It is formulated by fuzzy if-then rules which can give local linear representation of the overall nonlinear system. Second, the design of the fuzzy integral control is performed, in which the state feedback gains are obtained by solving linear matrix inequalities (LMI). The objective is to ensure trajectory tracking of an activated sludge process (ASP) by controlling two key variables: the substrate concentration and the level of dissolved oxygen. To assess the performance of the proposed control strategy, a comparative analysis is carried out with a gain scheduling PI (GS-PI) controller. Simulation results are provided to illustrate the effectiveness of the proposed approach. Where, the fuzzy integral control reduces the high energy consumption in water treatment plants.

Reduced order H∞ control of an autonomous underwater vehicle

Path planning and formation control are two of the most significant concepts which can be considered in multi-vehicle systems and particularly in autonomous underwater vehicles (AUVs). The cooperative implementation of complicated commands would lead to desirable results and increase the probability of success in the missions. Due to the nonlinear dynamics and environmental conditions, the cooperative control of AUVs is a challenging topic. The developments in AUV applications demonstrate the significance of research and development in path planning and formation control. Unlike ground or aerial autonomous vehicles, this field of study has not attracted considerable attention and further exploration is required as a result. The present paper reviews the different structures of formation control in AUVs and discusses their advantages and disadvantages. Besides formation control, the cooperative path planning of AUVs along with the limitations specific to the cooperative structure is taken into consideration in the present study. Moreover, avoiding any obstacle collision and preventing any encounter between group members are considered as critical issues in the formation control and cooperative path planning. Some areas are still open to investigation as implied by the technological suggestions, which will facilitate future research. At the end of the article, a simulated sample is given of the triangular formation path planning for AUVs.