In this paper, a highly non-linear model of an autonomous underwater vehicle (AUV) with six degrees-of-freedom is linearized to yaw (horizontal) and pitch (vertical) planes under several working conditions. For controlling steering and diving planes, an uncertainty disturbance estimator based sliding mode control (UDE-SMC) scheme is proposed and designed separately as single-input single-output controllers for horizontal and vertical plane dynamics of an AUV system. The proposed UDE-SMC scheme is effective in compensating the uncertainties in the hydrodynamic parameters of the vehicle and rejecting unpredictable disturbances due to ocean currents. The UDE-SMC consists of an equivalent and estimated lumped uncertain terms to suppress the effect of external disturbances and parametric uncertainties acting on the vehicle dynamics. Numerical simulations were performed to validate the UDE-SMC.

Uncertainty and disturbance estimator based sliding mode control of an autonomous underwater vehicle

Aiming to improve the performance of motion for autonomous underwater vehicle (AUV), a fractional-order PID strategy is proposed. It is a more generalized form for the conventional integer-order PID controller, keeping its simplicity and utilizing the generalized derivative and integral control actions. The fractional-order PID controller has been successfully applied to heading control, diving control and path-following system of AUV on sea trial. In addition, the fractional-order closed-loop system has proven to be stable. By comparing simulations and experiments, the satisfactory performance, such as overshoot, settling time and steady-state error, has been achieved. The cloud-model-based quantum genetic algorithm (CQGA) is employed to tune coefficients of fractional-order PID controller. The quantum bits and quantum superposition states avoid the pressure of selection and maintain the diversity of population in chromosome coding. Due to the randomness and stability tendency of cloud droplets, the cloud crossover operator and the cloud mutation operator can effectively overcome the shortcomings of premature and slow searching speed. Numerical simulations show that the CQGA is more efficient to find the optimal coefficients of fractional-order PID controller than GA.

/pdf/fractional-order-pid-motion-control-for-auv-using-cloud-1c4j1oz8or.pdf

Fractional-Order PID Motion Control for AUV Using Cloud-Model-Based Quantum Genetic Algorithm

In this article, an adaptive backstepping control is proposed for multi-input and multi-output nonlinear underwater glider systems. The developed method is established on the basis of the state-spa...

https://journals.sagepub.com/doi/pdf/10.1177/1729881416669484

Nonlinear multiple-input-multiple-output adaptive backstepping control of underwater glider systems

In this research, generation of a short and smooth path in three-dimensional space with obstacles for guiding an Unmanned Underwater Vehicle (UUV) without collision is investigated. This is done by utilizing spline technique, in which the spline control points positions are determined by Imperialist Competitive Algorithm (ICA) in three-dimensional space such that the shortest possible path from the starting point to the target point without colliding with obstacles is achieved. Furthermore, for guiding the UUV in the generated path, an Interval Type-2 Fuzzy Logic Controller (IT2FLC), the coefficients of which are optimized by considering an objective function that includes quadratic terms of the input forces and state error of the system, is used. Selecting such objective function reduces the control error and also the force applied to the UUV, which consequently leads to reduction of energy consumption. Therefore, by using a special method, desired signals of UUV state are obtained from generated three-dimensional optimal path such that tracking these signals by the controller leads to the tracking of this path by UUV. In this paper, the dynamical model of the UUV, entitled as "mUUV-WJ-1" , is derived and its hydrodynamic coefficients are calculated by CFD in order to be used in the simulations. For simulation by the method presented in this study, three environments with different obstacles are intended in order to check the performance of the IT2FLC controller in generating optimal paths for guiding the UUV. In this article, in addition to ICA, Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) are also used for generation of the paths and the results are compared with each other. The results show the appropriate performance of ICA rather than ABC and PSO. Moreover, to evaluate the performance of the IT2FLC, optimal Type-1 Fuzzy Logic Controller (T1FLC) and Proportional Integrator Differentiator (PID) controller are designed and applied to the UUV and compared with each other. The simulation results show the superiority of the IT2FLC than the other two controllers.

/pdf/path-planning-for-unmanned-underwater-vehicle-in-3d-space-4kzhho6qj4.pdf

Path planning for unmanned underwater vehicle in 3d space with obstacles using spline-imperialist competitive algorithm and optimal interval type-2 fuzzy logic controller

Underwater Gliders (UGs) are a type of Autonomous Underwater Vehicle (AUV) that uses buoyancy engines, an energy efficient locomotion, primarily for oceanography. In this paper, control strategies for existing underwater gliders are reviewed. A total of 50 papers indexed by Scopus with keywords control and underwater gliders were reviewed from 1989 to 2014. The majority of gliders use classical controllers, which cannot dynamically compensate for un-modeled hydrodynamic forces and unknown variations in water current and wind. With increasing operational depths and larger payloads, control strategies will become an increasingly important aspect for these gliders. Control strategies implemented in underwater gliders were reviewed and alternative control strategies are proposed.

Underwater gliders control strategies: A review

This paper presents an adaptive fuzzy logic based controller for the depth control of an Autonomous Underwater Vehicle(AUV). The kinematic and dynamic motion of an AUV is described using six degree of freedom differential equations of motion using bodyand earth-fixed frame of references. Due to hydrodynamic forces, these equations are complex, non-linear and highly coupled therefore are impractical for use in controller design. In practice, system is commonly decomposed into three non-interactive systems such as diving subsystem, steering subsystem and speed subsystem. In this study a reduced order model was derived for diving system using depth plane dynamics and a suitable dual loop control strategy is formulated by synthesizing fuzzy logic based control in series with a phase lead dynamic compensator to achieve the desired set point tracking and reasonably good performance objectives under variety of disturbances encountered in oceanic environments. The obvious benefits of this type of approach lies in the simplicity of the scheme compared to the conventional deterministic systems and easy implementation for real time control of the Autonomous Underwater Vehicles. The proposed fuzzy logic based controller accepts deterministic information, the depth of the vehicle as input and achieves imprecise reasoning and de-fuzzification to generate a deterministic control output which manipulates the pitch angle and hence the depth of the vehicle. The simulated results clearly demonstrate the efficacy of this approach as compared to the conventional PID controller designed and tuned using Ziegler-Nichols scheme.

Fuzzy logic based depth control of an autonomous underwater vehicle

This paper presents a robust H-infinity based control methodology for an Autonomous Underwater Vehicle(AUV). The kinematics and dynamics of an AUV is described using six degree of freedom differential equations of motion using body and earth-fixed frame of references. Due to hydrodynamic forces, these equations are highly coupled and non-linear. From the practical point of view it is essential to consider a reduced order model for efficient controller design. Hence the system is commonly subdivided into smaller subsystems, like depth, steering (or yawing) and speed subsystems, which are considered to be mutually non-interactive from the controller design perspective. In this study a reduced order model was derived using the depth plane dynamics of the vehicle. The working environment of an AUV is vastly uncertain due to varying environmental conditions, thereby demanding a robust controller which has the ability to adapt to these uncertainties and provide stabilizing effect irrespective of the change in the surrounding conditions. The proposed H-infinity controller takes into account the uncertainties in the hydrodynamic parameters which arise due to changing operating conditions and provides suitable control action for desired set point tracking as well as disturbance rejection. The altitude of the vehicle is strongly dependent on the pitch angle, and the controller presented here takes care of both the pitch and depth plane dynamics. The mixed sensitivity approach for H-infinity controller design is followed, and the efficacy of the controller is compared with Linear Quadratic Gaussian(LQG) controller and the Mixed H2/H-infinity controller. The controller design and simulation has been done in Matlab, and the simulated results provide satisfactory results, for disturbance rejection and set point tracking for the H-infinity controller in presence of hydrodynamic parametric uncertainties.

A robust H-infinity based depth control of an autonomous underwater vehicle

This paper presents a practical implementation model for simulating the pitching and yawing motions of an autonomous underwater vehicle (AUV) and its consequent control using an ARM based SBC Friendly ARM mini2440 A rotary encoder and adxl303 triple axis accelerometer has been used to measure the position and acceleration respectively The emphasis of this paper is given on the interfacing of the sensors with Friendly ARM mini2440 and the resultant control algorithm implemented on the embedded platform to control the designed testbench The control algorithm implemented is PID control It is to be noted that the entire project was done to study the movements of an underwater vehicle and the ensuing control strategies and the prototype developed fulfills those criteria

Anirban Nag

Papers

Fuzzy logic based depth control of an autonomous underwater vehicle

A robust H-infinity based depth control of an autonomous underwater vehicle

A Practical Prototype Development to Simulate and Control the Movements of an AUV using ARM9 based Microcontroller

Degenerate Cases in the Inverse Kinematics Problem of a General 6R Serial Robot