Energy-efficient optimal thrust allocation for spherical underwater robot

In this paper, a spherical underwater robot is proposed that uses six degree of freedom thrust allocator to determine the magnitude and the direction of thrust required for each water-jetted bilge pump thruster to create force and moment equilibrium. However, in order to ensure safe operation of the underwater robot it is equipped with redundant thruster configuration and therefore is over-actuated. Therefore, the choice of a particular solution for thrust allocation is found using an optimization process. In this work, the thrust allocation problem is formulated as an optimization problem, with an objective to minimize the total power consumption of the spherical underwater robot. A set of all physically realizable surge, sway and heave force for the i <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">th</sup> thruster is called as its Attainable Thrust Region (ATR). Since the thrust force produced by each thruster is restricted to its ATR, the power consumption of underwater robot is determined by establishing a relationship between the power consumption and the thrust of an individual bilge pump. The formulated optimal thrust allocation problem is solved using Mincon (Sequential Quadratic Programming) and GA (Genetic Algorithm) optimization algorithm. The percentage savings in total power consumption for thruster system using the GA as compared to Mincon method is 33.82 %.

Considering the complicated disturbance in underwater circumstance, usually it is difficult to solve the control problem when the robot changes its motion state or it is subject to ocean currents, its performance deteriorates since the fixed set of parameters is no longer valid for the new conditions. Thus, in this paper, an auto-tune PID (Proportional + Integral + Derivative)-like controller based on Neural Networks is applied to our amphibious spherical underwater robot, which has a great advantage on processing online for the robot due to their nonlinear dynamics. The Neural Networks (NN) plays the role of automatically estimating the suitable set of PID gains that achieves stability of the system. The NN adjusts online the controller gains that attain the smaller position tracking error. The performance of the NN-based controller is investigated in ADAMS and MATLAB cooperative simulation. The velocity of the spherical robot can be controlled to precisely track desired trajectory in body-fixed coordinate system. Additionally, real time experiments on our underwater spherical robot are conducted to show the effectiveness of the algorithm.

Aiming at multi robot cooperation application requirements of our small-scaled underwater spherical robots, a cooperative formation control system with static and dynamic target rounding up was proposed and studied in this paper. Considering the complex underwater environment and kinematic modeling of the robot, a simplified kinematic model of underwater spherical robot with horizontal and vertical motion was established. Given the environmental disturbances in practical underwater scenarios, an adaptive control algorithm was designed to control the underwater spherical robot, which has good robustness and adaptability. To handle the application requirement of static and dynamic target rounding up with multi robots, the path planning strategy of multi robot was proposed, the modeling of static and dynamic target rounding up was analyzed and optimized, and a controller based on linear quadratic regulator method was also designed to realize static/dynamic target rounding up with multi robots. In addition, underwater target rounding up experiments with two or three spherical robots were conducted to test the feasibility and performance of the proposed formation control system, and the experimental results confirmed the validity of the proposed system. This study may inspire future underwater multi robot cooperation that have properties of high efficiency, wide range and multi tasks and has low environmental interference of aquatic environments.

Although the spherical underwater robot has the advantage of 0 radius for the turning locomotion, a variable radius of turning locomotion is also necessary for the path planning and obstacle avoidance of an underwater robot. This paper focused on the turning locomotion with variable radius for the forthgeneration spherical underwater robot (SUR IV) with the hybrid propulsion device. The hybrid propulsion device could be controlled by PWM signals to modify the thrust and linear velocity. The motion state of the turning locomotion was developed in different radius. The centripetal force of curve motion is also analyzed by Newton's first law. The relationship between the centripetal force and turning radius was proposed. In order to verify the turning locomotion with different turning radius, the experiment was carried out in the swimming pool. The experimental results show that the change of the turning radius can be achieved by adjusting the control input PWM signal of the main thruster and the assist thruster.

Dynamic Positioning simulations of a Thrust Allocation Algorithm considering Hydrodynamic Interactions

\n The Dynamic Positioning (DP) System is responsible for the station keeping of vessels in several offshore operations. The forces required by the DP System are distributed among the available thrusters by a thrust allocation algorithm which should be accurate, efficient and robust. This means that the effective forces match the required forces while power consumption is minimized. Additionally, in case of impossibility of generating the required forces the heading of the vessel is maintained to avoid increasing environmental forces. To accurately generate the required forces, the physical limitations of the thrusters and the hydrodynamic interactions must be considered. The hydrodynamic interactions are consistently modelled to accommodate the following typical effects: thruster-hull, thruster-current and thruster-thruster interaction. The result of this modeling is a nonlinear optimization problem, which is solved using the Sequential Quadratic Programming (SQP) algorithm with slack variables. The DP simulation carried out show that by considering the hydrodynamic interactions on thrust allocation the overall performance (controllability and power consumption) of the DP system is improved.\n

This research aims to improve the collaboration ability and stability of the Spherical Underwater Robots (SUR III). According to our previous researches in last few years, the SURIII has no control stability module. This paper designed a new torque gyro control and PID control devoted to improve the stability of SUR III. In this new system, we used a gyro sensor and PID control to design a closed-loop control module to perform terrestrial underwater efficiently. Regarding the spherical robot mechanical structure and dynamic model, the robot control module is designed, and set up to complete underwater experiments. In the underwater experiment, the SUR III can stability motion. A certain offset occurs of SUR III under the disturbance of the wind. After the adjustment of the balance control module, the SUR III balance is quickly restored. In addition, it is certainly worth analyzing the underwater motion to evaluate the performance of the robot stability motion.

Underwater target acquisition and identification performed by manipulators having broad application prospects and value in the field of marine development. Conventional manipulators are too heavy to be used for small target objects and unsuitable for shallow sea working. In this paper, a bio-inspired Father–Son Underwater Robot System (FURS) is designed for underwater target object image acquisition and identification. Our spherical underwater robot (SUR), as the father underwater robot of the FURS, has the ability of strong dynamic balance and good maneuverability, can realize approach the target area quickly, and then cruise and surround the target object. A coiling mechanism was installed on SUR for the recycling and release of the son underwater robot. A Salamandra-inspired son underwater robot is used as the manipulator of the FURS, which is connected to the spherical underwater robot by a tether. The son underwater robot has multiple degrees of freedom and realizes both swimming and walking movement modes. The son underwater robot can move to underwater target objects. The vision system is installed to enable the FURS to acquire the image information of the target object with the aid of the camera, and also to identify the target object. Finally, verification experiments are conducted in an indoor water tank and outdoor swimming pool conditions to verify the effectiveness of the proposed in this paper.

A Gauss pseudospectral method is proposed in this study to solve the optimal trajectory-planning problem for satellite rapid large-angle maneuvers. In order to meet the requirement of rapid maneuver capability of agile small satellites, Single Gimbal Control Moment Gyros (SGCMGs) are adopted as the actuators for the attitude control systems (ACS). Because the singularity problem always exists for SGCMGs during the large-angle maneuvering of the satellites, a trajectory optimization method for the gimbal rates is developed based on the Gauss pseudospectral method. This method satisfies the control requirement of satellite rapid maneuvers and evades the singularity problem of SGCMGs. The method treats the large-angle maneuver problem as an optimization problem, which meets the boundary condition and a series of the physical constraints including the gimbal angle constraint, the gimbal rates constraint, the singularity index constraint, and some other performance criteria. This optimization problem is discretized as a nonlinear programming problem by the Gauss pseudospectral method. The optimal nonsingularity gimbal angle trajectory is obtained by the sequence of quadratic programming (SQP). This approach avoids the difficulties in solving the boundary value problem. The simulations reveal that the Gauss pseudospectral method effectively plans an optimal trajectory and satisfies all the constraints within a short time.

Direct optimal control methods first discretize a continuous-time Optimal Control Problem (OCP) and then solve the resulting Nonlinear Program (NLP). Sequential Quadratic Programming (SQP) is a popular family of algorithms to solve this finite dimensional optimization problem. In the specific case of a least squares cost, the Generalized Gauss-Newton (GGN) method is a popular approach which works very well under some assumptions. This paper proposes a Sequential Convex Quadratic Programming (SCQP) scheme which exploits additional convexities in the NLP in order to generalize the GGN algorithm, possibly extend its applicability and improve its local convergence. These properties are studied in detail for the proposed SCQP algorithm, which will be compared to the classical GGN method using a numerical case study of the optimal control of an inverted pendulum.

Although there are several well -known methods such as RCWA, FMM, for analyzing the diffraction properties of gratings, design of these optical elements with specified spectral properties is commonly a challenging problem. It is relatively not easy for the researchers to design narrow line-with diffraction filters based on guided mode resonance phenomenon with common diffraction algorithm. Simulated Annealing (SA) method is evolutionary, robust technique that has been widely utilized to design optical diffraction components. This method is inspired by the physical process of heating and controlled cooling of metal material to increase the size of its crystals and reduce their defects. The most distinctive features of this method lie in its powerful ability of convergence towards the global minimum in a reasonable computation time and the independence of the initial parameter values. In this paper, first, the physical basis of SA and its mathematical realization are introduced. Then, a Guided-Mode Resonant Grating (GMRG) filters with single layer is designed by using SA algorithm. The central wavelength of GMRG filter is locked at 532nm and its line-width is fixed at 1nm. The plane wave light radiates the grating from air cover with normal incidence. The optimized parameters are refractive indices and thicknesses of high and low material of grating, other parameters are grating period and fill factor of the grating. It is shown from our calculation that an excellent reflection spectrum with narrow line-width, high peak and low sideband can be obtained after optimizing the grating parameters. Next, a double layered GMRG filter with line-width of 4nm, which is relatively easy fabrication in experiment, is designed at central wavelength of 1064nm. The optimized parameters are grating period, groove depth, refractive index of waveguide layer and fill factor respectively. The grating substrate and waveguide layer are Sio2 and Hfo2 respectively, the grating structure is directly etched on the waveguide layer. The above grating values should be included in reasonable ranges in consideration of grating fabrication in our experiment condition. It is demonstrated from the calculations with the parameters obtained from SA optimization algorithm that the peak diffraction efficiency is more than 99% at central wavelength 1064nm and the sideband reflection is depressed at the level bellow 5% in a large wavelength range. Moreover, the parameters of a triple layer GMRG filter structure are also provided with this powerful method. Meanwhile, the results found by SA method are compared with RCWA theory.

Numerical analysis of circular straight mufflers equipped with three chambers at high-order-modes

This article presents a method named pseudo-inverse to solve the optimal thrust allocation of dynamic positioning (DP) system, proposes to optimally determine the azimuth angle of thrusters instead of man-control or semi-auto control, and combines with the pseudo-inverse methods to get the optimal solutions for dynamic positioning control system. It is able to greatly reduce the risk of manual mode. Three different kinds of modes are proposed and detailedly illuminated, and can be used to solve much more complex nonlinear constraint problems, such as typical forbidden vector boundary. Several illustrative examples are provided to demonstrate the effectiveness and correctness of the proposed thrust allocation modes.

A new SA (simulated annealing) method is presented for the design of longitudinal shim coils for NMR (nuclear magnetic resonance) equipment. First, AGL (adaptive Gauss-Lobatto) quadrature used by the traditional SA method is analyzed. Two Kinds of complete elliptic integrals are introduced to integrate the spatial magnetic field, which increase the computing speed by 13.3 times. Then, the System energy calculation is extended to the field of the z-axis. The results illustrate that the coil-set efficiency designed by the new SA method is 15% higher than that of the traditional one, and the field inhomogeneity is reduced frm 1.20% to 0.49%. Finally, a prototype of coil assembly for NMR rock-core analyzer is built, and the experimental results are in good agreement with the theoretically calculated results. * Supported by the National Key Technologies Research and Development Program of China (Grant No. 001BA210A03), and Key Project of 2005 Beijing Science and Technology Programme(Grant No. D0205002...

Thrust allocation (TA) is a vital part of the dynamic positioning (DP) system of vessels equipped with azimuth thrusters. It determines the control input of each thruster device according to the control command generalized by the DP controller, which has a great impact on the control accuracy, stability, and flexibility of marine operation. In order to solve the TA problem, a multi-agent distributed optimization method based on distributed TA quadratic programming (QP) model in Cartesian coordinates is proposed in this paper. The proposed method considers the power consumption, the mechanical wear, the mechanical constraints, and the singularity from the perspective of multi-agent. The simulation examples show that the method proposed in this paper can realize optimal TA effectively without error.