Genetic algorithm based intelligent station-keeping for spherical underwater robot

In this paper, a spherical underwater robot uses optimal 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. The power consumption of underwater robot depends on the thrust generated by each bilge pump. The relationship between the power consumption and the thrust of the bilge pump is established using experimental data. The formulated optimal thrust allocation problem is solved using Mincon (Sequential Quadratic Programming) and SA (Simulated Annealing) optimization algorithm. The percentage savings in total power consumption for thruster system using the SA method as compared to Mincon method is 50.6 %.

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its motion state or it is subject to ocean currents, its performance deteriorates since the fixed set of parameters is no longer valid for the new conditions.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.

In the navigation of underwater robots, large ocean current disturbance often causes significant tracking errors. To better resist ocean current disturbance, the hydrodynamic characteristics of the spherical underwater robot are studied, and a model predictive control strategy based on adaptive model parameters is proposed, according to these characteristics. Firstly, the hydrodynamic characteristics of the robot under static water and constant flow disturbance were obtained and analyzed by the computational fluid dynamics method. Then, the dynamic models of the robot under different disturbances could be calculated from the data obtained, based on the least square method. Finally, an adaptive model predictive control (AMPC) strategy, with an ocean current observer, was designed, based on the dynamic models. When the current disturbance velocity was twice the robot velocity, the proposed strategy reduced the tracking error by 39% and 42% in X and Y directions, respectively. In addition, the hydrodynamic characteristics were verified by experiments.

Underwater robots have been promoted a significant interest in monitoring the marine environment. In some complex situation, robots sometimes need to keep moving fast, sometimes need to keep low speed and low noise. To address this issue, a novel spherical underwater robot (SUR IV) with hybrid propulsion devices including vectored water-jet and propeller thrusters is proposed in this paper. The diversity of the movement modes is also proposed for the different targets as remote or hover and general or silent. To analyze the hydrodynamic characteristics of the hybrid thruster, the computational fluid dynamics simulation is calculated in ANSYS CFX by using the multi-reference frame method. The simulation results show the interaction between the propeller and water-jet thruster. The thrust experiment to evaluate the performance of the improved hybrid thruster is also conducted. The maximum thrust of the hybrid thruster is increased 2.27 times than before. In addition, a noise comparison experiment is conducted to verify the low noise of the water-jet thruster. Finally, the 3 DoF motions which include the surge, heave and yaw for the SUR IV were carried out in the swimming pool. The improvement of the overall robot is assessed by the experimental results.

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.

Recently, the semiconductor manufacturing industry has exhibited not only fast growth, but intense power consumption. Consequently, reducing power consumption is critical for running reliability. A view of literature reveals that the power consumption of facility system is 56.6 % in the fabs. Among all facility systems, chiller plants are the largest energy users, consuming 27.2 % of the total power consumption. Therefore, saving power consumption for chiller plants involves a considerable economic benefit. In addition, cooling the water temperature further improves the efficiency of chillers. Hence, this report analyzes the optimal temperature between the chiller and cooling tower. Currently, controlling the chiller and cooling tower are separate processes, though, in fact, they should not be. This is because the water cooling temperature affects the efficiency of the chiller. Each reduced degree of the chiller condenser temperature reduces the electrical power by approximately 2 % in the cooling tower, in contrast to the chiller. Therefore, the optimal water cooling water temperature must be analyzed. The analysis method in this report is linear regression. First, determine the equations of power consumption for the chiller and cooling tower with variables representing the water cooling temperature, water supply temperature of the chiller, and outdoor loading and wet-bulb temperatures. Second, add the coefficient of the same variable to obtain the total power consumption equation for the chiller and cooling tower. The result shows the relationships of power consumption with water cooling temperature under identical conditions of the water cooling temperature, water supply temperature of chiller, and outdoor loading and wet-bulb temperatures. Finally, use the differential method to determine the optimal water cooling temperature.

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.

On-site study was held to investigate the influences of load factor on power consumption and energy performance of water-cooled air conditioning (WCAC) system. A comprehensive measurement has been conducted to a WCAC plant of a supermall building located in West Java, Indonesia. Hourly and daily power consumption and performance characteristics of the WCAC system at varied load factors for a period of one year were evaluated. Regression analyses were developed to evaluate the influences of load factor on the WCAC power consumption and performance. The WCAC system was found to operate with varied load factor ranging from 70 percent to 100 percent. Power consumption of the system was strongly influenced by the load factor. Power consumption boosted when the power factor increased. The increase of load factor was also found to significantly improve the cooling capacity but reduce the coefficient of performance (COP). The best potential performance of the investigated WCAC system could be obtained at load factor between 70 percent and 85 percent.