Quoc Dong Hoang

Bio: Quoc Dong Hoang is an academic researcher from Vietnam Maritime University. The author has contributed to research in topics: Control theory (sociology) & Lyapunov function. The author has an hindex of 1, co-authored 1 publications receiving 20 citations.

Robust Position Control of an Over-actuated Underwater Vehicle under Model Uncertainties and Ocean Current Effects Using Dynamic Sliding Mode Surface and Optimal Allocation Control.

Abstract: Underwater vehicles (UVs) are subjected to various environmental disturbances due to ocean currents, propulsion systems, and un-modeled disturbances. In practice, it is very challenging to design a control system to maintain UVs stayed at the desired static position permanently under these conditions. Therefore, in this study, a nonlinear dynamics and robust positioning control of the over-actuated autonomous underwater vehicle (AUV) under the effects of ocean current and model uncertainties are presented. First, a motion equation of the over-actuated AUV under the effects of ocean current disturbances is established, and a trajectory generation of the over-actuated AUV heading angle is constructed based on the line of sight (LOS) algorithm. Second, a dynamic positioning (DP) control system based on motion control and an allocation control is proposed. For this, motion control of the over-actuated AUV based on the dynamic sliding mode control (DSMC) theory is adopted to improve the system robustness under the effects of the ocean current and model uncertainties. In addition, the stability of the system is proved based on Lyapunov criteria. Then, using the generalized forces generated from the motion control module, two different methods for optimal allocation control module: the least square (LS) method and quadratic programming (QP) method are developed to distribute a proper thrust to each thruster of the over-actuated AUV. Simulation studies are conducted to examine the effectiveness and robustness of the proposed DP controller. The results show that the proposed DP controller using the QP algorithm provides higher stability with smaller steady-state error and stronger robustness.

An Efficient Adaptive Fuzzy Hierarchical Sliding Mode Control Strategy for 6 Degrees of Freedom Overhead Crane

Abstract: The paper proposes a new approach to efficiently control a three-dimensional overhead crane with six degrees of freedom (DoF). In addition to five usual output variables including three positions of the trolley, bridge and pulley and two swing angles of the hoisting cable, it is proposed to consider elasticity of the hoisting cable, which causes oscillation in the cable direction. That is, there exists $6^{th}$ under-actuated output in the crane system. To design an efficient controller for the six-DoF crane, it first employs the hierarchical sliding mode control approach, which not only guarantees stability but also minimizes sway and oscillation of the overhead crane when it transports a payload to desired location. Moreover, the unknown and uncertain parameters of the system caused by its actuator nonlinearity and external disturbances are adaptively estimated and inferred by utilizing the fuzzy inference rule mechanism, which results in efficient operations of the crane in real time. More importantly, stabilization of the crane controlled by the proposed algorithm is theoretically proved by the use of the Lyapunov function. The proposed control approach was implemented in the synthetic environment for the extensive evaluation, where the obtained results demonstrate its effectiveness.

Vertical Profile Diving and Floating Motion Control of the Underwater Glider Based on Fuzzy Adaptive LADRC Algorithm

Abstract: The underwater glider is a kind of novel invention that has been proven to be perfect for long-duration, wide-range marine environmental monitoring tasks. It is controlled by changing the buoyancy and adjusting the posture. For precise control of the underwater glider’s trajectory, a fuzzy adaptive linear active disturbance rejection control (LADRC) is designed in this paper. This controller allows the glider to dive to a predetermined depth precisely and float at a specific depth. In addition, the controller takes some important factors into account, such as model uncertainty, environmental disturbances, and the limited dynamic output of the actual mechanical actuator. Finally, simulation results show the superiority of this fuzzy adaptive LADRC control method. Particularly, when the underwater glider was controlled to dive 100 m at a predetermined attitude angle θ = −1 rad, the maximum overshoot of FLADRC is reduced by 75.1%, 56.6% relative to PID, LADRC, respectively.

Radial Basis Function Neural Network Sliding Mode Control for Ship Path Following Based on Position Prediction

Abstract: In the process of ship navigation, due to the characteristics of large inertia and large time delay, overshoot can easily occur in the process of path following. Once the ship deviates from the waypoint, it is prone to grounding and collision. Considering this problem, a sliding mode control algorithm based on position prediction using the radial basis function (RBF) neural network is proposed. The desired heading angle is designed according to a backstepping algorithm. The hyperbolic tangent function is used to design the sliding surface, and the course is controlled by sliding mode control. The second-order Taylor expansion is used to predict the future position, the current error and future error functions are constructed, and the total errors are fed back to the desired heading angle. In the sliding mode control system, the RBF neural network is used to approximate the total unknown term, and a velocity observer is introduced to obtain the surge velocity and sway velocity. To verify the effectiveness of the algorithm, the mathematical model group (MMG) model is used for simulation. The simulation results show the effectiveness and superiority of the designed controller. Therefore, the RBF neural network sliding mode controller based on predicted position has robustness for ship path following.

Adaptive Nonsingular Fast Terminal Sliding Mode Tracking Control for an Underwater Vehicle-Manipulator System with Extended State Observer

Abstract: An adaptive nonsingular fast terminal sliding mode control scheme with extended state observer (ESO) is proposed for the trajectory tracking of an underwater vehicle-manipulator system (UVMS), where the system is subjected to the lumped disturbances associating with both parameter uncertainties and external disturbances. The inverse kinematics for the system is obtained by the quaternion-based closed-loop inverse kinematic algorithm. The proposed controller consists of the modified nonsingular fast terminal sliding mode surface (NFTSMS) and ESO, and the adaptive control law. The utilized NFTSMS can ensure the fast convergence of the tracking errors, together with avoiding the singularity in the derivation. According to the ESO method, the estimation error of the lumped disturbance vector can realize the fixed-time convergence to the origin, along with replacing the sign function with the saturation function to attenuate the chattering. A continuous fractional PI-type robust term with adaptive laws is introduced to handle the unknown bound of the estimation error. The closed-loop system is proved to be asymptotically stable by the Lyapunov theory. Simulations are performed on a ten degree-of-freedom UVMS under four different strategies. Comparative simulation results show that the proposed controller can achieve better tracking performance and stronger robustness of the disturbance rejection.

Double-Loop Sliding Mode Controller with An Ocean Current Observer for the Trajectory Tracking of ROV

Abstract: To solve the trajectory tracking problem of insufficient response and the large tracking error of remotely operated vehicles (ROVs) under the interference of large ocean currents, this paper proposes a double-loop sliding mode controller with an ocean current observer. The designed controller consisted of an outer-loop controller (the position controller) and an inner-loop controller (the velocity controller): the outer controller was designed by the position error, and a reference velocity was created for the inner loop to achieve accurate positioning and attitude tracking. The reference control input was treated as a new target to design the inner-loop controller, enabling the ROV to achieve accurate reference velocity tracking. Based on the theoretical idea of active disturbance rejection control, a kinematic equation-based ocean current observer was designed to estimate and compensate for large unknown currents to ensure accurate trajectory tracking performance under large currents. The simulation results proved that the double-loop sliding-mode control scheme with an ocean current observer always showed good tracking performance, demonstrating the excellent control performance and high robustness of the scheme. Compared with the high-complexity control schemes such as neural network-based PID control or fuzzy sliding mode control, it effectively improves the robustness to ocean current disturbances without increasing the computational effort excessively, and is more practical in ROV systems with limited computational power.

Modified Vector Field Path-Following Control System for an Underactuated Autonomous Surface Ship Model in the Presence of Static Obstacles

Abstract: A modified path-following control system using the vector field method for an underactuated autonomous surface ship model is proposed in the presence of static obstacles. With this integrated system, autonomous ships are capable of following the predefined path, while avoiding the obstacles automatically. It is different from the methods in most published papers, which usually study path-following and obstacle collision avoidance, separately. This paper considers the coupled path following and collision avoidance task as a whole. Meanwhile, the paper also shows the heading control design method in the presence of static obstacles. To obtain a strong stability property, a nonlinear autopilot is designed based on the manoeuvring tests of the free-running ship model. The equilibrium point of the controller is globally exponentially stable. For the guidance system, a novel vector field method was proposed, and the proof shows the coupled guidance and control system is uniform semi-global exponentially stable (USGES). To prevent the obstacles near the predefined path, the proposed guidance law is augmented by integrating the repelling field of obstacles so that it can control the ship travel toward the predefined path through the obstacles safely. The repelling field function is given considering the obstacle shape and collision risk using the velocity obstacle (VO) algorithm. The simulations and ship model test were performed to validate the integrated system of autonomous ships.