Mingyu Fu

Design of dynamic positioning systems using hybrid CMAC-based PID controller for a ship

The ship motion is a type of complicated nonlinear motion. It is very difficult to measure the precise hydrodynamic parameters when the ship is at sea. Moreover, the external disturbance forces coming from wind, waves and water current are changing at any moment. So, it is necessary to study new control techniques, with robust and adaptive properties, to implement precise position for dynamic positioning vessels. PID control law is a good robust and adaptive control law for a type of definite systems that precise modeling can be gotten in mathematics. But PID control results are not satisfactory for complex nonlinear systems such as ship motion. The neural network has self-learning and adapting ability, so we can combine the PID with neural network to build the strong robust and adaptive controller. In this paper, CMAC-based PID controller is studied. The simulation results show that the new control method is effective with strong robust and adaptive capability, and it can be applied to marine dynamic positioning systems.

Amphibious hovercraft course control based on support vector machines adaptive PID

Amphibious hovercraft is very different from conventional surface ships. Its mathematical model perturbs erratically as the change of sailing status and environment. For the nonlinear characteristic, adaptive PID controller based on support vector machines (SVM) is applied in the course control. The SVM is used to identify the system information, which is then linearized to extract the instantaneous linear model. The parameters of PID are turned based on the linear model. The simulation results in harsh environment show that the controller designed achieves high dynamic and steady performances, which brings a new effective method to solve the problem of hovercraft course control.

Research on sliding mode controller with an integral applied to the motion of underwater vehicle

A sliding mode controller with an integral for multi-variables system is devised to control the heading and speed of AUV in this paper. The simulation experiment results show that this scheme gives more robust and can eliminate steady error under disturbances. The accuracy heading and speed control is realized.

Fault-tolerant control of dynamic positioning vessel by means of a virtual thruster

This paper presents a method for on-line reconfiguration of fault-tolerant control to dynamic positioning (DP) vessel by means of a virtual thruster after the occurrence of thruster failures. First, a brief review of the main idea of a virtual actuator is presented. Then a suitable linear state-space model of DP vessel is derived which consists of motions in 3 DOF. A virtual thruster design is finished which combines with virtual actuator and DP vessel model. The reconfiguration block of virtual thruster generates suitable inputs for the faulty vessel based on the output of the nominal controllers. At last, the feasible and effective of this method are demonstrated by a simulation of a DP vessel.

An Idea of Heading Control for Air Cushion Vehicles

Air cushion vehicle (ACV) is one type of high performance watercraft. ACV can be propelled forward over the water, the ground and swale. It is widely used in both the civilian and military. Its operation is very different from general ships because of the structural particularity. The design of PID controller and neural net (NN) controller used for ACV heading control are explained in this paper. Simulations show that NN controller performs better than normal PID controller in heading control of ACV, when ACV is disturbed by wind.

Constrained control allocation using Cascading Generalized Inverse for dynamic positioning of ships

Control allocation is an important part of the dynamic positioning system, which determines the control inputs of each thruster device from the control law. Based on the Cascading Generalized Inverse algorithm, a simple and efficient control allocation scheme was proposed to improve the ability for keeping position of dynamic positioning ships. This method improved the performance of a single generalized inverse by using multiple generalized inverses, and solved the actuators saturation problem in constrained control allocation. Applying the method, an explicit solution was obtained, and achieved a greater capacity and efficiency in the implementation process. The validity and excellent performance of this algorithm was proved by the simulation results.

Multi-rate sensor adaptive data fusion algorithm based on incomplete measurement

This paper proposes an adaptive data fusion algorithm for a multi-rate sensor system based on incomplete measurement. The algorithm has built a method of sensor subsystem fault detection. The subsystem failure is detected and the incomplete measurement is confirmed to avoid contaminating the entire system due to the single failure. The algorithm has built the subsystem switch control and it also introduced mapping matrices. Meanwhile, the algorithm defined new information sharing coefficients. The algorithm can adaptively select subsystems for the center integration. When the incomplete measurement of the subsystem is found, the predicted value of the subfilter will displace the state estimation for the center fusion. The current state estimation and a priori value of the subfilter are used by the global fusion, and this will improve the center estimate performance. The simulation result indicates the effectiveness of the proposed algorithm.

Optimizing adaptive thrust allocation based on group biasing method for ship dynamic positioning

Thrust allocation is an important part of the dynamic positioning system of ships, which determines the control inputs of each thruster device from the control law. In order to improve the faults of thrust allocation algorithms efficiently, the concept of group biasing is given and the adaptive strategy of group biasing method is designed. Consequently, the optimizing adaptive thrust allocation algorithm is proposed which bases on the group biasing and optimal methods, and the amplitude of bias can be adjusted adaptively according to thrust force. Applying the algorithm, the dynamic performances of dynamic positioned ships are improved availably, and the fuel consumption and maneuverability are both considered simultaneously. The validity and excellent performances of this algorithm were proved by the simulation results.

Amphibious hovercraft course control based on adaptive multiple model approach

Resistances exert on the hull is changing erratically when an amphibious hovercraft sailing. So it is necessary to study nonlinear control means for amphibious hovercraft course control. Adaptive multiple model approach was applied to hovercraft course control. Multiple model sets were established, and work points were divided according to ship speed. Local controllers were designed for each work point, and switch rule bases on weighting methods. Course control simulation tests were done. Results show that adaptive multiple model approach is better than conventional control as for hovercraft course control.

Synchronization control of multiple surface vessels without velocity measurements

In this paper, we study the position synchronization problem of multiple surface vessels with model uncertainties and external disturbances. The synchronization controller is proposed under the situation when velocity measurements are unavailable. Extended state observer is employed to estimate the velocity measurements and the unknown external disturbances. Coupling errors are introduced to design the feedback control laws. It is shown that with the developed cooperative scheme, position synchronization can be achieved under an undirected connected communication graph. Based on the Lyapunov stability analysis, all the closed-loop signals are guaranteed to be uniformly ultimately bounded. Simulation results are given to demonstrate the effectiveness of the proposed methods.