Pang Yong-jie

Motion Control System Architecture of Underwater Robot

Motion control system architecture of underwater robot is presented, which includes hardware and software architecture. Considering the longitudinal velocity effects on the other dimensions of underwater robot, a nonlinear controller is presented. The stability is verified with Lyapunov function. In order to coordinate motions on different dimensions, a virtual sonar based guidance law is introduced which originates from the behavior of human beings. Finally, the reliability and feasibility of the motion control system are demonstrated by sea trial

Strong tracking adaptive Kalman filters for underwater vehicle dead reckoning

To impove underwater vehicle dead reckoning, a developed strong tracking adaptive kalman filter is proposed. The filter is improved with an additional adaptive factor and an estimator of measurement noise covariance. Since the magnitude of fading factor is changed adaptively, the tracking ability of the filter is still enhanced in low velocity condition of underwater vehicles. The results of simulation tests prove the presented filter effective.

A Fault-tolerable Control Scheme for an Open-frame Underwater Vehicle

Open-frame is one of the major types of structures of Remote Operated Vehicles (ROV) because it is easy to place sensors and operations equipment onboard. Firstly, this paper designed a petri-based recurrent neural network (PRFNN) to improve the robustness with response to nonlinear characteristics and strong disturbance of an open-frame underwater vehicle. A threshold has been set in the third layer to reduce the amount of calculations and regulate the training process. The whole network convergence is guaranteed with the selection of learning rate parameters. Secondly, a fault tolerance control (FTC) scheme is established with the optimal allocation of thrust. Infinity-norm optimization has been combined with 2-norm optimization to construct a bi-criteria primal-dual neural network FTC scheme. In the experiments and simulation, PRFNN outperformed fuzzy neural networks in motion control, while bi-criteria optimization outperformed 2-norm optimization in FTC, which demonstrates that the FTC controller can improve computational efficiency, reduce control errors, and implement fault tolerable thrust allocation.

Observer-Based Dynamic Control of an Underactuated Hand

The purpose of this paper was to construct a velocity observer based on the dynamic model and realize accurate dynamic curve and force control. Curve fitting with the observer obtained precise velocity signals. Compared with PID and factored moment methods, it decreased the fitting errors a lot and achieved ideal results. Compensated with the inverse dynamic equation, the force-based impedance control with the observer could not only realize accurate force tracking, but achieve finger dynamic control by the combination of curve fitting and force tracking. Furthermore, a static grasp model was established for appropriate force distribution. The finger could grasp slippery, fragile, comparatively heavy and large objects like an egg with only base joint torque and position sensors, which illustrated that the hand could accomplish difficult tasks by using the static grasp model and dynamic control.The purpose of this paper was to construct a velocity observer based on the dynamic model and realize accurate dynamic curve and force control. Curve fitting with the observer obtained precise velocity signals. Compared with PID and factored moment methods, it decreased the fitting errors a lot and achieved ideal results. Compensated with the inverse dynamic equation, the force-based impedance control with the observer could not only realize accurate force tracking, but achieve finger dynamic control by the combination of curve fitting and force tracking. Furthermore, a static grasp model was established for appropriate force distribution. The finger could grasp slippery, fragile, comparatively heavy and large objects like an egg with only base joint torque and position sensors, which illustrated that the hand could accomplish difficult tasks by using the static grasp model and dynamic control.

A fuzzy neural networks controller of underwater vehicles based on ant colony algorithm

Owing to the characteristic of autonomous underwater vehicles (AUV) control and to solve the typical nonlinearity control system, we deduced a new fuzzy neual network control based on expert experience and ant colony algorithm. This algorithm superiority in solving combination optimization problems which consists of the rule sets and parameters of the membership functions of the continuous fuzzy controller to be slected. In order to enhance the efficiency of ant colony algorithm and prevent the precocity, the expert experience and improving ant colony algorithm are introduced in. Simulation results and applications showed that method is effective enough to make control simpler and robust and to get good control performance.

Motion Control System of Underwater Robot without Rudder and Wing

Motion control system of underwater robot without rudder and wing is presented with hardware and software architecture. Considering coupling effects and thrust reduction of propellers, the control layer, perception layer and executive layer in underwater robot system architecture are modified. In control layer, a nonlinear controller is presented to handle coupling effects between the longitudinal dimension and other dimensions of underwater robot. The stability of the controller is verified with Lyapunov function. A virtual sonar based guidance law is proposed in perception layer to coordinate motions on different dimensions, which originates from the behavior of human beings. In executive layer a kind of thruster configuration for high speed traveling is introduced to handle thrust reduction of tunnel thrusters. Finally, the reliability and feasibility of the motion control system are demonstrated by sea trial

Research on a fuzzy immune PID controller to reduce roll of near-water-surface vehicle with active bionic fin stabilizer

Near-surface vehicel will invectively roll, pitch and heave heavily when they close to surface where there are waves, sea wind and ocean current. These disturbances influenced the normal working and safety of the autonomous underwater vehicles a lot. As anti-roll technology develops, a kind of active bionic fin stabilizer which can reduce roll effectively comes out. Hence this kind of active stabilization system has a lot of uncertainties, A fuzzy-immune PID controller is proposed to optimize parameters of PID controller under different wave disturbance. From simulation results, it can be seen that this kind of PID controller can optimize system effectively.

Type-2 fuzzy logic neural network control and target following for Remote Operated Vehicles

Accurate control and target following are very important for Remote Operated Vehicles subsea engineering. In order to make Remote Operated Vehicles task more effective and accurate, type-2 fuzzy logic neural network has been introduced to model and minimize the effects of uncertainties in rule-base fuzzy logic system. In the online learning strategy, the gradient descent method has been used for online training. The results of tank experiments have proved that the controller can improve the computation efficiency, reduce control errors, vibration and overshoot. Thus the controller displays strong robustness in the underwater robotic control. In the 3-D target following simulations, ROV can precisely follow the target in still and current underwater enviroment. These simulations verify the controllers capacity to realize 3D-trajectory control and target following. It can realize 3D-target following curve tracking, obstacle avoidance and guarantee underwater task accomplishment.

Research on a method to reduce roll and pitch of AUV based on active bionic fin stabilizer

Autonomous underwater vehicles will invectively roll, pitch and heave heavily when they close to surface where there are waves, sea wind and ocean current. These disturbances influenced the normal working and safety of the autonomous underwater vehicles a lot. As anti-roll technology develops, a kind of active bionic fin stabilizer which can reduce roll and pitch effectively comes out. Hence this kind of active stabilization system is proposed to reduce the roll and pitch of the autonomous underwater vehicle when the autonomous underwater vehicle closes to water surface. From simulation results, it can be seen that active bionic fin stabilizer can effectively reduce roll and pitch of AUV under different wave encounter angle.

Motion control of AUV based on embedded operation system

The software and hardware architecture of a certain AUVs motion control system based on embedded operation system are respectively described, and the data flow of motion control process is also discussed. Meanwhile, a switch function is presented to smooth the instruction output during joint operating with rudders and thrusters; a modified S-plane Controller (MSC) is proposed by analyzing underwater vehicles dynamics and taking static force and coupling effects between the longitude velocity and other dimensions into account. Finally, some experiments are conducted, and the results prove the motion control system feasible.