S-surface Control Research Articles

Improved active disturbance rejection heading control for unmanned wave glider

The Unmanned Wave Glider (UWG) captures wave energy in the ocean and mechanically converts it into propulsion. This unique propulsion mode makes the speed of UWG uncontrollable and changeable, which leads to the unique heading control problem. The large model perturbation brought by the speed change of UWG makes it difficult for traditional controllers to maintain consistent heading control effect. In this paper, the Improved Active Disturbance Rejection Control (IADRC) method was proposed for UWG heading control. The Improved Linear Extended State Observer (ILESO) was proposed to dynamically modify the second-order series integral system transformed from LESO based on similarity principle. Falfunction filter was utilized in ILESO to reduce the influence of speed sensor noise. The Improved S-surface control strategy was proposed as the error feedback of IADRC. Compared with Non-Linear State Error Feedback (NLSEF), the parameters of the controller are greatly reduced and can be adjusted adaptively according to the speed of UWG. Numerical simulation experiments and sea trail were performed. The results showed that the proposed IADRC can significantly improve heading control performance for UWG at both steady and unsteady speeds.

Disturbance Observer-Based Fuzzy Adapted S-Surface Controller for Spatial Trajectory Tracking of Autonomous Underwater Vehicle

A new adaptive robust control scheme combining the disturbance-observer-based control (DOBC) with fuzzy adapted S-Surface control is proposed for trajectory tracking control of autonomous underwater vehicle. The main contribution of the proposed method is that control configuration does not require the bounds of uncertainty of the vehicle to be known and disturbances effect can be estimated and rejected. The proposed control law is mainly composed of three parts: a feed forward control along with disturbance estimator, S-Surface control and single input adaptive fuzzy proportional-integral (PI) compensator. The nominal feed forward controller specifies desired closed loop dynamics with extravagance from known preferred acceleration vector. Meanwhile, the disturbance observer and adaptive fuzzy PI control term to compensate the unknown effects that are disturbances and unmodeled dynamics. An additional term as S-Surface control assures fast convergence due to a nonlinear expression in to surface and also enhance stability of the underwater vehicle in oceanic environment. Moreover, the disturbance observer enhances the robustness performance of the adaptive fuzzy system for disturbances that cannot be modeled by fuzzy logic. The stability of closed loop controlled system is proven to be guaranteed according to Lyapunov theory. Finally, numerical simulation results illustrate the effectiveness and robustness of the proposed control method.

Unmanned wave glider heading model identification and control by artificial fish swarm algorithm

We introduce the artificial fish swarm algorithm for heading motion model identification and control parameter optimization problems for the “Ocean Rambler” unmanned wave glider (UWG). First, under certain assumptions, the rigid-flexible multi-body system of the UWG was simplified as a rigid system composed of “thruster + float body”, based on which a planar motion model of the UWG was established. Second, we obtained the model parameters using an empirical method combined with parameter identification, which means that some parameters were estimated by the empirical method. In view of the specificity and importance of the heading control, heading model parameters were identified through the artificial fish swarm algorithm based on tank test data, so that we could take full advantage of the limited trial data to factually describe the dynamic characteristics of the system. Based on the established heading motion model, parameters of the heading S-surface controller were optimized using the artificial fish swarm algorithm. Heading motion comparison and maritime control experiments of the “Ocean Rambler” UWG were completed. Tank test results show high precision of heading motion prediction including heading angle and yawing angular velocity. The UWG shows good control performance in tank tests and sea trials. The efficiency of the proposed method is verified.

Heading control method and experiments for an unmanned wave glider

The control system designing of unmanned wave glider (UWG) is challenging since the control system is weak maneuvering, large time-lag and large disturbance, which is difficult to establish accurate mathematical model. The control system for the “Ocean Rambler” UWG is studied in this work. A heading control method based on S-surface controller is designed. For the “rudder zero drift” problem in trials, an improved S-surface control method based on rudder angle compensation is proposed, which can compensate the adverse effects from environmental forces and installation error. The tank test and sea trial results prove that the proposed control method has favorable control performance, and the feasibility and reliability of the designed control system are also verified.

The Intelligent Control System and Experiments for an Unmanned Wave Glider.

The control system designing of Unmanned Wave Glider (UWG) is challenging since the control system is weak maneuvering, large time-lag and large disturbance, which is difficult to establish accurate mathematical model. Meanwhile, to complete marine environment monitoring in long time scale and large spatial scale autonomously, UWG asks high requirements of intelligence and reliability. This paper focuses on the “Ocean Rambler” UWG. First, the intelligent control system architecture is designed based on the cerebrum basic function combination zone theory and hierarchic control method. The hardware and software designing of the embedded motion control system are mainly discussed. A motion control system based on rational behavior model of four layers is proposed. Then, combining with the line-of sight method(LOS), a self-adapting PID guidance law is proposed to compensate the steady state error in path following of UWG caused by marine environment disturbance especially current. Based on S-surface control method, an improved S-surface heading controller is proposed to solve the heading control problem of the weak maneuvering carrier under large disturbance. Finally, the simulation experiments were carried out and the UWG completed autonomous path following and marine environment monitoring in sea trials. The simulation experiments and sea trial results prove that the proposed intelligent control system, guidance law, controller have favorable control performance, and the feasibility and reliability of the designed intelligent control system of UWG are verified.

A Feasible and Applicable Motion Control Method for AUV

Both the high speed and the changing excess buoyancy can make it difficult in motion control of AUV, in order to solve the problems, an improved control method based on S-surface control is proposed. Taking static forces and coupling effects between longitude velocity and other dimensions into account, the compensation related to the speed is brought into the method to handle the effects caused by high speed. In accordance with the thoughts of S-surface control, an anti-windup intelligent integral method is presented to handle the changing excess buoyancy and propulsion loss via an adaptive weight determined by estimating the motion states of AUV. Finally, experiments of velocity control, yaw control and depth control are conducted, and the results prove the feasibility and advantages in application to AUV motion control.

AUV modeling and motion control strategy design

To provide a suitable model for AUV simulation and control purposes, a general nonlinear dynamic model including a novel thruster hydrodynamics model was derived. Based on the modeling method, the “AUV-XX” simulation platform was established to carry out fundamental tests on its motion characteristics, stability, and controllability. A motion control strategy consisting of both position and speed control in a horizontal plane was designed for different task assignments of underwater vehicles. Combined control of heave and pitch was adopted to compensate for the reduction of vertical tunnel thrusters when the vehicle is moving at a high speed. An improved S-surface controller based on the capacitor plate model was developed with flexible gain selections made possible by different forms of restricting the error and changing the rate of the error. Simulation results show that the derived general mathematical model together with simulation platform can provide a test bed for fundamental tests of motion control. Additionally, the capacitor plate model S-surface control shows a good performance in guiding the vehicle to achieve the desired position and speed with sufficient accuracy.

Modeling and simulation of a mini AUV in spatial motion

Accurate modeling and simulation of autonomous underwater vehicle (AUV) is essential for autonomous control and maneuverability research. In this paper, a mini AUV- “MAUV-II” was researched and the nonlinear mathematic model of the AUV in spatial motion was derived based on momentum theorem. The forces acting on AUV were resolved to several modules which were expressed in matrix form. Based on the motion model and combined with virtual reality technology, a motion simulation system was constructed. Considering the characteristic of “MAUV-II”, the heading control and depth control were simulated by adopting S-surface control method. A long distance traveling simulation experiment based on target planning was also done. The simulation results show that the “MAUV-II” has good spatial maneuverability, and verify the feasibility and reliability of control software.

Expert S-surface control for autonomous underwater vehicles

S-surface control has proven to be an effective means for motion control of underwater autonomous vehicles (AUV). However there are still problems maintaining steady precision of course due to the constant need to adjust parameters, especially where there are disturbing currents. Thus an intelligent integral was introduced to improve precision. An expert S-surface control was developed to tune the parameters on-line, based on the expert system, it provides S-surface control according to practical experience and control knowledge. To prevent control output over-compensation, a fuzzy neural network was included to adjust the production rules to the knowledge base. Experiments were conducted on an AUV simulation platform, and the results show that the expert S-surface controller performs better than an S-surface controller in environments with currents, producing good steady precision of course in a robust way.