## 6 Semi-Physical Marine Vehicle Simulation Platforms  
The observation sensor nodes are mainly composing of AUVs, AUGs, ASVs, and the dynamics and motion control of marine vehicles also have a significant impact on the sensor networks. This section gives a general control frame for marine vehicles as the following three parts (Figure 6): marine vehicle control simulation (MVCS), actual control of marine vehicle (ACMV), and ocean currents prediction and waypoint planning (OCPWP). Ocean currents have a significant influence on the vehicles' motion, especially for AUGs. Sometimes, ocean currents are considerable compared to an AUG's velocity, or even bigger than an AUG's velocity. Ocean currents are estimated and then compensated with the vehicles' velocity. As we know, due to the ocean currents and other external disturbances, the feedback velocity, position from MVCS and ACMV are different. From the multiple vehicles trajectory plan, we obtain the desired velocity \(v_{d}\) and position \(\eta_{d}\) in the static water without consideration of ocean currents, so the vehicles control velocity \(v_{A}\) for ACMV may be different from \(v_{d}\). From the difference between actual control feedback information \(v_{A},\eta_{A}\) and simulation feedback information \(v_{s},\eta_{s}\), ocean currents \(v_{c}\) can be predicted. Then the desired \(v_{d},\eta_{d}\) and ocean currents \(v_{c}\) are added to ACMV, and the desired \(v_{d},\eta_{d}\) are utilized in MVCS. Through the simulation and actual control module, current predictions are updated cyclically from \(v_{A},\eta_{A}\) and \(v_{s},\eta_{s}\). Current prediction information from the previous cycle is applied to correct the vehicle's present velocity. If the vehicle navigated the downstream, we have \(v_{A}<v_{d}\), otherwise, we have \(v_{A}>v_{d}\). From the nominal vehicle dynamic model, MVCS provides an intuitive impression about the vehicle motion in the virtual reality, and provides a convenient condition for handing any emergency, collision avoidance, ocean current compensation, and debugging the advance control methods. Due to some velocity V, and position \(\eta\) from OCPWP, the simulation results can be achieved from the  
Figure 6: Semi-physical simulation platforms. nominal dynamic model. Then through the coordinate frame transforms, the marine vehicles' velocity, trajectory and position are transformed to the inertial frame, and finally, displayed on the virtual reality screen. ASVs can easily communicate with the shored control center in real-time mode, so the simulation component and actual control component can feedback information online from each other. AUVs and AUGs usually work in a pre-planning mode; therefore, it is convenient to switch the information transformation from real-time contact mode to the pre-planning mode or NRT mode. The dynamic models of AUV, AUG and ASV have a general form as in Equation (2) with subtle differences caused the propulsion systems used [25]:  
\[\mathrm{M}\dot{\mathrm{v}}+\mathrm{D}(\mathrm{v})\mathrm{v}+\mathrm{C}( \mathrm{v})\mathrm{v}+\mathrm{g}(\mathrm{\eta})=\tau \tag{2}\]  
where \(\mathrm{v},\mathrm{\eta},\tau\) are the velocities, position, and propulsion force, respectively; \(\mathrm{M},\mathrm{D}(\mathrm{v}),\mathrm{C}(\mathrm{v}),\mathrm{g}(\mathrm{ \eta})\) are the inertial mass matrix, hydrodynamic damping matrix, rigid body coriolis and centripetal matrix, and restoring forces and moments. AUVs and ASVs are propelled by thrusters, fins and rudders, so many advanced control methods are used in these vehicles' control. AUGs are propelled by net buoyancy and wings' lift force. As a result, AUGs' maneuverability is poor. On the other side, AUGs usually glide in steady states, and the switch time from initial state to a steady gliding process is short compared to the steady gliding process, so it is necessary to modify and correct the nominal dynamic model with lots of AUG ocean and pool experiments.