Modeling and robust control approach for autonomous underwater vehicles

Autonomous Underwater Vehicle (AUV) is a relevant technology for the sustainable use of ocean resources. AUV can be used as an important ocean observing platform to collect information on marine environmental characteristics for research and industry fields. In order to improve the observation quality and increase the navigation ability, many issues should be addressed and considered simultaneously. Achieve necessary maneuverability depends on two key factors: an accurate hydrodynamic model and an advanced control system. However, the cost to develop an accurate hydrodynamic model, which shrinks the uncertainty intervals, is usually high. Meanwhile, when the robot geometry is complex, it becomes very difficult to identify its dynamic and hydrodynamic parameters. In addition, according to the quadratic damping factor, underwater vehicle dynamic and hydrodynamic model is nonlinear from the control point of view. Moreover, unmodeled dynamics, parameter variations and environmental disturbances create significant uncertainties among the nominal model and the reality. Sensor noise, signal delay as well as unmeasured states also affect the stability and control performance of the motion control system. In many of our underwater competitions, it has been confirmed that the traditional Proportional-Integral-Derivative (PID) regulation is less efficient for low mass AUV. In this case, our scope is more focused on the combination of numerical modeling approaches and robust control schemes. In this work, we proposed a model based robust motion control scheme. Without loss of generality, a robust heading controller was implemented and validated in the sea on cubic-shaped CISCREA AUV. The proposed solution uses cost efficient Computational Fluid Dynamic (CFD) software to predict the two hydrodynamic key parameters: The added mass matrix and the damping matrix. Four Degree of Freedom (DOF) model is built for CISCREA from CFD calculation. Numerical and experimental results are compared. Besides, the proposed control solution inherited the numerically obtained model from previous CFD calculation. Numerically predicted the actuator force compensates the nonlinear damping behavior result in a linear model with uncertainties. Based on the bounded linear nominal model, we proposed H∞ approach to handle the uncertainties, we used kalman filter to estimate unmeasured states such as angular velocity and we developed smith compensator to compensate the sensor signal delay. The proposed robust heading control application uses only one compass as feedback sensor. This is important while AUV is working at certain depth where only magnetic sensors still work. Our robust control scheme was simulated in Matlab and validated in the sea near Brest. Simulation shows obvious advantage of the proposed robust control approach. Meanwhile, the proposed robust heading control is much faster than PID controller. The robust controller is insensitive to uncertainties and has no overshot. From both simulations and real sea experiments, we found our proposed robust control approach and the one compass heading control applications are efficient for low mass and complex-shaped AUV CISCREA.