Resumen
When a cross-domain robot (CDR) flies on the water surface, the large pitch angle and roll angle may lead to water flooding into the robot cabin or even overturning. In addition, the CDR is influenced by some uncertain parameters and external disturbances, such as the water resistance and current. To constrain the robot attitude angle and improve the robustness of the controller, a non-singular terminal sliding mode asymmetric barrier control (NTSMABC) algorithm is proposed. All the uncertain disturbances are regarded as a lump disturbance, and a radial basis function neural network (RBFNN) is designed to compensate for the output of the controllers. Unlike the traditional quadrotors, the robot controls the yaw angle by paddles when the robot flies on the water surface. To prevent the actuator saturation and the robot from rolling over due to excessive yaw angular velocity, an adaptive integral sliding mode barrier control (AISMBC) algorithm is proposed to constrain the yaw angular velocity directly. This algorithm adaptively adjusts the gain of the sliding surface to suppress the influence of the lump disturbance on the robot. Another RBFNN is designed to compensate for the output of the controller. Simulation results demonstrate the effectiveness of the proposed control methods.