A comparison of functional control strategies for underwater vehicles: Theories, simulations and experiments

Functional control is key for any autonomous robot, linking high-level artificial intelligence with the robot actuators. Due to environmental disturbances, model uncertainties and nonlinear dynamic systems, reliable functional control is essential and improvements in the controller design can significantly benefit the overall vehicle performance. Even though there are many published studies considering the design of various advanced controllers, most of them are not evaluated in physical experiments. In this research, four different control strategies have been investigated: Proportional-Integral-Derivative Control (PID), Sliding Mode Control (SMC), Backstepping Control (BC) and Fuzzy Logic Control (FLC). The performances of these four controllers were simulated initially and evaluated by practical experiments in different conditions, including various environmental disturbances and hydrodynamic coefficients. The main contributions are as follows: Firstly, this paper reports a comparison study between different types of controllers based on simulations and physical experiments in various conditions; Secondly, this paper provides an improved SMC algorithm combining the merits from linear control and nonlinear control, and a customized second-order FLC method.