A robust nonlinear control design for remotely operated vehicle depth control systems

In this paper, an input-output linearization controller with an adaptive fuzzy outer loop is applied to the depth control of a nonlinear remotely operated vehicle (ROV). The adaptive fuzzy system is added to increase the robustness as well as add "intelligence" to conventional input-output controllers. The free control parameters are selected using multi-objective fuzzy genetic algorithm optimization. Simulation results are presented which demonstrate that the proposed control scheme can enhance the closed-loop system performance by reducing the output tracking errors.