Research articleRobust input design for nonlinear dynamic modeling of AUV

- It could provide an input design which can extract rich-information data set to accurately estimates AUV hydrodynamic derivatives.
- It could apply constraints to the input and output variables, resulting in optimized inputs that stay within the operational envelope of AUVs.
- It uses a trackable method to do input design that is insensitive to parameter values.
- It can satisfy both robustness of constraints and optimality.

Input design has a dominant role in developing the dynamic model of autonomous underwater vehicles (AUVs) through system identification. Optimal input design is the process of generating informative inputs that can be used to generate the good quality dynamic model of AUVs. In a problem with optimal input design, the desired input signal depends on the unknown system which is intended to be identified. In this paper, the input design approach which is robust to uncertainties in model parameters is used. The Bayesian robust design strategy is applied to design input signals for dynamic modeling of AUVs. The employed approach can design multiple inputs and apply constraints on an AUV system's inputs and outputs. Particle swarm optimization (PSO) is employed to solve the constraint robust optimization problem. The presented algorithm is used for designing the input signals for an AUV, and the estimate obtained by robust input design is compared with that of the optimal input design. According to the results, proposed input design can satisfy both robustness of constraints and optimality.