Hybrid approach for dynamic model identification of an electro-hydraulic parallel platform

In this paper, a hybrid optimization algorithm is proposed to identify the dynamic parameters of a 6-DOF electro-hydraulic parallel platform. The dynamic model of a parallel platform with arbitrary geometry, inertia distribution and frictions is obtained based on a structured Boltzmann–Hamel–d’Alembert formulation, and then the estimation equations are explicitly expressed in terms of a linear form with respect to the identified inertial and the friction coefficients in accordance with a linear friction model. However, when nonlinear friction models are considered, the parameter identification of the electro-hydraulic parallel platform is considered as an optimization process with an objective function minimizing the errors between the measurement and identification, and then an effective combination of the particle swarm optimization (PSO) method and the local quasi-Newton method is proposed to solve the identification problem. Experimental identification processes are carried out for the identified parameters, and the identified models are compared by the predicted forces between the LS method and the optimization technique as well as between the linear and nonlinear friction models.