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Cooperative Evolution Grey Wolf optimizer Algorithm for the Identification of the LuGre Friction Model in the Cart Motion of an Inverted Pendulum System

This paper proposes a cooperative evolution grey wolf optimizer algorithm for parameter identification of a LuGre friction model. The considered friction is affecting the cart of an inverted pendulum system without the pendulum. The proposed identification technique optimizes both of the static and the dynamic parameters simultaneously. It takes the advantages of the exploration capability of the evolutionary algorithm and the exploitation capability of the grey wolf optimizer to handle such nonlinear and multimodal optimization problem. Simulations have been conducted to assess the effectiveness of the proposed cooperative identification technique, and it is found to be significant in identifying both of the static and dynamic parameters accurately.