Parameter identification of gun servo friction model based on the particle swarm algorithm

The friction in gun AC servo systems is highly nonlinear.The particle swarm optimization algorithm was used to develop a two-step offline identification methodology of the LuGre friction parameters to compensate for the dynamic friction.Four static parameters were estimated via the Stribeck curve and two dynamic parameters were obtained from the stick-slip response for the dynamic friction compensation.Experimental results verify the effectiveness of the scheme for high-precision trajectory tracking,with position tracking errors for a sinusoidal trajectory of less than 1.25 mrad.