Friction Identification And Control Of The Linear Motor System

In general speaking, one motion control system consists of mechanical structure and control algorithm, how to realize the best matching of two components to get desired performance is the persistent aim for engineers. The rapidly development of industry proposed more stringent requirement for motion control system. In present, this requirement become to achieve high speed and high accuracy, facing this rigorous requirement, we should take consideration from two components of the motion control system. Firstly, making improvement from the mechanical structure, taking effort on mechanical configuration, such as high acceleration, high velocity range, good stiffness, and reduce the friction efforts. Secondly, put emphasize on the control algorithm design, the control law should provide robustness and suppress adequate disturbance and parameter variation. This thesis mainly starts on these two parts, firstly, among all the effect factors, friction badly degrades the positioning accuracy of servomechanisms. This paper presents a method for identifying the dynamic parameters, as well as the friction characteristics. The inertia and viscous friction are estimated through a biased least squares scheme. The nonlinear friction model is formulated by using describing functions. Friction elements are estimated through the limit cycle analysis in a velocity control loop using nonlinear least square method. Results from experiments are in good agreed with the simulations. We designed a robust controller based on the model identified before, this controller consists of three parts: friction compensation; feedback controller and disturbance observer. We applied this controller to our platform, found proposed controller can suppress the disturbance effectively and compensate the overall system properly as our desired.