Abstract

Friction force plays an important role in motion control systems. Research shows that friction force is strongly nonlinear in most applications. And the nonlinear friction force has great influence on control performance, especially in motion control systems of hydraulic actuators. To improve control performance, many model-based controllers have been developed. In the past years, LuGre model has been widely used in most hydraulic actuators. However, for systems with one-way seals whose friction force is asymmetric between instroke and outstroke stage, LuGre model is no longer suitable. The paper developed a friction force test bench and studied the transient friction force of a hydraulic actuator which includes one-way seals. Experiment results show that friction force at instroke stage is bigger than that of outstroke stage for the variable valve actuator. Based on the experiment results, a bristle direction hypothesis is proposed. The bristle of the friction surface is thought to have an initial direction. For actuators with two-way seals or without seals, the bristle is thought to be perpendicular to the friction surface. And for actuators with one-way seals, the angle between bristles and friction surface is not 90° anymore. To apply the bristle direction hypothesis to controllers, a bristle direction coefficient is introduced to LuGre model to explain asymmetric friction behaviors. The simulation results have good agreements with experiment results. Based on the improved LuGre model, a backstepping controller is developed to compensate the nonlinear friction force. The friction force and system matched uncertainty are estimated by an extended state observer. Finally, some comparative experiments are implemented to verify the advantages of the improved LuGre model. The experiment results show that the improved LuGre model can help to reduce the engine valve lift tracking errors. At outstroke stage (engine valve close), the maximum absolute errors can be reduced by 40.6% to 65.0%, and the mean absolute errors can be reduced by 21.2% to 59.4%.

Full Text
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