Sliding friction wear of high-speed current-carrying is a key factor limiting the engineering of electromagnetic railgun, and is also a hot spot and difficult area for current research. In this paper, we simulate the internal ballistic dynamics and electrical contact characteristics based on multi-physics field effects and consider the actual working conditions such as Lorentz force, friction force and interference fit to simulate the motion of the armature in the bore. Based on the Archard wear model, a finite element simulation method combining HyperMesh and ANSYS is proposed to realize the wear prediction. The simulation results are compared with the experimental results to verify the accuracy of the prediction model. The results show that under the single firing condition, the wear is mainly concentrated at the end of the armature arm, and the rail wear is relatively light; with the increase of electromagnetic thrust, the increase of armature wear volume does not change much and is approximately equal; the armature wear volume is influenced by the wear coefficient, in which the armature wear volume increases about 190 times when the wear coefficient increases from $1\times 10^{-6}$ to $1\times 10^{-3}$ . Therefore, in order to reduce the degree of wear between the armature and rails, the lubrication conditions should be improved as much as possible. This study provides a simulation method for the wear prediction of electromagnetic rail launcher, which is important for the engineering application of electromagnetic rail launcher.

In the study of the passive biped robot, the avoidance of fall over is always an important direction of the research. In this paper, we propose Deep Deterministic Policy Gradient (DDPG) to control the biped robot walk steadily on the slope. For improve the speed of DDPG training, the DDPG used in the paper is improved by parallel actors and Prioritized Experience Replay (PER). In the simulation, we control different initial states that cause the biped robot to fall over. After the control, the biped robot can walk stably, which indicating that DDPG can effectively control the fall over of the biped robot.

Wear between the armature and the rail directly affects the state of armature–rail contact, which in turn affects the service life and launching efficiency of the electromagnetic rail launcher. In order to investigate the armature melting wear law during the launching process, a heat distribution model on the contact surface of the armature–rail is proposed, and a transient calculation model of armature wear is derived; to solve the model, the excitation current, inductance gradient, and contact resistance of the launcher were calculated and further analyzed with respect to the kinematic characteristics of the armature chamber. On this basis, the change rule of armature melting wear rate and the influencing factors are studied, and the derived calculation model is verified by using the experimental method. The results of this study show that the trend of armature wear rate can be broadly classified into a rapidly increasing phase, a sharply decreasing phase, and a smooth phase, with the maximum wear rate reaching about 0.008; the coefficient of friction, rail material, and rail structure all have an effect on the magnitude of the armature wear rate, but do not affect the trend of the armature wear rate; the experimentally verified armature wear volume differs from the theoretically calculated wear volume by only 3.65%. The model and analysis results established in this article are of great significance for optimizing the armature structure, improving the armature–rail contact performance, and ensuring the launching safety.