To overcome ill-posed problem of force identification in the Transfer Path Analysis (TPA) of a rocket engine, this paper proposes a novel TPA based on weighted Tikhonov regularization. Firstly, the upper bound of relative force identification error of the traditional TPA is derived. Secondly, weighting matrix and Bayesian theory are adopted to improve the accuracy of force identification, and then the theory of the improved TPA is built. Finally, a ground vibration testing of the rocket engine is performed to analyze its path contributions. The results show that the proposed TPA is more accurate than the traditional TPA.

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Quadruped robots working in jungles, mountains or factories should be able to move through challenging scenarios. In this paper, we present a control framework for quadruped robots walking over rough terrain. The planner plans the trajectory of the robot's center of gravity by using the normalized energy stability criterion, which ensures that the robot is in the most stable state. A contact detection algorithm based on the probabilistic contact model is presented, which implements eventbased state switching of the quadruped robot legs. And an on-line detection of contact force based on generalized momentum is also showed, which improves the accuracy of proprioceptive force estimation. A controller combining whole body control and virtual model control is proposed to achieve precise trajectory tracking and active compliance with environment interaction. Without any knowledge of the environment, the experiments of the quadruped robot SDUQuad-144 climbs over significant obstacles such as 38 cm high steps and 22.5 cm high stairs are designed to verify the feasibility of the proposed method.

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