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Interference-fit riveting is a critical fastening technique in the field of aerospace assembly. The fatigue and sealing performance of the rivet joint are determined by the interference-fit level of the rivet joint. As a result, it is of great importance to measure the interference-fit level accurately and effectively. Conventional interference-fit level measurement methods can be divided into direct measurement (destructive test on test-piece) and indirect measurement (off-line dimensional measurement of upset rivet head). Both methods cannot be utilized in automatic riveting. In this paper, an on-line non-destructive measurement method is developed to measure the interference-fit level. By taking full advantage of servo-driving riveting integrated with force measurement, the force-deformation data of the deformed rivet can be obtained in real time. The recognized feature points from the force-deformation data can reflect the height of the upset rivet head.

In this paper, a closed loop path planning and tracking control approach of collision avoidance for autonomous vehicle is proposed. The two-level model predictive control (MPC) is proposed for the path planning and tracking. The upper-level MPC is designed based on the simple vehicle kinematic model to calculate the collision-free trajectory and the potential field method is adopted to evaluate the collision risk and generate the cost function of the optimization problem. The lower-level MPC is the trajectory-tracking controller based on the vehicle dynamics model that calculates the desired control inputs. Finally the control inputs are distributed to steering wheel angle and motor torque via optimal control vectoring algorithm. Test cases are established on the Simulink/CarSim platform to evaluate the performance of the controller.

To reduce the energy consumption level of electric vehicles, the working range of the regenerative braking system will gradually expand to the high state of charge of the battery. The time delay in the control signal transmission path of the high state of charge regenerative braking control process will affect the regenerative braking. At the same time, regenerative braking under a high state of charge puts forward higher requirements for the control accuracy of regenerative current. In the research of this paper, the motor model, battery model, and vehicle dynamics model are firstly established by using MATLAB/Simulink, and the dynamic relationship between regenerative current and regenerative braking torque is analyzed at the same time. Considering the system time delay, this paper proposes a high-charge regenerative braking control strategy (SPPC) that combines Smith prediction and prescribed performance control.