In order to track the desired path as fast as possible,a novel autonomous vehicle path tracking based on model predictive control(MPC)and PID speed control was proposed for high-speed automated vehicles considering th...In order to track the desired path as fast as possible,a novel autonomous vehicle path tracking based on model predictive control(MPC)and PID speed control was proposed for high-speed automated vehicles considering the constraints of vehicle physical limits,in which a forward-backward integration scheme was introduced to generate a time-optimal speed profile subject to the tire-road friction limit.Moreover,this scheme was further extended along one moving prediction window.In the MPC controller,the prediction model was an 8-degree-of-freedom(DOF)vehicle model,while the plant was a 14-DOF vehicle model.For lateral control,a sequence of optimal wheel steering angles was generated from the MPC controller;for longitudinal control,the total wheel torque was generated from the PID speed controller embedded in the MPC framework.The proposed controller was implemented in MATLAB considering arbitrary curves of continuously varying curvature as the reference trajectory.The simulation test results show that the tracking errors are small for vehicle lateral and longitudinal positions and the tracking performances for trajectory and speed are good using the proposed controller.Additionally,the case of extended implementation in one moving prediction window requires shorter travel time than the case implemented along the entire path.展开更多
Brush scrubber cleaning is widely used for post chemical mechanical polishing(CMP)cleaning in semiconductor manufacturing.In this study,an experimental system based on fluorescence technique and particle-tracking velo...Brush scrubber cleaning is widely used for post chemical mechanical polishing(CMP)cleaning in semiconductor manufacturing.In this study,an experimental system based on fluorescence technique and particle-tracking velocimetry(PTV)technique was employed to characterize the particle removal displacement and velocity in the interface between a transparent copper film and a porous polyvinyl alcohol(PVA)brush during the cleaning process.Several different cleaning conditions including rotation speeds,loading pressure and cleaning agent were examined and the particle removal rate was compared.Elastic and friction removal,hydrodynamic removal and mixed-type removal are the three types of particle removal.Particles with an arc trace and uniform velocity curves were removed by friction and elastic force which were related to the brush load.Particles with a random trace and fluctuant velocity curves were removed by hydrodynamic force which was determined by the brush rotation speed.The increase of particle removal rate(PRR)with brush rotation speed is a logistic function.It is easier to improve PRR by increasing the brush load or by adding surfactant than by increasing the brush rotation speed.展开更多
基金Project(20180608005600843855-19)supported by the International Graduate Exchange Program of Beijing Institute of Technology,China。
文摘In order to track the desired path as fast as possible,a novel autonomous vehicle path tracking based on model predictive control(MPC)and PID speed control was proposed for high-speed automated vehicles considering the constraints of vehicle physical limits,in which a forward-backward integration scheme was introduced to generate a time-optimal speed profile subject to the tire-road friction limit.Moreover,this scheme was further extended along one moving prediction window.In the MPC controller,the prediction model was an 8-degree-of-freedom(DOF)vehicle model,while the plant was a 14-DOF vehicle model.For lateral control,a sequence of optimal wheel steering angles was generated from the MPC controller;for longitudinal control,the total wheel torque was generated from the PID speed controller embedded in the MPC framework.The proposed controller was implemented in MATLAB considering arbitrary curves of continuously varying curvature as the reference trajectory.The simulation test results show that the tracking errors are small for vehicle lateral and longitudinal positions and the tracking performances for trajectory and speed are good using the proposed controller.Additionally,the case of extended implementation in one moving prediction window requires shorter travel time than the case implemented along the entire path.
基金supported by the National Natural Science Foundation of China(Grant No.51205006)the Tribology Science Fund of State Key Laboratory of Tribology and the Program for Excellent Talents by the Beijing Ministry of Organization
文摘Brush scrubber cleaning is widely used for post chemical mechanical polishing(CMP)cleaning in semiconductor manufacturing.In this study,an experimental system based on fluorescence technique and particle-tracking velocimetry(PTV)technique was employed to characterize the particle removal displacement and velocity in the interface between a transparent copper film and a porous polyvinyl alcohol(PVA)brush during the cleaning process.Several different cleaning conditions including rotation speeds,loading pressure and cleaning agent were examined and the particle removal rate was compared.Elastic and friction removal,hydrodynamic removal and mixed-type removal are the three types of particle removal.Particles with an arc trace and uniform velocity curves were removed by friction and elastic force which were related to the brush load.Particles with a random trace and fluctuant velocity curves were removed by hydrodynamic force which was determined by the brush rotation speed.The increase of particle removal rate(PRR)with brush rotation speed is a logistic function.It is easier to improve PRR by increasing the brush load or by adding surfactant than by increasing the brush rotation speed.
