<div style="text-align:justify;"> A test method and system for AI industrial application capabilities of smart terminals. The method includes the following steps: According to the temperature change va...<div style="text-align:justify;"> A test method and system for AI industrial application capabilities of smart terminals. The method includes the following steps: According to the temperature change values of different AI industrial applications executed by standard smart terminal equipment under different equipment parameters, the equipment parameters and temperature changes of standard smart terminal equipment are constructed. Correlation model;obtain the device parameters of the smart terminal device to be tested, and obtain the predicted value of the temperature change of the smart terminal device to be tested based on the correlation model between the device parameters of the standard smart terminal device and the temperature change;Measure the actual value of the temperature change of the intelligent terminal device executing different AI industrial applications;obtain the test result of the intelligent terminal device to be tested according to the predicted value of the temperature change and the actual value of the temperature change. </div>展开更多
The choice of this investigation is to tune the proportional-integral-derivative (PID) parameters separately for controlling the moisture content in paper industry by using Particle Swarm Optimization (PSO). This pape...The choice of this investigation is to tune the proportional-integral-derivative (PID) parameters separately for controlling the moisture content in paper industry by using Particle Swarm Optimization (PSO). This paper boon a new algorithm for PID controller tuning based particle swarm optimization. PSO algorithm has recently developed as a very powerful method for real parameter optimization. This new process is proposed to combine both the algorithms to get better optimization values. The proposed algorithm tuned the PID parameters and its performance has been compared with PID algorithm. Compared to PID algorithm technique, dynamic performance requirements such as rise time settling time and peak overshoot optimal values produced by PSO. The plant model represented by the transfer function is obtained by the system identification toolbox.展开更多
The mobile hybrid machining robot has a very bright application prospect in the field of high-efficiency and high-precision machining of large aerospace structures.However,an inappropriate base placement may make the ...The mobile hybrid machining robot has a very bright application prospect in the field of high-efficiency and high-precision machining of large aerospace structures.However,an inappropriate base placement may make the robot encounter a singular configuration,or even fail to complete the entire machining task due to unreachability.In addition to considering the two constraints of reachability and non-singularity,this paper also optimizes the robot base placement with stiffness as the goal to improve the machining quality.First of all,starting from the structure of the robot,the reachability and nonsingularity constraints are transformed into a simple geometric constraint imposed on the base placement:feasible base placement area.Then,genetic algorithm is used to search for the base placement with near optimal stiffness(near optimal base placement for short)in the feasible base placement area.Finally,multiple controlled experiments were carried out by taking the milling of a protuberance on the spacecraft cabin as an example.It is found that the calculated optimal base placement meets all the constraints and that the machining quality was indeed improved.In addition,compared with simple genetic algorithm,it is proved that the feasible base placement area method can shorten the running time of the whole program.展开更多
文摘<div style="text-align:justify;"> A test method and system for AI industrial application capabilities of smart terminals. The method includes the following steps: According to the temperature change values of different AI industrial applications executed by standard smart terminal equipment under different equipment parameters, the equipment parameters and temperature changes of standard smart terminal equipment are constructed. Correlation model;obtain the device parameters of the smart terminal device to be tested, and obtain the predicted value of the temperature change of the smart terminal device to be tested based on the correlation model between the device parameters of the standard smart terminal device and the temperature change;Measure the actual value of the temperature change of the intelligent terminal device executing different AI industrial applications;obtain the test result of the intelligent terminal device to be tested according to the predicted value of the temperature change and the actual value of the temperature change. </div>
文摘The choice of this investigation is to tune the proportional-integral-derivative (PID) parameters separately for controlling the moisture content in paper industry by using Particle Swarm Optimization (PSO). This paper boon a new algorithm for PID controller tuning based particle swarm optimization. PSO algorithm has recently developed as a very powerful method for real parameter optimization. This new process is proposed to combine both the algorithms to get better optimization values. The proposed algorithm tuned the PID parameters and its performance has been compared with PID algorithm. Compared to PID algorithm technique, dynamic performance requirements such as rise time settling time and peak overshoot optimal values produced by PSO. The plant model represented by the transfer function is obtained by the system identification toolbox.
基金supported by National Natural Science Foundation of China(Nos.91948301,52175025 and 51721003).
文摘The mobile hybrid machining robot has a very bright application prospect in the field of high-efficiency and high-precision machining of large aerospace structures.However,an inappropriate base placement may make the robot encounter a singular configuration,or even fail to complete the entire machining task due to unreachability.In addition to considering the two constraints of reachability and non-singularity,this paper also optimizes the robot base placement with stiffness as the goal to improve the machining quality.First of all,starting from the structure of the robot,the reachability and nonsingularity constraints are transformed into a simple geometric constraint imposed on the base placement:feasible base placement area.Then,genetic algorithm is used to search for the base placement with near optimal stiffness(near optimal base placement for short)in the feasible base placement area.Finally,multiple controlled experiments were carried out by taking the milling of a protuberance on the spacecraft cabin as an example.It is found that the calculated optimal base placement meets all the constraints and that the machining quality was indeed improved.In addition,compared with simple genetic algorithm,it is proved that the feasible base placement area method can shorten the running time of the whole program.
