35results about How to "Realize automatic tuning" patented technology

The invention discloses a neural-network self-correcting control method of a permanent magnet synchronous motor speed loop. The method is characterized by: taking a current loop and a motor as generalized objects; firstly, collecting information, such as a rotating speed, a current and the like; using an adaptive linear time-delay neural network to carry out off-line parameter identification to the motor; then, taking a weight obtained through off-line learning as an initial value of on-line learning; finally, carrying out on-line parameter identification to the system, calculating a load torque of the motor according to the identified parameter; designing a neural-network self-correcting control law according to the obtained parameter value and a load disturbance value, adjusting the network weight on line according to an error between a controlled object and an identification model, and then setting the parameter of the neural-network self-correcting controller on line so as to realize online adjustment of the controller parameter. Uncertainty of the system and influence brought by the external disturbance can be eliminated. Dynamic performance and an anti-disturbance ability of a servo system can be improved.

The invention provides a method for automatic adjustment of a linpack performance test. The method specifically includes the following steps that the theoretical value and expected value of CPU performance are calculated; the N value and the NB value are continuously adjusted, and automatic adjustment of the linpack performance test is achieved. The invention further provides a system for automatic adjustment of the linpack performance test. The system comprises a CPU performance value calculation module and an automatic optimization module, wherein the CPU performance value calculation module is used for reading the information of the core number, the number and basic frequency of a CPU, and calculating the theoretical value and expected value of the CPU performance; the automatic optimization module is used for modifying the NB value and N value of a configuration file, wherein N represents the operation order of a linpack, and NB represents the size of a solved matrix block. Automatic optimization of the linpack performance test can be achieved, automated configuration is achieved, automatic running of the test is achieved, the optimal result is output, it is unnecessary to artificially modify the configuration file, the labor resource and the time resource of the test are saved, and simplification and automation of the test are achieved.