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.

The invention discloses an industrial robot based on iterative feedback adjustment and a trajectory tracking control method thereof, and belongs to the field of industrial robot control. The method combines the limitation of the amplitude of a control input signal and trajectory tracking errors, establishes a trajectory tracking control criterion, derives to obtain a partial derivative of the control criterion relative to a speed controller and a position controller, then designs three iterative experiments and uses the collected data to complete the estimation of the information of the partial derivative of the control criterion, and realizes the update and correction of trajectory tracking controller parameters of joint drive systems. Compared with the prior art, the trajectory trackingcontrol method is a model-free adaptive control method which is not affected by unmodeled dynamics and modeling errors, the effect of noise disturbance by a method of repeatedly obtaining data by iteration is eliminated, and position following errors in an iteration domain are combined to adaptively update the trajectory tracking controller parameters of a correction system to ensure that the following control performance of the system is optimal.