A type of inverter power supply based on harmonic elimination PWM control

In order to output sine wave with small degree of distortion and improve stability,a type of inverter power supply is designed based on harmonic elimination pulse-width modulation(PWM)control.The rectifier and filter are added to input circuit of the inverter.Single-phrase full-bridge inverter performs the function of converting direct current into alternating current(DC/AC).In the control circuit,single chip micyoco(SCM)AT89C2051 is used for main control chip to accomplish the hardware design of the control system.A given value of output frequency of the inverter is input in the way of coding.According to the output frequency code which is read,SCM AT89C2051 defined harmonic elimination PWM control data which will be selected.Through internal timing control,the switches are switched under this provision of PWM control data.Then the driving signals of the switches in the inverter are output from I/O of SCM AT89C2051 to realize harmonic elimination PWM control.The results show that adding Newton homotopic algorithm of harmonic elimination PWM control to corresponding software of the control system can make the quality of output voltage of the inverter higher and it will have broad application prospects.

PRIMAL-DUAL PATH-FOLLOWING METHODS AND THE TRUST-REGION UPDATING STRATEGY FOR LINEAR PROGRAMMING WITH NOISY DATA

In this article,we consider the primal-dual path-following method and the trust-region updating strategy for the standard linear programming problem.For the rank-deficient problem with the small noisy data,we also give the preprocessing method based on the QR decomposition with column pivoting.Then,we prove the global convergence of the new method when the initial point is strictly primal-dual feasible.Finally,for some rankdeficient problems with or without the small noisy data from the NETLIB collection,we compare it with other two popular interior-point methods,i.e.the subroutine pathfollow.m and the built-in subroutine linprog.m of the MATLAB environment.Numerical results show that the new method is more robust than the other two methods for the rank-deficient problem with the small noise data.