As one of the core equipment of ITER sensor steady-state test platform, high-precision power supply is a large capacity single-phase inverter. In order to realize the fast response of power supply and the high-precision of output current, a cascaded H-bridge inverter scheme is adopted and a carrier phase-shifted pulse width modulation (CPS-PWM) strategy is proposed for this topology. Based on the analysis of multi-level inverter topology and control strategy, a control system based on DSP-CPLD is designed in this paper. Simulation and experimental results verify the feasibility and effectiveness of the proposed scheme.

In this paper, we present a sparse matrix transform (SMT) based linear discriminant analysis (LDA) algorithm for high dimensional data. The within-class scatter matrix in LDA is constrained to have an eigen-decomposition that can be represented as an SMT. Then, under maximum likelihood framework, based on greedy minimization strategy, the within-class scatter matrix can be efficiently estimated. Moreover, the estimated within-class scatter matrix is always positive definite and well-conditioned even with limited sample size, which overcomes the singularity problem in traditional LDA algorithm. The proposed method is compared, in terms of recognition rate, to other commonly used LDA methods on ORL and UMIST face databases. Results indicate that the performance of the proposed method is overall superior to those of traditional LDA approaches, such as the Fisherfaces, D-LDA, S-LDA and newLDA methods.