Hydraulic model with roughness coefficient updating method based on Kalman filter for channel flood forecast

A real-time channel flood forecast model was developed to simulate channel flow in plain rivers based on the dynamic wave theory. Taking into consideration channel shape differences along the channel, a roughness updating technique was developed using the Kalman filter method to update Manning＇s roughness coefficient at each time step of the calculation processes. Channel shapes were simplified as rectangles, triangles, and parabolas, and the relationships between hydraulic radius and water depth were developed for plain rivers. Based on the relationship between the Froude number and the inertia terms of the momentum equation in the Saint-Venant equations, the relationship between Manning＇s roughness coefficient and water depth was obtained. Using the channel of the Huaihe River from Wangjiaba to Lutaizi stations as a case, to test the performance and rationality of the present flood routing model, the original hydraulic model was compared with the developed model. Results show that the stage hydrographs calculated by the developed flood routing model with the updated Manning＇s roughness coefficient have a good agreement with the observed stage hydrographs. This model performs better than the original hydraulic model.

Subband adaptive filter with variable reusing order of coefficient vectors

To increase the convergence rate of the improved normalized subband adaptive filter,a simple but effective method is presented to change the reusing order of coefficient vectors of the adaptive filter. At the beginning of adaptation the algorithmjust uses its current coefficient vector to update the adaptive filter to maintain fast convergence rate,while in steady state it employs several most recent coefficient vectors to update the adaptive filter to reduce misalignment. Simulation results showthat the proposed algorithmcan obtain both fast convergence rate and small steady-state misalignment.

Design of complex FIR filters with arbitrary magnitude and group delay responses

To design approximately linear-phase complex coefficient finite impulse response （FIR） digital filters with arbitrary magnitude and group delay responses, a novel neural network approach is studied. The approach is based on a batch back-propagation neural network algorithm by directly minimizing the real magnitude error and phase error from the linear-phase to obtain the filter＇s coefficients. The approach can deal with both the real and complex coefficient FIR digital filters design problems. The main advantage of the proposed design method is the significant reduction in the group delay error. The effectiveness of the proposed method is illustrated with two optimal design examples.

Noise level estimation method with application to EMD-based signal denoising

This paper proposes a new signal noise level estimation approach by local regions. The estimated noise variance is applied as the threshold for an improved empirical mode decomposition（EMD） based signal denoising method. The proposed estimation method can effectively extract the candidate regions for the noise level estimation by measuring the correlation coefficient between noisy signal and a Gaussian filtered signal. For the improved EMD based method, the situation of decomposed intrinsic mode function（IMFs） which contains noise and signal simultaneously are taken into account. Experimental results from two simulated signals and an X-ray pulsar signal demonstrate that the proposed method can achieve better performance than the conventional EMD and wavelet transform（WT） based denoising methods.

A Control Strategy of Frequency Self-adaptation Without Phase-locked Loop for VSC-HVDC

A control strategy of frequency self-adaptation without phase-locked loop(PLL)underαβstationary reference frame(αβ-SRF)for a VSC-HVDC system is presented to improve the operational performance of the system under severe harmonic distortion conditions.The control strategy helps to eliminate the cross-coupling under dq synchronous reference frame(dq-SRF),and is achieved through two key technologies:1)positive phase sequence(PPS)and negative phase sequence(NPS)fundamental components are extracted from the AC grid voltage with an improved multiple complex coefficient filter(IMCF),and 2)grid instantaneous frequency is rapidly and precisely tracked using a frequency self-adaptation tracking algorithm(FATA)without PLL.The proposed strategy is applied to a point-to-point VSCHVDC system and validated by means of simulations.The results are compared to those with the traditional vector control strategy under dq-SRF.Simulation results illustrate that the proposed strategy results in better system performance than that with the traditional strategy in terms of harmonic suppression under normal and severe operating conditions of the AC system.