Optimal and self‐tuning fusion Kalman filters for discrete‐time stochastic singular systems

Based on the optimal fusion estimation algorithm weighted by scalars in the linear minimum variance sense, a distributed optimal fusion Kalman filter weighted by scalars is presented for discrete‐time stochastic singular systems with multiple sensors and correlated noises. A cross‐covariance matrix of filtering errors between any two sensors is derived. When the noise statistical information is unknown, a distributed identification approach is presented based on correlation functions and the weighted average method. Further, a distributed self‐tuning fusion filter is given, which includes two stage fusions where the first‐stage fusion is used to identify the noise covariance and the second‐stage fusion is used to obtain the fusion state filter. A simulation verifies the effectiveness of the proposed algorithm. Copyright © 2008 John Wiley & Sons, Ltd.     

TFM调制及其改进技术的研究

通过对TFM调制技术的研究,修正了其中预调制滤波器冲击响应波形g(f)在时间轴上的位置及其频谱G(w)的表达式.然后将TFM基带信号进行近似,即对TFM的相位路径进行进一步的控制,得到一个改进的TFM调制技术.改进后的TFM调制技术和原TFM调制技术相比,频带压缩能力提高了一倍,误码性能不变,但会出现3 dB的寄生调幅,需要提高发射机的发射功率.     

A novel distributed approach to robust fault detection and identification

In this paper, we propose a novel distributed robust fault detection and identification (RFDI) scheme for a class of nonlinear systems. Firstly, a detection and identification estimator—robust fault tracking approximator (RFTA) is designed for online health monitoring. A novel feature of the RFTA is that it can simultaneously detect and accurately identify the shape and magnitude of the fault and disturbance. Moreover, it takes less online training time compared with the traditional neural network based fault diagnosis schemes. For some distributed systems, a network of distributed estimators is constructed where the RFTA is embedded into each estimator. Then we use consensus filter to filter the outputs of each estimator. One of the most important merits of the consensus filter is that its outputs can dramatically improve the accuracy of fault detection and identification. Next, the stability of the distributed RFDI scheme is rigorously investigated. Finally, two numerical examples are given to illustrate the feasibility and effectiveness of the proposed approach.     

An attempt to compare the performance of bioscrubbers and biotrickling filters for degradation of ethyl acetate in gas streams

This study presents a comparison of the efficiency of a bioscrubber and a biotrickling filter (BTF) for the removal of ethyl acetate (EA) vapour from a waste gas stream, under the same operating conditions. The maximum EA elimination capacity achieved in the bioscrubber was 550 g m^?3 h^?1 with removal efficiency higher than 96%. For higher EA loadings the bioscrubber was oxygen limited, which caused incomplete EA biodegradation. When pure oxygen was fed to the bioscrubber at a rate of 0.02 L min^?1, the bioscrubber recovered and could treat higher EA loadings without any oxygen limitation. The BTF achieved EA elimination capacity of 600 g m^?3 h^?1 with removal efficiency higher than 97% and the dissolved oxygen concentration remained substantially higher than in the bioscrubber. However, severe channelling and blockage of the spray nozzle occurred due to the excessive biomass growth. Overall, the bioscrubber system was easier to operate and control than the BTF, while an enhancement of the oxygen mass transfer in the bioscrubber could potentially increase its performance by up to three times. Copyright © 2005 Society of Chemical Industry     

A genetic‐based neuro‐fuzzy controller for blind equalization of time‐varying channels

This paper presents a neuro‐fuzzy network (NFN) where all its parameters can be tuned simultaneously using genetic algorithms (GAs). The approach combines the merits of fuzzy logic theory, neural networks and GAs. The proposed NFN does not require a priori knowledge about the system and eliminates the need for complicated design steps such as manual tuning of input–output membership functions, and selection of fuzzy rule base. Although, only conventional GAs have been used, convergence results are very encouraging. A well‐known numerical example derived from literature is used to evaluate and compare the performance of the network with other equalizing approaches. Simulation results show that the proposed neuro‐fuzzy controller, all parameters of which have been tuned simultaneously using GAs, offers advantages over existing equalizers and has improved performance. From the perspective of application and implementation, this paper is very interesting as it provides a new method for performing blind equalization. The main contribution of this paper is the use of learning algorithms to train a feed‐forward neural network for M‐ary QAM and PSK signals. This paper also provides a platform for researchers of the area for further development. Copyright © 2008 John Wiley & Sons, Ltd.     

A novel robust current control approach using adaptive line enhancer for three‐phase current‐source active power filter

An effective system control method is presented for applying a three‐phase current‐source PWM converter with a deadbeat controller to active power filters (APFs). In the shunt‐type configuration, the APF is controlled such that the current drawn by the APF from the utility is equal to the current harmonics and reactive current required for the load. To attain the time‐optimal response of the APF supply current, a two‐dimensional deadbeat control scheme is applied to APF current control. Furthermore, in order to cancel both the delay in the two‐dimensional deadbeat control scheme and the delay in DSP control strategy, an Adaptive Line Enhancer (ALE) is introduced in order to predict the desired value three sampling periods ahead. ALE has another function of bringing robustness to the deadbeat control system. Due to the ALE, settling time is made short in a transient state. On the other hand, total harmonic distortion (THD) of source currents can be minimized compared to the case where ideal identification of the controlled system can be made. The experimental results obtained from the DSP‐based APF are also reported. The compensating ability of this APF is very high in accuracy and responsiveness although the modulation frequency is rather low. © 2004 Wiley Periodicals, Inc. Electr Eng Jpn, 150(1): 50–61, 2005; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20014     

STATIONARY AND NON-STATIONARY STATE SPACE MODELS

Abstract. The concepts of time invariance, stationarity, non-stationarity and immemorial time are considered for state space models (SSMs). Necessary and sufficient conditions for stationarity are given and connected with standard conditions. Expressions are given for the unconditional mean and covariance matrix of the state of a time-immemorial SSM. Application of the results is made to a variety of theoretical and empirical models and the initialization of the Kalman filter in the non-stationary case and for the ARIMA ( p, d, q ) model.     

降低过滤机滤饼水分和细粒煤脱水浅析

根据对选煤厂细粒煤样的实验室优化脱水试验、工业试验及分析结果 ,对真空系统、气水分离器和分配头实施了技术改造 ,细粒煤脱水系统的运行状况得到显著改善 :圆盘真空过滤机滤饼水分降到 2 0 %左右 ,脱饼率在 95 %以上 ,每年的直接经济效益可达 30 0多万元     

Filtration of liquid aerosols with a horizontal fibrous filter

The aim of this study was to determine the filtration efficiency and pressure drop in liquid aerosol capture mechanisms using a fibrous coalescent filter. The experimental set-up was designed to measure filtration efficiency and pressure drop through the filter. To avoid the gravimetric effect, the filter was placed horizontally. A series of experiments highlighted the importance of operating conditions such as filtration velocity and aerosol concentration. The results demonstrated the advantage of working at high velocities to minimise the resistance of the medium and to enhance the mass efficiency of the coalescent filter. In parallel, no effect of aerosol concentrations in the pressure drop increase was noted.