In order to eliminate the characteristic harmonics in high voltage direct current (HVDC) transmission systems and to simplify the analog controller structure, this paper proposes a new digital controller by adopting an approximate inverse system control strategy according to the frequency response characteristic of the hybrid power filter. The proposed digital controller is implemented with a TMS320C32 DSP, including a series of parallel digital band-pass filters, phase shifters and amplifiers. The results of both simulations based on PSCAD and experiments on a 30 kVA HVDC system prove that the proposed digital control system is stable and efficient for eliminating the harmonics.

Utilizing the feature of quick response of HVDC to improve the performance of AC/DC system has become the emphasis to be researched. This paper introduces firstly the principle of the robust adaptive control of nonlinear systems with unmodeled dynamics, then developed the robust adaptive additional control of HVDC with unmodeled dynamics of generator in order to improve stability of power system. The additional control of HVDC with unmodeled dynamics only uses the local signals and its design is simple, furthermore it can obviously improve the stability of power system in different operational conditions. Experimental results using the presented concepts obtained on single machine infinite bus model are also included. These results prove the efficiency of the control scheme. The design process of controller provided a new idea to design controller by use of simplified model.

Spectral leakage caused by synchronous error in a nonsynchronous sampling system is an important cause that reduces the accuracy of spectral analysis and harmonic measurement. This paper presents a software sampling frequency adaptive algorithm that can obtain the actual signal frequency more accurately, and then adjusts sampling interval base on the frequency calculated by software algorithm and modifies sampling frequency adaptively. It can reduce synchronous error and impact of spectral leakage; thereby improving the accuracy of spectral analysis and harmonic measurement for power system signal where frequency changes slowly. This algorithm has high precision just like the simulations show, and it can be a practical method in power system harmonic analysis since it can be implemented easily.

The main objectives of this paper are to simultaneously improve power system damping and to maintain voltage at the static var compensator (SVC) location bus simultaneously. A new controller for SVC with closed-form analytic solution nonlinear optimal predictive control (NOPC) law was presented. The controller does not require online optimization and the huge calculation burden can be avoided, so that the demand of real-time control can be satisfied. In addition, there are only two design parameters, which are the predictive period and control order; so it is easy to implement and test in practical use. Simulation results have shown that the controller can not only attenuate power system oscillation effectively but can also maintain voltage at the SVC bus location.

A novel three-level zero-voltage zero-current switching (ZVZCS) DC/DC converter is proposed in this paper. A tapped-inductor is used to replace the normal output filter inductor, so that the circulating current in the zero-state can be reset to zero. The reset voltage and the reset time can be set conveniently just by simply changing the winding ratio of the tapped inductor. The converter achieves a zero-current tuning off for inner switching, and a zero-voltage tuning on for outer switching. No circulating current exists in the zero state, so that the loss in the on-state is reduced, and the efficiency can be improved. The experimental results verify that the ZVZCS has low voltage stress, zero-voltage and zero-current switching.

Because of the broad application of multilevel converters in the high-power area, a cascaded multilevel voltage-source inverter with phase-shifted SPWM (PS-SPWM) switching scheme is proposed as a static synchronous compensator (STATCOM). This can eliminate the bulky and weighty transformers and reduce power loss. In addition, the equivalent carrier frequency can be doubled and the output harmonics will be reduced compared with the STATCOM being put into operation. The operating principle and control methods are analyzed in detail and the feasibility is validated by simulation with MATLAB.

A substation system requires that communication be transmitted reliably, accurately and in real-time. Aimed at solving problems, e.g., flow confliction and sensitive data transmission, a model of the communication system of an agent-based automated substation is introduced. The running principle is discussed in detail and each type of agent is discussed further. At the end, the realization of the agent system applied to the substation is presented. The outcome shows that the communication system of an agent-based automated substation improves the accuracy and reliability of the data transfer and presents it in real-time.

It is recognized throughout history that understanding the properties of resources and transforming these resources into products are regarded as the nucleus of science and technology. Understanding the properties of information and transforming the information into products will then play a crucial role in the development of science and technology in the information age. An attempt is thus made in this paper to present the results on the concepts of information and the fundamental features of information transforms. Here information theory will be given a much broader scope than the well-known Shannon theory and the knowledge theory will go beyond the existing knowledge engineering. It is discovered in the paper that the transformations from information to knowledge and further to intelligence constitute the core mechanism of intelligence formation and is hence named the mechanism approach to intelligence research. It is also discovered that the major approaches to artificial intelligence in history, the structuralism, functionalism and behaviorism, can harmoniously be unified within the framework of the mechanism approach and no longer be contradictory.

A new precise actuator is proposed, which is actuated by the impact force of an end-loaded piezoelectric bimorph cantilever, and bears two degrees of freedom for translation and rotation. The dynamic characteristics of the piezoelectric bimorph were analyzed by FEM, and are further proved by experimental tests. A new control system for the actuator was put forward and tested, which is called the fixed-frequency with adjustable voltage. In addition, the actuator s performance of translation and rotation were both measured. The results demonstrate that the actuator is characterized by a simple structure, large movement range, strong driving ability and high positioning resolution. Its cost is estimated at only 1 % of the traditional impact actuators.

A principle for choosing the coherent integration number and an improved Doppler beam sharpening (DBS) imaging algorithm for mechanic scanning radar are presented in this paper. By compensating the range migration in wideband airborne mechanic scanning radar, the proposed DBS imaging algorithm can efficiently improve the resolution of a DBS image. In addition, based on the characteristic that the echo from the moving target will be modulated by the antenna pattern, a novel method used to locate the moving target is also presented, which begins with the sub-aperture moving target detection followed by the sliding window detection. Proper location can be achieved by using this method. Finally, the results on real radar data are provided to demonstrate the effectiveness of these proposed methods.

We propose the hybrid optical burst switching (HOBS), and investigate the HOBS-based ring topology with numerical simulation. Results indicate that the packet loss ratio in HOBS is much less than that in optical burst switching(OBS) and its performance depends on some parameters such as the packet proportion, the electronic buffer size and the processing speed in the node.

In order to rapidly and automatically identify the modulation level of digital amplitude modulated signals at low signal-to-noise ratio (SNR), a method of identifying the modulation levels of M-ary quadrature amplitude modulation (M-QAM) and M-ary amplitude shift keying (M-ASK) is proposed. In this method, wavelet transform with the optimal scale is used to identify the modulation levels of M-QAM and M-ASK signals. The performance of this method was investigated through simulations. Simulation results show that when the SNR is not lower than  4 dB, the percentage of correct identification of M-QAM is higher than 93 %, and when the SNR is not lower than 10 dB, the percentage of correct identification of M-ASK is higher than 90 %, using only 100 observed symbols. It shows that this method can rapidly acquire good performance at a low SNR.

In speech signal processing systems, frameenergy based voice activity detection (VAD) method may be interfered with the background noise and non-stationary characteristic of the frame-energy in voice segment. The purpose of this paper is to improve the performance and robustness of VAD by introducing visual information. Meanwhile, data-driven linear transformation is adopted in visual feature extraction, and a general statistical VAD model is designed. Using the general model and a two-stage fusion strategy presented in this paper, a concrete multimodal VAD system is built. Experiments show that a 55.0 % relative reduction in frame error rate and a 98.5 % relative reduction in sentence-breaking error rate are obtained when using multimodal VAD, compared to frame-energy based audio VAD. The results show that using multimodal method, sentence-breaking errors are almost avoided, and frame-detection performance is clearly improved, which proves the effectiveness of the visual modal in VAD.

In this paper, a new fast mode-selection approach is proposed. This algorithm combines the proposed approaches of mode pre-decision and precise large-small mode decision, by selecting the best mode efficiently. Experimental results show that the proposed approach can reduce the computational cost of full search and fast multi-block motion estimation by 80 % and 45 %, respectively, with similar visual quality and bit rate. The proposed algorithm also reduces by 75 % the computational cost of the large-small mode isolation algorithm for low-motion sequence coding, and with 0.06 PSNR gain and 3.7 % reduction in bit rate.

As a necessary input parameter for maximum a-posteriori(MAP) decoding algorithm, SNR is normally obtained from the channel estimation unit. Corresponding research indicated that SNR estimation deviation degraded the performance of Turbo decoding significantly. In this paper, MAP decoding algorithm with SNR estimation deviation was investigated in detail, and the degradation mechanism of Turbo decoding was explained analytically. The theoretical analysis and computer simulation disclosed the specific reasons for the performance degradation when SNR estimation was less than the actual value, and for the higher sensitivity of SNR estimation to long-frame Turbo codes.

Dynamic multicast traffic grooming in wavelength division multiplexing (WDM) networks was analyzed to minimize networkwide costs and to increase the network resource utilization. A network model was developed for dynamic multicast t

Sensor deployment is an important problem in mobile wireless sensor networks. This paper presents a distributed self-spreading deployment algorithm (SOMDA) for mobile sensors based on artificial neural-networks selforganizing maps algorithm. During the deployment, the nodes compete to track the event and cooperate to form an ordered topology. After going through the algorithm, the statistical distribution of the nodes approaches that of the events in the interest area. The performance of the algorithm is evaluated by the covered percentage of region/events, the detecting ability and the energy equalization of the networks. The simulation results indicate that SOMDA outperforms uniform and random deployment with lossless coverage, enhancive detecting ability and significant energy equalization.

A parametric curve based on a manifold is designed for constructing an accurate closed curve. A circle was defined as the parametric space and a non-uniform B-splines defined on the unit circle were used as base functions. A method to construct knot vectors, control points and corresponding parameters were proposed. A method to determine the coordinates for any point on a curve was also proposed. Some non-uniform rational B-splines (NURBS) control techniques, such as curves with an embedded line, a sharp angle, and so on, were used to verify the proposed method s compatibility with NURBS. Some examples were used to compare the arithmetic with that of NURBS. The results show that the method is not only simple, feasible and reliable but also compatible with a CAD system using NURBS.

In the research on spatial hearing and virtual auditory space, it is important to effectively model the head-related transfer functions (HRTFs). Based on the analysis of the HRTFs  spectrum and some perspectives of psychoacoustics, this paper applied multiple demes  parallel and real-valued coding genetic algorithm (GA) to approximate the HRTFs  zero-pole model. Using the logarithmic magnitude s error criterion for the human auditory sense, the results show that the performance of the GA is on the average 39 % better than that of the traditional Prony method, and 46 % better than that of the Yule-Walker algorithm.

A method of realization of automatic abstracting based on text clustering and natural language understanding is explored, aimed at overcoming shortages of some current methods. The method makes use of text clustering and can realize automatic abstracting of multi-documents. The algorithm of twice word segmentation based on the title and first sentences in paragraphs is investigated. Its precision and recall is above 95 %. For a specific domain on plastics, an automatic abstracting system named TCAAS is implemented. The precision and recall of multi-document s automatic abstracting is above 75 %. Also, the experiments prove that it is feasible to use the method to develop a domain automatic abstracting system, which is valuable for further in-depth study.

An integrated user access control method was proposed to address the issues of security and management in networked manufacturing systems (NMS). Based on the analysis of the security issues in networked manufacturing system, an integrated user access control method composed of role-based access control (RBAC), task-based access control (TBAC), relationship-driven access control (RDAC) and coalition-based access control (CBAC) was proposed, including the hierarchical user relationship model, the reference model and the process model. The elements and their relationships were defined, and the expressions of constraints authorization were given. The extensible access control markup language (XACML) was used to implement this method. This method was used in the networked manufacturing system in the Shaoxing spinning region of China. The results show that the integrated user access control method can reduce the costs of system security maintenance and management.

In order to predict and improve the performance of networked storage systems, this paper explored the relationship between the system I/O response time and its performance factors by quantitative analytical method. Through analyzing data flow in networked RAID storage system, we established its analytical model utilizing closed queueing networks and studied the performance bounds of the system I/O response time. Experimental results show that the theoretical bounds are found to be in agreement with the actual performance bounds of the networked RAID storage system and reflect the dynamic trend of its actual performance. Furthermore, it concludes that the CPU processing power and cache hit rate of the central storage server are the key factors affecting the I/O response time as the concurrent jobs are lower, while the network bandwidth and cache hit rate of the central storage server become the key factors as the concurrent jobs go higher.

Based on the analysis of the network intrusion detection model, a new design scheme for the integrated classifier is proposed. The attribute reduction algorithm of the discernibility matrix is used for the optimization design of reducing nodes of input and hidden layers. The experimental test result shows that this design is valid.

Implementing a flexible configuration of the QoS parameter in a distributed computing network has become a problem due to the weak scalability of current approaches. In an effort to solve this problem, an inner basic model of an intelligent agent (IA) is presented. The IA functionality was extended by introducing a primarily mobile agent. A QoS guarantee scheme was subsequently designed and implemented based on the model as well. By utilizing the proposed scheme, the IA can sense, predict and configure the data flow traffic. Since the communicating ability was considered and provided, the competition among different devices could be eliminated effectively and the global traffic can be optimized. The results of the simulations have shown that the proposed model can provide a QoS guarantee.