Qian Qing-quan

Networked control systems based on generalized predictive control and modified Smith predictor

The distributed control networks encounter nondeterministic delays in data communication between sensors, actuators and controllers, including direct-feedback control and higher level supervisor control. Aiming to uncertain network delays, time-variant or nonlinear controlled plant and imprecise Smith predictor models, a novel approach is proposed that modified Smith predictor combined with generalized predictive control (GPC). Because modified Smith predictor does not include network delay models, so it is no need for measuring, identifying or estimating network delays on line. The GPC enhances the systematic robustness and anti-jamming ability. Based on CSMA/CD (Ethernet) and CSMA/AMP (CAN Bus), the simulation results show that modified Smith dynamic predictor combined with GPC is effective.

Distribution Network Service Restoration Multiple Attribute Group Decision-making Using Entropy Weight and Group Eigenvalue

With the consideration of the group decision-making behavior for power distribution system dispatch, a distribution network service restoration multiple attribute group decision-making approach using entropy weight and group eigen value is proposed in this paper. Firstly, five evaluation indices such as the quantities of restored load, the number of switching operations and the rate of load balancing are introduced. With the introduction of entropy weights and objective weights, the schemes are comprehensively evaluated. On this basis, the group eigen value method for service restoration scheme is introduced based on the Perron-Frobenius theorem. And the numerical method is used to calculate the vector of the idealized experts comprehensive evaluation X*, namely to obtain the preferred sequence of service restoration schemes. A case study on the six-feeder distribution network indicates that the proposed method can give a rapid and efficient group decision-making for service restoration.

Wavelet analysis and electric power market E-commerce

The outlines principle from Fourier transform to wavelet analysis technology including Fourier transform, short time Fourier transform, continuous wavelet transform, discrete wavelet transform are presented. Based on this, a E-commerce model applied in electric power market is investigated, in this model, wavelet analysis can be applied to solve series problems. So, wavelet based power system signal denoises and compression techniques, wavelet based security attestation techniques, wavelet based data mining and information fusion techniques, wavelet based loads forecasting and electricity price forecasting techniques, wavelet neural networks based data mining and information fusion techniques are discussed.

Fuzzy RBF neural network control for networked control systems based on modified Smith predictor

Network delay highly degrades the control performance of networked control systems (NCS). Aiming to random and uncertain network delay, time-variant or nonlinear controlled plant and imprecise Smith predictor models, a novel approach is proposed that modified Smith predictor combined with fuzzy radial basis function neural network (FRBFNN). This approach can identify the controlled plant on-line, timely adjusts the weights of the adaptive controller. Because modified Smith predictor does not include network delays, therefore, it is no need for measuring, identifying or estimating network delays on-line. It is applicable to some occasions that network delays are larger than one, even tens of sampling periods. Based on CSMA/CD (Ethernet) and CSMA/AMP (CAN Bus), the simulation results show that modified Smith dynamic predictor combined with FRBFNN is effective.

A study of wavelet entropy measure definition and its application for fault feature pick-up and classification

Shannon entropy in time domain is a measure of signal or system uncertainty. When based on spectrum entropy, Shannon entropy can be taken as a measure of signal or system complexity. Therefore, wavelet analysis based on wavelet entropy measure can signify the complexity of non-steady signal or system in both time and frequency domain. _In this paper, in order to meet the requirements of post-analysis on abundant wavelet transform result data and the need of information mergence, the basic definition of wavelet entropy measure is proposed, corresponding algorithms of several wavelet entropies, such as wavelet average entropy, wavelet time-frequency entropy, wavelet distance entropy, etc. are put forward, and the physical meanings of these entropies are analyzed as well. The application principle of wavelet entropy measure in ElectroEncephaloGraphy (EEG) signal analysis, mechanical fault diagnosis, fault detection and classification in power system are analyzed. Finally, take the transmission line fault detection in power system for example, simulations in two different systems, a 10kV automatic blocking and continuous power transmission line and a 500kV Extra High Voltage (EHV) transmission line, are carried out, and the two methods, wavelet entropy and wavelet modulus maxima, are compared, the results show feasibility and application prospect of the six wavelet entropies.

Discrimination of Inrush Current Based on Dynamic Magnetizing Inductance Solved by Sinusoid Approximation of Instantaneous Signal

For a long time, the discrimination of the inrush current for power transformer is a perplexing problem. In this paper, a new method used to distinguish the inrush current from the inner fault is proposed. Based on sinusoid approximation of instantaneous signal (SAIS), the dynamic magnetizing inductance in the power transformer can be calculated, whose validity is illuminated with two emulating models. With the character of calculated dynamic magnetizing inductance, distinguishing the inrush current from the short circuit between turns can be processed.

The research of heterogeneous networked control systems based on modify Smith predictor and fuzzy adaptive control

Fuzzy control is simple in design, and has strong robustness. It can obtain ideal control effect in the case of not firmly knowing the system model, and can be applied to many nonlinear systems. In order to effectively restrain the impact of network delays for networked control systems (NCS), a novel approach is proposed that modified Smith predictor combined with fuzzy adaptive PID control for the heterogeneous networked control systems (HNCS). The HNCS adopt the cascade control system structure, use P control in the inner loop and fuzzy adaptive control in the outer loop. The data communications of loops adopt heterogeneous wired networks. Based on modified Smith predictor, achieve complete compensations for delays of networks and controlled plants. Because modified Smith predictor does not include network delay models, it is no need for measuring, identifying or estimating network delays on line. Therefore it is applicable to occasions that network delays are larger than one, even tens of sampling periods. Based on CSMA/AMP (CAN bus) in the inner loop and CSMA/CD (Ethernet) in the outer loop, and there are data packets loss, the results of simulation show validity of the control scheme, and can improve dynamic performance, enhance robustness, self-adaptability and anti-jamming abilities.

A distributed remote simulation system for electric power supply system of subway

In this paper we present an approach to build up a simulation system for power supply system of subway on the World Wide Web based on a distributed processing architecture. There are several advantages to this approach. First of all, users can employ this tool through a Web browser without any investment in maintenance of expensive hard- and software at the client-side. Secondly, since multiple processing units are available, the average response time of each job is reduced with respect to an environment with a single processing unit. By using object oriented technology in modeling and software developing and ADS technology in the system structure and communication, the software and hardware of the simulation system can be easy expanded and cut out.

Combining OPC with autonomous decentralized systems

Autonomous Decentralized System (ADS), which has the characteristics of on-line maintainability, on-line expandability and fault-tolerance, has been used successfully in many distributed computing domains. And OPC (OLE for Process Control), which provides us with a standard interface for process control with advantage of openness, interoperability, speed, efficiency, harmony, easy modification and maintenance, has been used in many industrial control areas since 1996. In this paper, OPC is combined with ADS into the same computer control system. Under this architecture, computer control system obtains the respective benefits of the two technology.

Applying neural networks in adaptive distance protection

Classic distance relaying measures the apparent impedance of the transmission line. Fault resistance and the remote source infeed to the fault branch significantly modifies the apparent impedance, which causes a possible overreach or underreach error. The error is influenced by the actual power system conditions so that it is difficult to select a universal operating characteristic. In this paper we show how neural networks can be designed to achieve adaptive distance relaying for the above problem. A realistic, complicated 500 kV system is considered. The research is concentrated on designing, training and testing of the neural distance relays for line-to-ground faults.