Identification and Control of Dynamical Systems Using Modified Neural Networks

Aim To study the identification and control of nonlinear systems using neural networks. Methods A new type of neural network in which the dynamical error feedback is used to modify the inputs of the network was employed to reduce the inherent network approximation error. Results A new identification model constructed by the proposed network and stable filters was derived for continuous time nonlinear systems, and a stable adaptive control scheme based on the proposed networks was developed. Conclusion Theory and simulation results show that the modified neural network is feasible to control a class of nonlinear systems.

Integrated automatic HAZOP analysis and fault diagnosis based on Petri net

Based on systematically analyzing the procedure of hazard and operability (HAZOP) study, the author introduces a method of modeling fault diagnosis with the Petri net with fuzzy colors, in which the fuzzy information can be represented effectively in the process of analysis. The author proposes the architecture of a knowledge base, which integrates HAZOP analysis and fault diagnosis, and provides the conditions for constructing the knowledge-based expert system. The author also presents a method of knowledge representation for on-line HAZOP analysis and on-line fault diagnosis is presented based on the technology of Petri net with fuzzy colors, which establishes a technological fundamental for integrating the automatic HAZOP analysis and fault diagnosis.

Multi-objective optimization of water supply network rehabilitation with non-dominated sorting Genetic Algorithm-II

Through the transformation of hydraulic constraints into the objective functions associated with a water supply network rehabilitation problem, a non-dominated sorting Genetic Algorithm-II (NSGA-II) can be used to solve the altered multi-objective optimization model. The introduction of NSGA-II into water supply network optimal rehabilitation problem solves the conflict between one fitness value of standard genetic algorithm (SGA) and multi-objectives of rehabilitation problem. And the uncertainties brought by using weight coefficients or punish functions in conventional methods are controlled. And also by in-troduction of artificial inducement mutation (AIM) operation, the convergence speed of population is accelerated;this operation not only improves the convergence speed, but also improves the rationality and feasibility of solutions.

Fundamental Issues in Networked Control Systems

Abstract--This paper provides a survey on modeling and theories of networked control systems （NCS）. In the first part, modeling of the different types of imperfections that affect NCS is discussed. These imperfections are quantization errors, packet dropouts, variable sampling/transmission intervals, vari- able transmission delays, and communication constraints. Then follows in the second part a presentation of several theories that have been applied for controlling networked systems. These theories include： input delay system approach, Markovian system approach, switched system approach, stochastic system approach, impulsive system approach, and predictive control approach. In the last part, some advanced issues in NCS including decentral- ized and distributed NCS, cloud control system, and co-design of NCS are reviewed. Index Terms--Decentralized networked control systems （NCS）, distributed networked control systems, network constraints, net- worked control system, quantization, time delays.

Synchronization and channel estimation for MIMO OFDM wireless LAN systems

A new preamble structure is designed for wireless LAN based on MIMO OFDM systems, which can be used for both synchronization and channel estimation. Modulatable orthogonal polyphase sequence is utilized in training symbol design regarding its correlation properties. The time synchronization and channel estimation are achieved by measuring the correlation between the received training sequence and the locally generated training sequence. Repeated training symbols are used to get carrier frequency offset （CFO） estimation. It is shown from the analysis that the accuracy of frequency synchronization is close to the Cramer-Rao lower bound. The training sequences are optimal for channel estimation based on the minimum mean square error （MMSE）.

Model Warehouse

This paper puts forward a new conception:model warehouse,analyzes the reason why model warehouse appears and introduces the characteristics and architecture of model warehouse.Last,this paper points out that model warehouse is an important part of WebGIS.

The Design of Internet of Things Smart Home System based on S3C2440 and Zigbee

In order to achieve the smart home system for remote management and wireless transmission function in the smart home networking system design, the article will combined with ARM technology and ZigBee wireless network technology based on samsung＇s $3C2440 chip and some related peripheral devices to form into home gateway of the system control platform, and the home control network using the internal ZigBee wireless network technologies. Practice has proved that the system is stable, is worth promoting.

A Control Scheme Based on Online Delay Evaluation for a Class of Networked Control Systems

A control scheme that integrates control technology with communication technology to solve the delay problem is introduced for a class of networked control systems: Networked Half-Link Systems (NHLS). Concretely, we use the master-slave clock synchronization technology to evaluate the delays online, and then the LQ optimal control based on delays is adopted to stabilize the controlled plant. During the clock synchronization process, the error of evaluated delays is inevitably induced from the clock synchronization error, which will deteriorate the system performances, and even make system unstable in certain cases. Hence, the discussions about the clock error, and the related control analysis and design are also developed. Specifically, we present the sufficient conditions of controller parameters that guarantee the system stability, and a controller design method based on the error of delays is addressed thereafter. The experiments based on a CANbus platform are fulfilled, and the experimental results verify the previous analytic results finally.

Smart Cities as Cyber-Physical Social Systems

The emerging prototype for a Smart City is one of an urban environment with a new generation of inno- vative services for transportation, energy distribution, healthcare, environmental monitoring, business, commerce, emergency response, and social activities. Enabling the technology for such a setting re- quires a viewpoint of Smart Cities as cyber-physical systems （CPSs） that include new software platforms and strict requirements for mobility, security, safety, privacy, and the processing of massive amounts of information. This paper identifies some key defining characteristics of a Smart City, discusses some lessons learned from viewing them as CPSs, and outlines some fundamental research issues that remain largely open.

Web-services-based Integration Design of PDM and DNC Systems

In a networked manufacturing environment, product data integration is the foundation of collaborative manufacturing among manufacturing enterprises. It is very important to build an effective integration mechanism for product data sharing of manufacturing enterprises in geographically dispersed, heterogeneous system platform. In order to integrate enterprise level product data management (PDM) system and shop floor level distributed numerical control (DNC) system, based on the description of Web services technology, a Web-services-based integration approach is presented for facilitating seamless sharing of product data between PDM and DNC systems in a networked manufacturing environment. In order to verify the validity of the proposed approach, an example-based integration development has been implemented with Java 2 Software Development Kit and Java Web Services Developer Pack in Windows 2000 Professional environment.

Stability analysis of discrete-time BAM neural networks based on standard neural network models

To facilitate stability analysis of discrete-time bidirectional associative memory (BAM) neural networks, they were converted into novel neural network models, termed standard neural network models (SNNMs), which interconnect linear dynamic systems and bounded static nonlinear operators. By combining a number of different Lyapunov functionals with S-procedure, some useful criteria of global asymptotic stability and global exponential stability of the equilibrium points of SNNMs were derived. These stability conditions were formulated as linear matrix inequalities (LMIs). So global stability of the discrete-time BAM neural networks could be analyzed by using the stability results of the SNNMs. Compared to the existing stability analysis methods, the proposed approach is easy to implement, less conservative, and is applicable to other recurrent neural networks.

A Web-based machining process monitoring system for E-manufacturing implementation

Recently, with the rapid growth of information technology, many studies have been performed to implement Web-based manufacturing system. Such technologies are expected to meet the need of many manufacturing industries who want to adopt E-manufacturing system for the construction of globalization, agility, and digitalization to cope with the rapid changing market requirements. In this research, a real-time Web-based machine tool and machining process monitoring system is developed as the first step for implementing E-manufacturing system. In this system, the current variations of the main spindle and feeding motors are measured using hall sensors. And the relationship between the cutting force and the spindle motor RMS (Root Mean Square) current at various spindle rotational speeds is obtained. Thermocouples are used to measure temperature variations of important heat sources of a machine tool. Also, a rule-based expert system is applied in order to decide the machining process and machine tool are in normal conditions. Finally, the effectiveness of the developed system is verified through a series of experiments.

New Developments in Maritime Communications： a Comprehensive Survey

This paper summarizes the requirements for modem maritime wireless communication networks in the marine environments including the sea- to-sea and sea-to-shore communication scenarios. The existing maritime wireless communication sys- tems are presented and the development of the state-of-the-art maritime communication systems is surveyed. Furthermore, a hierarchical and integrated maritime network architecture is proposed to satisfy the increasing various classes of services which demand different Quality of Service （QoS）. Finally, the open issues for further development of maritime communications are identified.

Grey series time-delay predicting model in state estimation for power distribution networks

A new combined model is proposed to obtain predictive data value applied in state estimation for radial power distribution networks. The time delay part of the model is calculated by a recursive least squares algorithm of system identification, which can gradually forget past information. The grey series part of the model uses an equal dimension new information model (EDNIM) and it applies 3 points smoothing method to preprocess the original data and modify remnant difference by GM(1,1). Through the optimization of the coefficient of the model, we are able to minimize the error variance of predictive data. A case study shows that the proposed method achieved high calculation precision and speed and it can be used to obtain the predictive value in real time state estimation of power distribution networks.

Actuator fault diagnosis of autonomous underwater vehicle based on improved Elman neural network

Autonomous underwater vehicles(AUV) work in a complex marine environment. Its system reliability and autonomous fault diagnosis are particularly important and can provide the basis for underwater vehicles to take corresponding security policy in a failure. Aiming at the characteristics of the underwater vehicle which has uncertain system and modeling difficulty, an improved Elman neural network is introduced which is applied to the underwater vehicle motion modeling. Through designing self-feedback connection with fixed gain in the unit connection as well as increasing the feedback of the output layer node, improved Elman network has faster convergence speed and generalization ability. This method for high-order nonlinear system has stronger identification ability. Firstly, the residual is calculated by comparing the output of the underwater vehicle model(estimation in the motion state) with the actual measured values. Secondly, characteristics of the residual are analyzed on the basis of fault judging criteria. Finally, actuator fault diagnosis of the autonomous underwater vehicle is carried out. The results of the simulation experiment show that the method is effective.

Implementation of Embedded Ethernet Based on Hardware Protocol Stack in Substation Automation System

Embedded Ethernet technology has been utilized increasingly widely as the communication mode in the substation automation system(SAS).This paper introduces the current applying situation about embedded Ethernet in SAS First.After analyzing the protocol levels used in SAS based on embedded Ethernet and the differences between the TCP and UDP,UDP/IP is selected as the communication protocol between the station-level and bay-level devices for its real-time characteristic.Then a new kind of implementation of the embedded Ethernet is presented based on hardware protocol stack.The designed scheme can be implemented easily,reduce cost significantly and shorten developing cycle.

Consistency and Asymptotic Property of a Weighted Least Squares Method for Networked Control Systems

In this paper, we study the problems related to parameter estimation of a single-input and single-output networked control system, which contains possible network-induced delays and packet dropout in both of sensor-to-controller path and controller-to-actuator path. A weighted least squares(WLS) method is designed to estimate the parameters of plant, which could overcome the data uncertainty problem caused by delays and dropout. This WLS method is proved to be consistent and has a good asymptotic property. Simulation examples are given to validate the results.

Admission control with long-range dependence traffic input

The admission control scheme is investigated for a FIFO self-similar queuing system with Quality of Service (QoS) performance guarantees. Since the self-similar queuing system performance analysis is often carried out under the condition of infinite buffer, it is difficult to deduce the upper boundary of buffer overflow probability. To overcome this shortcoming, a simple overflow condition is proposed, which defines a buffer overflow occurrence whenever the arrival rate exceeds the service rate. The analytic formula for the buffer overflow probability upper boundary is easily obtained under this condition. The required bandwidth upper boundary with long-range dependence input and determined overflow probability is then derived from this formula. Based on the above analytic formulas, the upper boundaries of the admission control regions for homogeneous and heterogeneous long-range dependence traffic sources are separately obtained. Finally, an effective admission control scheme for long-range dependence input is proposed. Simulation studies with real traffic have confirmed the validity of these results.

Allocation of congestion relief cost based on flow change on the congested facilities

Congestion management in an electricity market is introduced in this paper and a new method of allocating congestion cost to transactions is proposed. The proposed method is a two-step process, in which the total congestion cost is firstly allocated to congested facilities and then to each transaction involved. The cost of relieving a congested facility allocated to each transaction is proportional to the power flow change on the congested facility caused by the transaction. The more the power flow change is on the congested facility caused by the transaction, the deeper the degree of involvement by the transaction. Therefore, cutting down the magnitudes of such transactions contributes to relieving congestion. Test results on a 5-bus system indicate that the proposed method can reflect reasonably the degree of involvement by each transaction in the congestion and provide correct price signals contributing to relieving congestion.