The Similar Structures and Control Problems of Complex Systems

In this paper, the naturally evolving complex systems, such as biotic and social ones, are considered. Focusing on their structures, a feature is noteworthy, i.e., the similarity in structures. The relations between the functions and behaviors of these systems and their similar structures will be studied. Owing to the management of social systems and the course of evolution of biotic systems may be regarded as control processes, the researches will be within the scope of control problems. Moreover, since it is difficult to model for biotic and social systems, it will start with the control problems of complex systems, possessing similar structures, in engineering. The obtained results show that for either linear or nonlinear systems and for a lot of control problems similar structures lead to a series of simplifications. In general, the original system may be decomposed into reduced amount of subsystems with lower dimensions and simpler structures. By virtue of such subsystems, the control problems of original system can be solved more simply. At last, it turns round to observe the biotic and social systems and some analyses are given.

Management and Control of Outsourcing in Dispersed Network Manufacturing Systems

The trend of economic globalisation and advances in i nformation technology has led to the emergence of dispersed manufacturing system s as a form of the virtual organisation. New manufacturing strategy pays more at tention to the management of the total value chain and therefore puts emphasis o n outsourcing. In fact, outsourcing is an efficient way of utilizing available r esources and has become one key aspect of the manufacturing strategy. Improved d ecision and organization on outsourcing will result in cost production and short er lead-times. However, most concepts and practice of traditional outsourcing do not adapt to t he changing environment and meet increasing performance requirements. On the oth er hand, virtual organisations might display instability between pure outsourcin g and establishing alliance. Balance and trade-off between independent agents a nd creating alliance are thus required. Therefore, the purpose of this paper is to develop a model to support decision-making, management and control on outsou rcing in a dispersed network manufacturing system and to discuss several key iss ues that are relevant to the relationship between the agents of the network. Dev elopment of the model will deploy Applied System Theory and will be built on fou ndations of earlier research on industrial management such the theories of Outso urcing, Order Entry Points, Design of Organisations and Logistic Control. The is sues that will be addressed in this paper are: · The selection of suppliers and co-makers; · Communication between suppliers and clients; · The mechanisms for profit-sharing between agents; · The product data management to integrate the knowledge of the different agent s into product design. Industrial companies will benefit from this research by the practical methods an d implementation extending their business models beyond concepts for outsourcing and alliances. Additionally, the exploration will lead to proactive contributio n of manufacturing during engineering, which would improve management and contro l of dispersed manufacturing systems.

Special Issue on New Trends in Theory and Applications of Complex Control Systems

Complexity is one of the leading features of modem control systems. It is caused by the complex properties of controlled plants and the varied requirements in controller designs. In dealing with the control problems with complexity, in the past two decades, a lot of papers have been published that reported fruitful results on different theoretical backgrounds and with different methodologies, such as differential geometry-based design methods, hybrid system theory, switching control, neural network-based intelligent control, etc.

Research on Technological Support System of Control and Management of Rural Tourism Safety

As the sources of overt and covert potential safety hazards were widespread, the safety control and management of rural tourism became more complicated and difficult, which required more for technological support of rural tourism safety management. Based on the latitude of technological support, from the perspective of management practice of rural tourism safety, through analysis on inner symbiosis of management and technological support of rural tourism safety, the paper had studied three parts of control and management system of rural tourism safety, which were rural tourism safety identification, rural tourism safety isolation and control, and rural tourism safety treatment and solution; and the connotation of technological support during safety management had been discussed from the three aspects. It hoped to serve as reference for tourism safety management and control, so as to promote healthy, stable and sustainable development of tourism.

Research Progress of Parallel Control and Management

Based on ACP(artificial systems,computational experiments,and parallel execution)methodology,parallel control and management has become a popularly systematic and complete solution for the control and management of complex systems.This paper focuses on summarizing comprehensive review of the research literature of parallel control and management achieved in the recent years including the theoretical framework,core technologies,and the application demonstration.The future research,application directions,and suggestions are also discussed.

Decentralized Variable Structure Control of Complex Giant Singular Uncertainty Systems

This paper, at the first time, considers the problem of decentralized variable structure control of complex giant singular uncertainty systems by using the property of diagonally dominant matrix and Frobenius-Person theorem. The splendid selection of switching manifold for each subsystem makes the design relatively straightforward and can be easily realized. An illustrate example is given.

Structure identification of an uncertain network coupled with complex-variable chaotic systems via adaptive impulsive control

In this paper, structure identification of an uncertain network coupled with complex-variable chaotic systems is in- vestigated. Both the topological structure and the system parameters can be unknown and need to be identified. Based on impulsive stability theory and the Lyapunov function method, an impulsive control scheme combined with an adaptive strategy is adopted to design effective and universal network estimators. The restriction on the impulsive interval is relaxed by adopting an adaptive strategy. Further, the proposed method can monitor the online switching topology effectively. Several numerical simulations are provided to illustrate the effectiveness of the theoretical results.

Lyapunov-Based Dynamic Neural Network for Adaptive Control of Complex Systems

In this paper, an adaptive neuro-control structure for complex dynamic system is proposed. A recurrent Neural Network is trained-off-line to learn the inverse dynamics of the system from the observation of the input-output data. The direct adaptive approach is performed after the training process is achieved. A lyapunov-Base training algorithm is proposed and used to adjust on-line the network weights so that the neural model output follows the desired one. The simulation results obtained verify the effectiveness of the proposed control method.

The Development of the Production Management and Control System for 10th Assembly Workshop under XAC-CIMS

This paper gives brief introduction to the production management and control system (PMCS) for 10th assembly workshop under Xi’ an Aircraft Company (XAC)--CIMS. Its user requirements 9 structure, ftinctions, and implementation are described. It is showed that the development problems of PMCS can be further reduced to a development methodology for Chinese enterprises, which will make them competitive.

Robust Resource Management Control for CO2 Emission and Reduction of Greenhouse Effect: Stochastic Game Approach

With the increasingly severe global warming, investments in clean technology, reforestation and political action have been studied to reduce CO2 emission. In this study, a nonlinear stochastic model is proposed to describe the dynamics of CO2 emission with control inputs: clean technology, reforestation and carbon tax, under stochastic uncertainties. For the efficient resources management, a robust tracking control is designed to force resources tracking a desired reference output. The worst-case effect of stochastic parametric fluctuations, external disturbances and uncertain initial conditions on the tracking performance is considered and minimized from the dynamic game theory perspective. This stochastic game problem, in which one player (stochastic uncertainty) maximizes the tracking error and another player (control input) minimizes the tracking error, could be equivalent to a robust minimax tracking problem. To avoid solving the HJI, a fuzzy model is proposed to approximate the nonlinear CO2 emission model. Then the nonlinear stochastic game problem could be easily solved by fuzzy stochastic game approach via LMI technique.

Recent Progress in Reinforcement Learning and Adaptive Dynamic Programming for Advanced Control Applications

Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and its applications to various advanced control fields. First, the background of the development of ADP is described, emphasizing the significance of regulation and tracking control problems. Some effective offline and online algorithms for ADP/adaptive critic control are displayed, where the main results towards discrete-time systems and continuous-time systems are surveyed, respectively.Then, the research progress on adaptive critic control based on the event-triggered framework and under uncertain environment is discussed, respectively, where event-based design, robust stabilization, and game design are reviewed. Moreover, the extensions of ADP for addressing control problems under complex environment attract enormous attention. The ADP architecture is revisited under the perspective of data-driven and RL frameworks,showing how they promote ADP formulation significantly.Finally, several typical control applications with respect to RL and ADP are summarized, particularly in the fields of wastewater treatment processes and power systems, followed by some general prospects for future research. Overall, the comprehensive survey on ADP and RL for advanced control applications has d emonstrated its remarkable potential within the artificial intelligence era. In addition, it also plays a vital role in promoting environmental protection and industrial intelligence.

Engineering complex systems applied to risk management in the mining industry

Related to complexity, there is a wide diversity of concepts, ranging from ‘‘systemic" to ‘‘complex", implying a need for a unified terminology. Per different authors, the main drivers of complexity can be found in human behaviour and uncertainty. This complexity, structural or dynamic can be organizational, technological, or nested in their relationship. ISO international standard 31000:2009 definition of risk management ‘‘coordinated activities to direct and control an organization with regard to risk", when applied to economic sectors, industry, services, project, or activity, it requires the use of models or theories as guidelines. Therefore, as its basic elements comprehend human behaviour and/or uncertainty, risk management to be effective and adapted as much as possible to reality, must be operational within complex systems, as already demonstrated in different R&D environments. Risk management faces demanding challenges when approaching specific and endogenous needs, such as the mining sector. This paper presents a multivariable function analysis methodology approach based on complex system modelling and through real data corresponding to a risk management tool in the mining sector.

Parameter Estimation and Topology Identification of Uncertain General Fractional-order Complex Dynamical Networks with Time Delay

Complex networks have attracted much attention from various fields of sciences and engineering in recent years. However, many complex networks have various uncertain information, such as unknown or uncertain system parameters and topological structure, which greatly affects the system dynamics. Thus, the parameter estimation and structure identification problem has theoretical and practical importance for uncertain complex dynamical networks. This paper investigates identification of unknown system parameters and network topologies in uncertain fractional-order complex network with time delays (including coupling delay and node delay). Based on the stability theorem of fractional-order differential system and the adaptive control technique, a novel and general method is proposed to address this challenge. Finally two representative examples are given to verify the effectiveness of the proposed approach. © 2014 Chinese Association of Automation.

En-route Sector Complexity Control Strategies in Air Traffic Management

Along with the rapid development of air traffic, the contradiction between conventional air traffic management(ATM)and the increasingly complex air traffic situations is more severe,which essentially reduces the operational efficiency of air transport systems. Thus,objectively measuring the air traffic situation complexity becomes a concern in the field of ATM. Most existing studies focus on air traffic complexity assessment,and rarely on the scientific guidance of complex traffic situations. According to the projected time of aircraft arriving at the target sector boundary,we formulated two control strategies to reduce the air traffic complexity. The strategy of entry time optimization was applied to the controllable flights in the adjacent upstream sectors. In contrast,the strategy of flying dynamic speed optimization was applied to the flights in the target sector. During the process of solving complexity control models,we introduced a physical programming method. We transformed the multi-objective optimization problem involving complexity and delay to single-objective optimization problems by designing different preference function. Actual data validated the two complexity control strategies can eliminate the high-complexity situations in reality. The control strategy based on the entry time optimization was more efficient than that based on the speed dynamic optimization. A basic framework for studying air traffic complexity management was preliminarily established. Our findings will help the implementation of a complexity-based ATM.

Low-Cost Embedded Controller for Complex Control Systems

Because of limited resource of embedded platforms, the computational complexity of advanced control algorithms raises significant challenges for the use of embedded systems in complex control field. A Scilab/Scicos based embedded controller is developed on which various control software can be easily modeled, simulated, implemented, and evaluated to meet the ever-expanding requirements of industrial control applications. Built on the Cirrus Logic EP9315 ARM systems-on-chip board, this embedded controller is possible to develop complex embedded control systems that employ advanced control strategies in a rapid and cost-efficient fashion. Due to the free and open source nature of the software packages used, the cost of the embedded controller is minimized.

A Novel Evolutionary-Fuzzy Control Algorithm for Complex Systems

This paper presents an adaptive fuzzy control scheme based on modified genetic algorithm. In the control scheme, genetic algorithm is used to optimze the nonlinear quantization functions of the controller and some key parameters of the adaptive control algorithm. Simulation results show that this control scheme has satisfactory performance in MIMO systems, chaotic systems and delay systems.

Hybrid Power Systems Energy Controller Based on Neural Network and Fuzzy Logic

This paper presents a novel adaptive scheme for energy management in stand-alone hybrid power systems. The proposed management system is designed to manage the power flow between the hybrid power system and energy storage elements in order to satisfy the load requirements based on artificial neural network (ANN) and fuzzy logic controllers. The neural network controller is employed to achieve the maximum power point (MPP) for different types of photovoltaic (PV) panels. The advance fuzzy logic controller is developed to distribute the power among the hybrid system and to manage the charge and discharge current flow for performance optimization. The developed management system performance was assessed using a hybrid system comprised PV panels, wind turbine (WT), battery storage, and proton exchange membrane fuel cell (PEMFC). To improve the generating performance of the PEMFC and prolong its life, stack temperature is controlled by a fuzzy logic controller. The dynamic behavior of the proposed model is examined under different operating conditions. Real-time measured parameters are used as inputs for the developed system. The proposed model and its control strategy offer a proper tool for optimizing hybrid power system performance, such as that used in smart-house applications.

Design and Reliability Analysis of DP-3 Dynamic Positioning Control Architecture

As the exploration and exploitation of oil and gas proliferate throughout deepwater area, the requirements on the reliability of dynamic positioning system become increasingly stringent. The control objective ensuring safety operation at deep water will not be met by a single controller for dynamic positioning. In order to increase the availability and reliability of dynamic positioning control system, the triple redundancy hardware and software control architectures were designed and developed according to the safe specifications of DP-3 classification notation for dynamically positioned ships and rigs. The hardware redundant configuration takes the form of triple-redundant hot standby configuration including three identical operator stations and three real-time control computers which connect each other through dual networks. The function of motion control and redundancy management of control computers were implemented by software on the real-time operating system VxWorks. The software realization of task loose synchronization, majority voting and fault detection were presented in details. A hierarchical software architecture was planed during the development of software, consisting of application layer, real-time layer and physical layer. The behavior of the DP-3 dynamic positioning control system was modeled by a Markov model to analyze its reliability. The effects of variation in parameters on the reliability measures were investigated. The time domain dynamic simulation was carried out on a deepwater drilling rig to prove the feasibility of the proposed control architecture

A New Thinking of the Objects Served Relationship Management in Complex System

Take a digital libraries＇ service system for example, Objects Served Relationship Management （OSRM） in complex systems is proposed firstly as a new concept, and its connotation is explained. The significances and constructions of OSRM are analyzed. Both the fundamental facts and the important natures that the things which are interested by Objects Served （OS） （e. g. publishers and readers） and the server （e. g. digital libraries are the servers of publishers and readers） will not be the same completely although there are a lot of common benefits between OS and servers, are indeed clarified. The valuable information,which should be used by OS and their server, is often hidden behind them. Thus, how to find, manage and control the relationship among OS and their servers is very necessary and important for the common benefits among all of them.（e. g. the three dimensions of OSRM in digital library system and its overall framwork are proposed. The different strategies to different cases in the digital library＇s multidimensional framework are analyzed.）

Local Government Asset Management:Affecting Factors and Policy Implications on Government Work Unit of Central Java Province in Indonesia

This study aims to analyze the influence of Human Resource Competence,Regulation,Information Technology,Reconciliation,and Internal Control System on Asset Management in Local Government Work Unit(abbreviated SKPD)of Central Java Provincial Government.This research is conducted because there is still record in the Final Report of Inspection by the Republic of Indonesia Audit Board(abbreviated BPK)concerning problem of asset management conducted by some SKPDs of Central Java Provincial Government,although in general the Local Government Financial Report of Central Java Province has got opinion“Reasonable Without Exception”.The data source of this research is primary data collected through interview method on asset management officers at the 48 SKPD in Central Java Provincial Government.Data analysis method used in this research is multiple regression analysis.This research finds that the Human Resource Competence,the Regulation,the Information Technology,the Reconciliation,and the Internal Control System have positive and significant effect on the Asset Management at the Local Government Work Unit of Central Java Provincial Government at level of significance 0.05.Ability to explain of the independent variables to the Asset Management variable is equal to 67.7%.