Design of a common observer for two linear systems with unknown inputs

This paper considers the design of a common linear functional observer for two linear time-invariant systems with unknown inputs. A structure for a common observer which only uses the available output information is proposed. Here, for the proposed structure, we show that the simultaneous functional observation problem of two plants is reduced to a problem of designing two observers: the first is a full-order unknown input observer of one of the two systems; the second observer is a common unknown input observer of a system comprises two-connected systems. In general, the existence conditions for the second observer are very difficult to satisfy. This paper thus concludes that it is indeed very difficult to find a common observer for two linear systems with unknown inputs.

Observer-based control of multi-agent systems under decentralized information structure

This paper addresses the problem of decentralized implementation of a global state feedback controller for multi-agent systems. The system is assumed to be under the constraint of a complete decentralized information structure. The decentralization of the control task is achieved through the construction of low-order decentralized functional observers with the purpose of generating the required corresponding control signal for each local control station. A design procedure is developed for obtaining an approximate solution to the design of the observers. Stability analysis is provided for the global system using the proposed observer-based approach. A numerical example is given to illustrate the design procedure and cases when the observers' order increases from the lowest value.

State and input simultaneous estimation for a class of time-delay systems with uncertainties

This brief addresses the problem of estimation of both the states and the unknown inputs of a class of systems that are subject to a time-varying delay in their state variables, to an unknown input, and also to an additive uncertain, nonlinear disturbance. Conditions are derived for the solvability of the design matrices of a reduced-order observer for state and input estimation, and for the stability of its dynamics. To improve computational efficiency, a delay-dependent asymptotic stability condition is then developed using the linear matrix inequality formulation. A design procedure is proposed and illustrated by a numerical example.

Taxonomy and survey of location management systems

In wireless mobile computing, location management is introduced whenever users move from one place to another. In order to track a mobile user, the system must store information about their current location and report new locations to a home base station. Numerous techniques have been proposed to optimally manage the location of mobile hosts in mobile networks. This paper attempts to present a more structured and comprehensive analysis of the current location management techniques architectures and their technology enablers. We discuss some of the principal issues involved in location management and present a taxonomy and survey of location management strategies that have been proposed in the literature over the years for mobile computing systems.

On the existence and design of functional observers for linear systems

Darouach [1] recently derived necessary and sufficient conditions for the existence and stability of functional observers with an order, p, equals to the dimension m of the vectors to be estimated. In general, these conditions are difficult to satisfy and when they are not, the only available option is to increase the order of the functional observers. This note presents new conditions for the existence of a general pth-order functional observer. Systematic procedures for the synthesis of reduced-order functional observers are given. A numerical example is given to illustrate the design procedures.

Design of linear functional observers for time-delay systems of the neutral-type

This paper presents the design of reduced-order linear functional observers for a class of linear time-delay systems of the neutral-type. The type of the observer proposed in this paper is without internal delay and its order is the same as the number of linear functions to be estimated. First, conditions for the existence of the reduced-order functional observers that are capable of asymptotically estimating any given function of the state vector are derived. Then, based on the newly derived existence conditions, a procedure is given for the determination of the observer parameters. The results derived in this paper include a range of linear systems and extend some existing results of linear functional observers to linear neutral delay systems. A numerical example is given to illustrate the design procedure.

The welfare economics of measuring sustainability: a new approach based on social choice theory and systems analysis

This paper presents a new measure of sustainability within a welfare economics framework. Gross domestic product (GDP) can be used as an indicator of sustainability if the GDP estimates are undertaken within a cost-benefit analysis framework based on social choice perspectives. Sustainability is dependent on a healthy and functioning socio-economic and environmental (SEE) system. Economic development can damage the SEE system through resource degradation, over-harvesting and pollution. This paper addresses the tensions between economic development and sustainability by undertaking a number of SEE-based adjustments to GDP based on social choice perspectives in order to measure sustainability. These adjustments include the environmental and social costs caused by economic development such as water pollution, the depletion of non-renewable resources, and deforestation. Thailand is used as a case study for a 25 year period (1975-1999). The results show a divergence in terms of GDP per capita and the SEE-adjusted GDP per capita figure. The paper concludes that, with increasing environmental and social costs of economic development, pursuing such extreme high growth objectives without due environmental and social considerations can threaten present social welfare and future sustainability. Copyright © 2005 John Wiley & Sons, Ltd and ERP Environment.

Robust strictly positive real synthesis of polynomial segments for discrete time systems

By using the result of robust strictly positive real synthesis of polynomial segments for continuous time systems, it is proved that, for any two n-th order polynomials a(z) and b(z), the Schur stability of their convex combination is necessary and sufficient for the existence of an n-th order polynomial c(z) such that c(z)/a(z) and c(z)/b(z) are both strictly positive real. We also provide the construction method of c(z). Illustrative examples are provided to show the effectiveness of this method.

Disturbance decoupled observers for systems with unknown inputs

This note deals with the design of reduced-order disturbance decoupled scalar functional observers for linear systems with unknown inputs. Based on a parametric approach, existence conditions are derived and a design procedure for finding reduced-order scalar functional observers is given. The derived existence conditions are relaxed and the procedure can find first-order disturbance decoupled scalar functional observers for some cases where the number of unknown inputs is more than the number of outputs. Also, the observer matching condition, which is the necessary requirement for the design of state observers for linear systems with unknown inputs, is not required. Numerical examples are given to illustrate the attractiveness of the proposed design method.

Predictive mapping of powerful owl (Ninox strenua) breeding sites using Geographical Information Systems (GIS) in urban Melbourne, Australia

Urban expansion is a principal process threatening biodiversity globally. It is predicted that over half of the world's population will reside in urban centres by 2010. If we are to conserve biodiversity, a shift in perspective from traditional ecological studies based in natural environments, to studies based in less natural environments is paramount. To effectively conserve species which occur in urban environments, comprehensive analysis is necessary to determine the processes that are driving this urban usage. Geographical Information Systems (GIS) technology provides a valuable tool for efficient spatial analysis and predictive mapping of species distributions.

This study used GIS to analyze current breeding sites for the powerful owl, a vulnerable top order predator in urban Melbourne, Australia. GIS analysis suggests that a number of ecological attributes were influencing powerful owl usage of urban environments. Using these ecological attributes, predictive mapping was undertaken, which identified a number of potential breeding sites for powerful owls within urbanized Melbourne.

Urban environments are traditionally perceived as “the wastelands” of natural environments, however, this study demonstrates that they have the potential to support apex predators, an important finding for the management of rare and threatened species.

Protecting information systems from DDoS attack using multicore methodology

Previous work, in the area of defense systems has focused on developing a firewall like structure, in order to protect applications from attacks. The major drawback for implementing security in general, is that it affects the performance of the application they are trying to protect. In fact, most developers avoid implementing security at all. With the coming of new multicore systems, we might at last be able to minimize the performance issues that security places on applications. In our bodyguard framework we propose a new kind of defense that acts alongside, not in front, of applications. This means that performance issues that effect system applications are kept to a minimum, but at the same time still provide high grade security. Our experimental results demonstrate that a ten to fifteen percent speedup in performance is possible, with the potential of greater speedup.

Applications and prototype for systems of systems swarm robotics

In order to develop a robotic system of systems the robotic platforms must be designed and built. For this to happen, the type of application involved should be clear. Swarm robots need to be self contained and powered. They must also be self governing. Here the authors examine various applications and a prototype robot that may be useful in these scenarios.

Evaluating the triple bottom line in the implementation of photovoltaic systems in UK social housing

The Intergovernmental Panel on Climate Change warnings regarding the detrimental effects of carbon dioxide emissions and global warming have gained acceptance amongst many governments (IPCC 2001). The UK government has agreed to reduce emissions, implement a package of enabling measures (UKCCP 2000) and issued an Energy White Paper (HMSO 2003) calling for a diversification of energy supply policies which will include renewable sources.

Housing accounts for approximately 25% of UK CO2 emissions and as providers of social housing, Registered Social Landlords (RSLs) and their tenants are major contributors. RSLs are deliverers of national policy in several areas and contribute to the attainment of governmental environmental, social and economic targets and impact upon the wider demands of housing policy, healthcare, education and law & order (DETR 1999, Cole and Shayer 1998).

Photovoltaic (PV) electricity generation could deliver “free” electricity to the low income households historically housed by RSLs. PV helps address such issues as fuel poverty and could be used as a stimulus for creating interest in areas of low demand for social housing.

RSLs provide housing solutions which cross traditional economic, social and environmental divides and this lends their modus operandi to the concept of the triple bottom line. The triple bottom line enables social and environmental aspects to be considered alongside economic considerations within decision-making frameworks (Elkington 1999, Andreason 1995).

Using a qualitative research methodology, this paper assesses current commercial viability of PV installations on RSL developments and identifies key barriers to implementation. The paper also investigates whether the application of the triple bottom line can liberate RSLs from viewing PV as a non-viable option by enabling a greater emphasis to be placed on the social & environmental aspects of PV. The paper considers whether a framework for RSLs to improve their decision-making processes by embracing social & environmental factors is feasible.

Intelligent assistant to re-configure parameter-driven systems

Parameter-Driven Systems (PDS) are widely used in commerce for large-scale applications. Reusability is achieved with a PDS design by relocating implicit control structures in the software and the storage of explicit data in database files. This approach can accommodate various user requirements without tedious modification of the software. In order to specify appropriate parameters in a system, knowledge of both business activities and system behaviour are required. For large, complex software packages, this task becomes time consuming and requires specialist knowledge, yet the consistency and correctness still cannot be guaranteed. My research studied the types of knowledge required and agents involved in the PDS customisation. The work also identified the associated problems and constraints. A solution is proposed and implemented as an Intelligent Assistant prototype than a manual approach. Three areas of achievement have been highlighted: 1. The characteristics and problems of maintaining parameter instances in a PDS are defined. It is found that the verification is not complete with the technical/structural knowledge alone, but a context is necessary to provide semantic information and related business activities (thus the implemented parameters) so that mainline functions can relate with each other. 2. A knowledge-based modelling approach has been proposed and demonstrated via a practical implementation. A Specification Language was designed which can model various types of knowledge in a PDS and encapsulate relationships. The Knowledge-Based System (KBS) developed verifies parameters based on the interpreted model of a given context. 3. The performance of the Intelligent Assistant prototype was well received by the domain specialist from the participating organisation. The modelling and KBS approach developed in my research offers considerable promise in solving practical problems in the software industry.

Fuzzy neural networks for control of dynamic systems

This thesis provides a unified and comprehensive treatment of the fuzzy neural networks as the intelligent controllers. This work has been motivated by a need to develop the solid control methodologies capable of coping with the complexity, the nonlinearity, the interactions, and the time variance of the processes under control. In addition, the dynamic behavior of such processes is strongly influenced by the disturbances and the noise, and such processes are characterized by a large degree of uncertainty. Therefore, it is important to integrate an intelligent component to increase the control system ability to extract the functional relationships from the process and to change such relationships to improve the control precision, that is, to display the learning and the reasoning abilities. The objective of this thesis was to develop a self-organizing learning controller for above processes by using a combination of the fuzzy logic and the neural networks. An on-line, direct fuzzy neural controller using the process input-output measurement data and the reference model with both structural and parameter tuning has been developed to fulfill the above objective. A number of practical issues were considered. This includes the dynamic construction of the controller in order to alleviate the bias/variance dilemma, the universal approximation property, and the requirements of the locality and the linearity in the parameters. Several important issues in the intelligent control were also considered such as the overall control scheme, the requirement of the persistency of excitation and the bounded learning rates of the controller for the overall closed loop stability. Other important issues considered in this thesis include the dependence of the generalization ability and the optimization methods on the data distribution, and the requirements for the on-line learning and the feedback structure of the controller. Fuzzy inference specific issues such as the influence of the choice of the defuzzification method, T-norm operator and the membership function on the overall performance of the controller were also discussed. In addition, the e-completeness requirement and the use of the fuzzy similarity measure were also investigated. Main emphasis of the thesis has been on the applications to the real-world problems such as the industrial process control. The applicability of the proposed method has been demonstrated through the empirical studies on several real-world control problems of industrial complexity. This includes the temperature and the number-average molecular weight control in the continuous stirred tank polymerization reactor, and the torsional vibration, the eccentricity, the hardness and the thickness control in the cold rolling mills. Compared to the traditional linear controllers and the dynamically constructed neural network, the proposed fuzzy neural controller shows the highest promise as an effective approach to such nonlinear multi-variable control problems with the strong influence of the disturbances and the noise on the dynamic process behavior. In addition, the applicability of the proposed method beyond the strictly control area has also been investigated, in particular to the data mining and the knowledge elicitation. When compared to the decision tree method and the pruned neural network method for the data mining, the proposed fuzzy neural network is able to achieve a comparable accuracy with a more compact set of rules. In addition, the performance of the proposed fuzzy neural network is much better for the classes with the low occurrences in the data set compared to the decision tree method. Thus, the proposed fuzzy neural network may be very useful in situations where the important information is contained in a small fraction of the available data.