Genie:supporting the model driven development of reflective, component-based adaptive systems

Engineering adaptive software is an increasingly complex task. Here, we demonstrate Genie, a tool that supports the modelling, generation, and operation of highly reconfigurable, component-based systems. We showcase how Genie is used in two case-studies: i) the development and operation of an adaptive flood warning system, and ii) a service discovery application. In this context, adaptation is enabled by the Gridkit reflective middleware platform.

Sustainability of systems interoperability in dynamic business networks

Dissertação para obtenção do Grau de Doutor em Engenharia Electrotécnica e de Computadores

In-line rheo-optical microstructural characterization of complex polymer systems

Tese de Doutoramento em Ciência e Engenharia de Polímeros e Compósitos.

Method to assess and optimise dependability of complex macro-systems: application to a railway signalling system

Achieving a high degree of dependability in complex macro-systems is challenging. Because of the large number of components and numerous independent teams involved, an overview of the global system performance is usually lacking to support both design and operation adequately. A functional failure mode, effects and criticality analysis (FMECA) approach is proposed to address the dependability optimisation of large and complex systems. The basic inductive model FMECA has been enriched to include considerations such as operational procedures, alarm systems. environmental and human factors, as well as operation in degraded mode. Its implementation on a commercial software tool allows an active linking between the functional layers of the system and facilitates data processing and retrieval, which enables to contribute actively to the system optimisation. The proposed methodology has been applied to optimise dependability in a railway signalling system. Signalling systems are typical example of large complex systems made of multiple hierarchical layers. The proposed approach appears appropriate to assess the global risk- and availability-level of the system as well as to identify its vulnerabilities. This enriched-FMECA approach enables to overcome some of the limitations and pitfalls previously reported with classical FMECA approaches.

Semiotic modelling for complex enterprise systems

An enterprise is viewed as a complex system which can be engineered to accomplish organisational objectives. Systems analysis and modelling will enable to the planning and development of the enterprise and IT systems. Many IT systems design methods focus on functional and non-functional requirements of the IT systems. Most methods are normally capable of one but leave out other aspects. Analysing and modelling of both business and IT systems may often have to call on techniques from various suites of methods which may be placed on different philosophic and methodological underpinnings. Coherence and consistency between the analyses are hard to ensure. This paper introduces the Problem Articulation Method (PAM) which facilitates the design of an enterprise system infrastructure on which an IT system is built. Outcomes of this analysis represent requirements which can be further used for planning and designing a technical system. As a case study, a finance system, Agresso, for e-procurement has been used in this paper to illustrate the applicability of PAM in modelling complex systems.

A neural network enhanced generalized minimum variance self-tuning proportional, integral and derivative control algorithm for complex dynamic systems

A neural network enhanced proportional, integral and derivative (PID) controller is presented that combines the attributes of neural network learning with a generalized minimum-variance self-tuning control (STC) strategy. The neuro PID controller is structured with plant model identification and PID parameter tuning. The plants to be controlled are approximated by an equivalent model composed of a simple linear submodel to approximate plant dynamics around operating points, plus an error agent to accommodate the errors induced by linear submodel inaccuracy due to non-linearities and other complexities. A generalized recursive least-squares algorithm is used to identify the linear submodel, and a layered neural network is used to detect the error agent in which the weights are updated on the basis of the error between the plant output and the output from the linear submodel. The procedure for controller design is based on the equivalent model, and therefore the error agent is naturally functioned within the control law. In this way the controller can deal not only with a wide range of linear dynamic plants but also with those complex plants characterized by severe non-linearity, uncertainties and non-minimum phase behaviours. Two simulation studies are provided to demonstrate the effectiveness of the controller design procedure.

Organocatalytic domino reaction of cyanosulfones: access to complex cyclohexane systems with quaternary carbon centers

When ε-nitro-a,β-unsaturated esters are added to conjugated cyanosulfones in the presence of a bifunctional thiourea catalyst, a highly stereoselective domino reaction occurs to generate complex cyclohexanes with up to four stereogenic centers, one of which is quaternary in nature. Therefore, it is demonstrated that, like nitro compounds, sulfones can undergo an asymmetric intramolecular conjugate addition to r,β- unsaturated esters in the presence of a bifunctional organocatalyst.

CASCADE: An Agent Based Framework For Modeling The Dynamics Of Smart Electricity Systems

The Complex Adaptive Systems, Cognitive Agents and Distributed Energy (CASCADE) project is developing a framework based on Agent Based Modelling (ABM). The CASCADE Framework can be used both to gain policy and industry relevant insights into the smart grid concept itself and as a platform to design and test distributed ICT solutions for smart grid based business entities. ABM is used to capture the behaviors of diff erent social, economic and technical actors, which may be defi ned at various levels of abstraction. It is applied to understanding their interactions and can be adapted to include learning processes and emergent patterns. CASCADE models ‘prosumer’ agents (i.e., producers and/or consumers of energy) and ‘aggregator’ agents (e.g., traders of energy in both wholesale and retail markets) at various scales, from large generators and Energy Service Companies down to individual people and devices. The CASCADE Framework is formed of three main subdivisions that link models of electricity supply and demand, the electricity market and power fl ow. It can also model the variability of renewable energy generation caused by the weather, which is an important issue for grid balancing and the profi tability of energy suppliers. The development of CASCADE has already yielded some interesting early fi ndings, demonstrating that it is possible for a mediating agent (aggregator) to achieve stable demandfl attening across groups of domestic households fi tted with smart energy control and communication devices, where direct wholesale price signals had previously been found to produce characteristic complex system instability. In another example, it has demonstrated how large changes in supply mix can be caused even by small changes in demand profi le. Ongoing and planned refi nements to the Framework will support investigation of demand response at various scales, the integration of the power sector with transport and heat sectors, novel technology adoption and diffusion work, evolution of new smart grid business models, and complex power grid engineering and market interactions.

Necessary and sufficient condition for generalized passivity, passification and application to multivariable adaptive systems

Recently, a generalized passivity concept for linear multivariable systems was obtained which allows circumventing the restrictiveness of the usual passivity concept. The latter is associated with the classical SPR (Strictly Positive Real) condition whereas the new concept of passivity is associated with the so called WSPR condition and its advantage in multivariable systems is that it does not require a restrictive symmetry condition of SPR systems. As a result, it allows the design of multivariable adaptive control that, unlike some existing factorization approaches, does not imply in additional overparameterization of the adaptive controller. In this paper, we complete a previously established WSPR sufficient condition and prove that it is also necessary. We also propose some methods of passification by either premultiplying the system output tracking error vector or the system input vector by an adequate passifying matrix multiplier, so that the resulting input/output transfer function becomes WSPR. The efficiency of our proposals are illustrated by simulation utilizing a well known robotics adaptive visual servoing problem. © 2011 IFAC.

On the Study of Complex Impulsive Systems

The article investigates complex impulsive systems in which the so-called controlling systems jumps effect emerges. In particular, this research includes the correctness of the solution to the impulsive control system and approximation lemmas. A 3D model example is provided which illustrates the relevance of the considered approach to the study of complex impulsive systems.

Structure property relations in complex copolymer systems

A thorough investigation was made of the structure-property relation of well-defined statistical, gradient and block copolymers of various compositions. Among the copolymers studied were those which were synthesized using isobornyl acrylate (IBA) and n-butyl acrylate (nBA) monomer units. The copolymers exhibited several unique properties that make them suitable materials for a range of applications. The thermomechanical properties of these new materials were compared to acrylate homopolymers. By the proper choice of the IBA/nBA monomer ratio, it was possible to tune the glass transition temperature of the statistical P(IBA-co-nBA) copolymers. The measured Tg’s of the copolymers with different IBA/nBA monomer ratios followed a trend that fitted well with the Fox equation prediction. While statistical copolymers showed a single glass transition (Tg between -50 and 90 ºC depending on composition), DSC block copolymers showed two Tg’s and the gradient copolymer showed a single, but very broad, glass transition. PMBL-PBA-PMBL triblock copolymers of different composition ratios were also studied and revealed a microphase separated morphology of mostly cylindrical PMBL domains hexagonally arranged in the PBA matrix. DMA studies confirmed the phase separated morphology of the copolymers. Tensile studies showed the linear PMBL-PBA-PMBL triblock copolymers having a relatively low elongation at break that was increased by replacing the PMBL hard blocks with the less brittle random PMBL-r-PMMA blocks. The 10- and 20-arm PBA-PMBL copolymers which were studied revealed even more unique properties. SAXS results showed a mixture of cylindrical PMBL domains hexagonally arranged in the PBA matrix, as well as lamellar. Despite PMBL’s brittleness, the triblock and multi-arm PBA-PMBL copolymers could become suitable materials for high temperature applications due to PMBL’s high glass transition temperature and high thermal stability. The structure-property relation of multi-arm star PBA-PMMA block copolymers was also investigated. Small-angle X-ray scattering revealed a phase separated morphology of cylindrical PMMA domains hexagonally arranged in the PBA matrix. DMA studies found that these materials possess typical elastomeric behavior in a broad range of service temperatures up to at least 250°C. The ultimate tensile strength and the elastic modulus of the 10- and 20-arm star PBA-PMMA block copolymers are significantly higher than those of their 3-arm or linear ABA type counterparts with similar composition, indicating a strong effect of the number of arms on the tensile properties. Siloxane-based copolymers were also studied and one of the main objectives here was to examine the possibility to synthesize trifluoropropyl-containing siloxane copolymers of gradient distribution of trifluoropropyl groups along the chain. DMA results of the PDMS-PMTFPS siloxane copolymers synthesized via simultaneous copolymerization showed that due to the large difference in reactivity rates of 2,4,6-tris(3,3,3-trifluoropropyl)-2,4,6-trimethylcyclotrisiloxane (F) and hexamethylcyclotrisiloxane (D), a copolymer of almost block structure containing only a narrow intermediate fragment with gradient distribution of the component units was obtained. A more dispersed distribution of the trifluoropropyl groups was obtained by the semi-batch copolymerization process, as the DMA results revealed more ‘‘pure gradient type’’ features for the siloxane copolymers which were synthesized by adding F at a controlled rate to the polymerization of the less reactive D. As with trifluoropropyl-containing siloxane copolymers, vinyl-containing polysiloxanes may be converted to a variety of useful polysiloxane materials by chemical modification. But much like the trifluoropropyl-containing siloxane copolymers, as a result of so much difference in the reactivities between the component units 2,4,6-trivinyl-2,4,6-trimethylcyclotrisiloxane (V) and hexamethylcyclotrisiloxane (D), thermal and mechanical properties of the PDMS-PMVS copolymers obtained by simultaneous copolymerization was similar to those of block copolymers. Only the copolymers obtained by semi-batch method showed properties typical for gradient copolymers.

Software Engineering for Self-Adaptive Systems: A Second Research Roadmap

The goal of this roadmap paper is to summarize the state-of-the-art and identify research challenges when developing, deploying and managing self-adaptive software systems. Instead of dealing with a wide range of topics associated with the field, we focus on four essential topics of self-adaptation: design space for self-adaptive solutions, software engineering processes for self-adaptive systems, from centralized to decentralized control, and practical run-time verification & validation for self-adaptive systems. For each topic, we present an overview, suggest future directions, and focus on selected challenges. This paper complements and extends a previous roadmap on software engineering for self-adaptive systems published in 2009 covering a different set of topics, and reflecting in part on the previous paper. This roadmap is one of the many results of the Dagstuhl Seminar 10431 on Software Engineering for Self-Adaptive Systems, which took place in October 2010.