Complex Hybrid Systems Research Articles

A methodology to design a fuzzy logic based supervision of Hybrid Renewable Energy Systems

Hybrid Renewable Energy Systems (HRES) are increasingly used to improve the grid integration of wind power generators. The goal of this work is to propose a methodology to design a fuzzy logic based supervision of this new kind of production unit. A graphical modeling tool is proposed to facilitate the analysis and the determination of fuzzy control algorithms adapted to complex hybrid systems. To explain this methodology, the association of wind generators, decentralized generators and storage systems are considered for the production of electrical power. The methodology is divided in six steps covering the design of a supervisor from the system work specifications to an optimized implementation of the control. The performance of this supervisor is shown with the help of simulations. Finally, the application of this methodology to the supervision of different topologies of HRES is also proposed to bring forward the systematic dimension of the approach.

Méthodologie de développement de superviseurs à logique floue de centrales multisources à base d'énergie renouvelable

Hybrid Energy Systems (HES) including storage will be increasingly used to improve the grid integration of renewable generation. The goal of this work is to propose a methodology to design a fuzzy logic based supervision of this new kind of production unit. A graphical modeling tool is proposed to facilitate the analysis and the determination of fuzzy control algorithms adapted to complex hybrid systems. To explain this methodology, the association of wind generators, foreseeable decentralized generators and storage systems is considered for the production of electrical power in a small grid system. The performance of this supervisor is shown with the help of simulations and quantitative indicators. Finally, the application of this methodology to the supervision of different topologies of HES is proposed to bring forward the systematic and modular characteristics of the approach.

Integrated modeling of the electric grid, communications, and control

PurposeThis paper aims to address a central concern in modeling and simulating electric grids and the information infrastructure that monitors and controls them. The paper discusses the need for and methods to construct simulation models that include important interactions between the physical and computational elements of a large power system.Design/methodology/approachThe paper offers a particular approach to modeling and simulation of hybrid systems as an enabling technology for analysis (via simulation) of modern electric power grids. The approach, based on the discrete event system specification, integrates existing simulation tools into a unified simulation scheme. The paper demonstrates this approach with an integrated information and electric grid model of a distributed, automatic frequency maintenance activity.FindingsPower grid modernization efforts need powerful modeling and simulation tools for hybrid systems.Research limitations/implicationsThe main limitation of this approach is a lack of advanced simulation tools that support it. Existing commercial offerings are not designed to support integration with other simulation software products. The approach to integrating continuous and discrete event simulation models can overcome this problem by allowing specific tools to focus on continuous or discrete event dynamics. This will require, however, adjustments to the underlying simulation technology.Originality/valueThis paper demonstrates an approach to simulating complex hybrid systems that can, in principle, be supported by existing simulation tools. It also indicates how existing tools must be modified to support our approach.

Perfect Simulation of a Class of Stochastic Hybrid Systems with an Application to Peer to Peer Systems

In this paper we present a class of hybrid systems made of deterministic differential equations and random discrete jumps. We then show how to construct a simulation of such a stochastic hybrid system that provides perfect samples of its asymptotic behavior based on the extension to continuous state-space of coupling-from-the-past techniques introduced by Foss and Tweedie (Stoch Models 14:187–204, 1998) and using suitable envelope trajectories to tackle non-monotonicity. The applicability of the method is illustrated by showing how this framework can be used to model the Squirrel peer to peer system and by reporting a simulation study based on this approach. This paper provides both a framework on how to carry simulation based experimental studies of large and complex hybrid systems and its application in the Squirrel model demonstrating how versatile and powerful this approach can be over a typical example.

Causality assignment and model approximation for quantitative hybrid bond graph-based fault diagnosis

Bond graph (BG) is an effective tool for modeling complex systems and it has been proven to be useful for fault detection and isolation (FDI) purposes for large continuous systems. BG provides causality between system's variables which allows FDI algorithms to be developed systematically from the graph. Similarly, Hybrid bond graph (HBG) is a bond graph-based modeling approach which provides an avenue to model complex hybrid systems; however, due to the lack of understanding, HBG has not been well-utilized for fault diagnosis. This is the first of a two-part paper that investigates the feasibility of utilizing HBG for quantitative FDI applications for hybrid systems. In this first paper, we present an analysis on the causality properties of the HBG where useful properties and insights associated with FDI applications are gained. Based on these properties, a causality assignment procedure and modeling approximation techniques are developed to achieve a HBG with a causality that facilitates efficient and effective FDI design for hybrid systems.

Discrete Event Simulation: A Review of SimEvents

A new entrant in the field of discrete event simulation systems, SimEvents has several desirable system features. It still has some catching up to do in some areas, but SimEvents is particularly useful for existing Matlab and Simulink users looking to construct complex hybrid systems of discrete/continuous processing.

A Mechanistic Study of the Formation of Mesoporous Structures from in Situ AC Conductivity Measurements

The purpose of this work is to study the kinetics of self-assembly in the formation mechanism of anionic templated mesoporous solids (AMS-n) during the first few seconds of the synthesis as well as to demonstrate the use of alternating ion current (AIC) conductivity measurements to follow the self-assembly in complex hybrid systems. The formation of different AMS-n caged-type mesostructures through the delayed addition of the silica source is demonstrated and explained in terms of the interaction between the co-structure-directing agent (CSDA) and the oppositely charged surfactant headgroup regions. Our findings, supported by transmission electron microscopy, 29Si magic angle spinning nuclear magnetic resonance (MAS NMR) spectroscopy, dynamic light scattering (DLS) measurements, and powder X-ray diffraction suggest that the interaction of the CSDA with the surfactant headgroup occurs within seconds after its addition to the synthesis gel leading to interaction between the polymerizing CSDAs and the oppositely charged micelle and to an increase in the micelle-CSDA aggregate size. Both DLS and AIC measurements agree that this process occurs within the first 1000 s after addition of the CSDA to the synthesis gel at room temperature. In addition to the mechanistic study it was found that the intermediate materials are comprised of a three-layer entity. Time-dependent 29Si MAS NMR studies reveal that an organo-silica layer forms around the micelles prior to a condensed outer inorganic shell of silica.

Landing system verification based on petri nets and a hybrid approach

One of the most important activities of control system design is its verification. Verification ensures that the controlled system will behave as expected under any circumstances it may operate. In this context, the purpose of this paper is to introduce a new method for the verification of aircraft control systems. The focus of this method is on aircraft systems that are characterized as hybrid, i.e., that merge continuous and discrete dynamics. The method proposed is divided into two main parts: the system modeling and the verification of behavioral properties. In the first part, Petri net, differential equation systems, and object oriented concepts are used concurrently in order to model complex hybrid systems. In the second part, the distributed nature of the model is explored in order to decompose a complex verification problem into series of simple local problems. Linear logic is used as a basis of a theorem-proving approach for the verification from the discrete-event point of view. The verification method has been applied to a number of case studies. Among them is the landing system of a military aircraft, which is described in this paper

Morphology of hybrid polystyrene- block-poly(ethylene oxide) micelles: Analytical ultracentrifugation and SANS studies

Morphology and structure of aqueous block copolymer solutions based on polystyrene- block-poly(ethylene oxide) (PS- b-PEO) of two different compositions, a cationic surfactant, cetyl pyridinium chloride (CPC), and either platinic acid (H 2PtCl 6⋅6H 2O) or Pt nanoparticles were studied using a combination of analytical ultracentrifugation (AUC), transmission electron microscopy (TEM), and small angle neutron scattering (SANS). These studies combining methods contributing supplemental and analogous structural information allowed us to comprehensively characterize the complex hybrid systems and to discover an isotope effect when H 2O was replaced with D 2O. In particular, TEM shows formation of both micelles and larger aggregates after incorporation of platinic acid, yet the amount of aggregates depends on the H 2PtCl 6⋅6H 2O concentration. AUC reveals the presence of micelles and micellar clusters in the PS- b-PEO block copolymers solution and even larger (supermicellar) aggregates in hybrids (with CPC). Conversely, SANS applied to D 2O solutions of the similar species indicates that micelles are spherical and no other micellar species are found in block copolymer solutions. To reconcile the SANS and AUC data, we carried out AUC examination of the corresponding D 2O block copolymer solutions. These measurements demonstrate a pronounced isotope effect on micelle aggregation and micelle size, i.e., no micelle aggregation in D 2O solutions, revealing good agreement of AUC and SANS data.

Evaluation of geo‐referenced grids of 1961–1990 Canadian temperature and precipitation normals

Four sets of geo‐referenced grids of 1961–90 normals, or thirty‐year averages, of monthly maximum and minimum temperatures, and total precipitation are compared for the following areas of western Canada: Alberta, Saskatchewan, Manitoba and south‐eastern British Columbia. The landscape varies from lowlands around Hudson Bay in the east and flat plains in the south, to moderate elevation hills and numerous lakes in the north, to a complex terrain of high mountains and deep valleys in the west. Interpolation methods used to create the grids range from a very simple technique ‐ Inverse Distance Weighting (IDW) of closest neighbours, to more sophisticated statistical models ‐ ANUSPLIN (thin plate smoothing splines on geographic location and elevation) and SQUARE‐GRID (multivariate regression on elevation, distance from large water bodies and barriers, etc.), to even more complex hybrid systems ‐ PRISM (statistical regression, combined with physical models and expert knowledge). The main characteristics of each technique are discussed in detail, as they are often very good predictors of the accuracy of the ensuing gridpoint values. Based on the intercomparison of point and average values, as well as the verification of temperature with upper air soundings and precipitation with streamflow measurements, all grids, except SQUARE‐GRID for precipitation, produce very good results in the Prairies’ ecozone. Temperatures in most cases agree within 1°C and precipitation within several percent. PRISM, which was verified to model the Arctic inversion correctly, performs the best in winter in northern Saskatchewan, Manitoba, and Alberta, in particular, over the hills of northern Alberta (PRISM warmer), and most likely over low lying areas of the Nelson River Delta (PRISM colder). PRISM and ANUSPLIN can be recommended for the mountains of south‐eastern British Columbia and southwestern Alberta. Both grids verify well, in both winter and summer, with upper air soundings for maximum temperature and station vertical profiles for minimum temperature. They are remarkably close to water balance estimates of precipitation computed from streamflow gauge measurements ‐ PRISM is slightly high and ANSUPLIN slightly low. Precipitation from IDW and SQUARE‐GRID are not satisfactory in the mountains; both severely underestimate precipitation by as much as 40%. IDW, which does not incorporate any orographic effects, is also too warm in the mountains. As expected, topography, physiography, and monitoring network issues are sources of major discrepancies among the grids. SQUARE‐GRID, besides using far fewer stations and a preprocessed dataset, also produced anomalous values, e.g., values of zero precipitation along the eastern slopes of the Rocky Mountains.

Compositional Abstractions of Hybrid Control Systems

Abstraction is a natural way to hierarchically decompose the analysis and design of hybrid systems. Given a hybrid control system and some desired properties, one extracts an abstracted system while preserving the properties of interest. Abstractions of purely discrete systems is a mature area, whereas abstractions of continuous systems is a recent activity. In this paper we present a framework for abstraction that applies to discrete, continuous, and hybrid systems. We introduce a composition operator that allows to build complex hybrid systems from simpler ones and show compatibility between abstractions and this compositional operator. Besides unifying the existing methodologies we also propose constructions to obtain abstractions of hybrid control systems.

Airfield simulation with optimization via decomposition

The United States Transportation Command (USTRANSCOM) is responsible for managing our Air Force's capability to move personnel, equipment, and cargo during wartime and peacetime from any origin to any destination within its global system of airfields. The analysis groups of USTRANSCOM and the Air Mobility Command (AMC) employ sophisticated computer models and simulations to help them better understand the capabilities and limitations of the many types of resources making up this complex transportation system. This study describes the development and use of the computer model that analyzes the complex activities that occur at a military airfield in order to assess the airfield's ability to support many types of aircraft missions. It also outlines the optimizing of complex hybrid systems using a method of decomposition that allows for the use of classical methods to improve the performance of the airfield system. Previously known as the Base Resource and Capabilities Estimator (BRACE), the model and computer simulation are now referred to as the Airfield Simulation Tool (AST). BRACE/AST is used by the Air Force on a daily basis to analyze the capabilities of their many airfields throughout the world and has been used to support several major policy and infrastructure enhancement studies.

Petri Net Place Associated to a Continuous or Discretized Control Algorithm

In the design, analysis and implementation of the Industrial Automation Systems, it is often observed that the modeling complexity can increase due its possible hybrid nature.In this paper, an approach for different nature subsystems integration in an unique Petri Net model is presented. This integration will be made by means of the inclusion of Places Associated to Continuous or Discretized Algorithms and it will be applied to Automated Complex Hybrid Systems.

A simulation-optimisation programme for designing hybrid energy systems for supplying electricity and fresh water through desalination to remote areas: Case study: the Merssini village, Donoussa island, Aegean Sea, Greece

The aim of the present paper is to develop and apply a software tool for designing hybrid renewable energy systems. The hybrid system consists of a wind generator and photovoltaic modules which are the renewable technologies for energy production. The programme has been applied for simulating a hybrid system with the above mentioned technologies in order cover the electricity and water needs of the Merssini village on Donoussa island in the Aegean Sea of Greece. The Merssini village is occupied by 20 year-round residents while the population is doubled during the summer period. The village is non-electrified and faces a problematic scarcity of fresh water. In the analysis that follows, the considered technical data as well as the results of programme runs for winter and summer seasons are presented. The electricity consumption consists of both the household and desalination plant consumption. The system is supplemented with batteries and a micro hydraulic plant for energy storage. The simulation programme was used to optimise the design of the system as well as to manage the energy supply and energy storage. The results prove that this simulation programme constitutes a valuable tool for the determination not only of the optimum combination of technologies, but also the optimum energy management of complex hybrid systems.

Structuring of Large-scale Complex Hybrid Systems: from Illustrative Analysis toward Modelization

System structuring is paramount to the development of large-scale complex hybrid systems (LCHS). However, there is no well-established and effective methodology for the structuring of LCHS. Using the approach of illustrating and abstracting, this paper investigates the structuring of LCHS based on a wide variety of applications. First, intrinsic attributes of LCHS are explored. Then, a unified framework-based analysis is made of six typical examples of LCHS, i.e. human brain-body systems, autonomous robot systems, autonomous fed-batch reactor systems, human-car driving systems, autonomous urban traffic systems, and autonomous production (manufacturing/industrial process) systems. In this way, common characteristics among typical examples, e.g., perception–decision link, distributing, nesting, hierarchy, multiple gradation and hybrid dynamics over a spectrum of time drivers, and, incidentally, wide application orientations of LCHS, are illustrated. Furthermore, after basic concepts for the modelization of LCHS are formulated, two novel general-purpose information-processing modules are proposed and constructed, called perception cube and decision spheroid. Based on them, a novel block diagram based model is originally proposed and established for LCHS.

Modular representation of complex hybrid systems: application to the simulation of batch processes

A modelling approach of complex systems is presented. The goal is to define a modular and non-causal representation able to describe hybrid dynamics, and to generate automatically the models corresponding to the different configurations of the real system. These models can then be used to simulate process evolution. In this paper, we define the structure of the basic model blocks and the interactions of these blocks through different kinds of signals.

Continuous-discrete interactions in chemical processing plants

This paper discusses important hybrid aspects of chemical processing plants. It is outlined that discrete phenomena occur both on the physical level and in the control of these plants. As the dynamics of the transformations of energy and material are predominantly continuous, large and complex hybrid systems arise. We focus on three different aspects of dealing with such systems: (1) Modeling and simulation of hybrid systems for the design and optimization of plants, controllers and operating strategies. We present powerful simulation environments that have been developed in recent years. (2) Validation of plant instrumentation and discrete controllers. These systems are largely responsible for the safe and economic operation of chemical plants and the protection of the workforce, and the environment. Techniques for the verification of discrete controllers for continuous processes are discussed, which are based on a discrete approximation of the continuous dynamics. (3) Scheduling of batch plants. For plants that are operated in a discontinuous fashion, the timing and sequencing of the operations are very important for the efficient use of the equipment. This leads to large mixed-integer optimization problems. For a typical example, we show how the process and the constraints can be modeled and describe an efficient solution algorithm.

Electrical Actuation Systems with AC Motors an Example of Complex Automatic Control

Abstract Digitally controlled actuation systems with VSI fed AC motors are examples of complex hybrid systems combining digital and continuous variables : - synchronous or induction motors are non linear multivariable subsystems; - the control amplifier consisting in a power electronic converter feeding the motor can only produce a limited number of control vectors from which control variables are obtained by an appropriate sequence in order to follow the references generated by the digital regulator. It will be shown how the discrete and non linear characteristics of these systems can be taken into account even if the control is fully digital.

Object-oriented modelling and simulation of batch plants

Abstract In this paper, the modelling and simulation of recipe driven multipurpose chemical or biochemical plants using an object oriented approach is described. A data model is presented which enables the description of all important aspects of batch plants: the model of the plant (reactors, tanks, pipes, separation units etc.), the batches of material and the dynamics of their transformation, and the recipe driven sequential production process. Batch plants are complex hybrid systems (Cellier et al. (1993), Clark and Joglekar (1992)) because many different components with associated continuous dynamics are involved, the production sequence is event-driven, continuous and discrete state variables must be used to describe the production process, and the structure of the system and the number of state variables change over time.

Hybrid Connectionist Fuzzy Production System: Towards Building Comprehensive AI

ABSTRACTThe article presents major principles of building complex hybrid systems for knowledge engineering. The systems make use of neural networks (for low level processing), fuzzy systems (for intermediate level processing), and symbolic AI systems (for higher level processing). Knowledge acquisition and rules extraction is considered an important part of the whole system. An experimental environment, Fuzzy COPE, which facilitates building comprehensive AI systems, is described. It consists of data a analysis module, a neural network module, a fuzzy inference module, a production rules module, and a fuzzy rules extraction module. Such an environment makes possible using all of the three paradigms, i.e. fuzzy rules, neural networks and symbolic production rules, as well as other paradigms of soft computing, in one system. A methodology for building comprehensive AI systems is described. The use of Fuzzy COPE for building hybrid systems is illustrated on a test problem for decision making in stock trading...