Proved development of the real-time properties of the IEEE 1394 Root Contention Protocol with the event-B method

We present a model of the IEEE 1394 Root Contention Protocol with a proof of Safety. This model has real-time properties which are expressed in the language of the event-B method: first-order classical logic and set theory. Verification is done by proof using the event-B method and its prover, we also have a way to model-check models. Refinement is used to describe the studied system at different levels of abstraction: first without time to fix the scheduling of events abstractly, and then with more and more time constraints.     

Distributed system software design paradigm with application tocomputer networks

A paradigm for the system and software design of distributed systems is presented with application to an actual large-scale computer network involving both local area networks and a wide area network. A number of design principles are offered with particular reference to how they can be applied to the design of distributed systems. The author's major point is an explanation of how to make design decisions about distributed systems in a way which will enhance maintainability and understandability of the software and, at the same time, result in good system performance. The aim is to recognize the implications for software quality of various decisions which must be made in the process of specifying a distributed system     

Explicit level set and density methods for topology optimization with equivalent minimum length scale constraints

The goal of this paper is to introduce local length scale control in an explicit level set method for topology optimization. The level set function is parametrized explicitly by filtering a set of nodal optimization variables. The extended finite element method (XFEM) is used to represent the non-conforming material interface on a fixed mesh of the design domain. In this framework, a minimum length scale is imposed by adopting geometric constraints that have been recently proposed for density-based topology optimization with projections filters. Besides providing local length scale control, the advantages of the modified constraints are twofold. First, the constraints provide a computationally inexpensive solution for the instabilities which often appear in level set XFEM topology optimization. Second, utilizing the same geometric constraints in both the density-based topology optimization and the level set optimization enables to perform a more unbiased comparison between both methods. These different features are illustrated in a number of well-known benchmark problems for topology optimization.

     

SCPIP – an efficient software tool for the solution of structural optimization problems

This paper describes SCPIP, a FORTRAN77 subroutine that has been proven to be a reliable implementation of convex programming methods in an industrial environment. Convex approximation methods like the method of moving asymptotes are used nowadays in many software packages for structural optimization. They are known to be efficient tools for the solution of design problems, in particular if displacement dependent constraints like stresses occur. A major advantage over many but not all classical approaches of mathematical programming is that at an iteration point a local model is formulated. For the solution of such a model no further function and gradient evaluations are necessary besides those at the current iteration point. The first versions of convex approximation methods used all a dual approach to solve the subproblems which is still a very efficient algorithm to solve problems with at most a medium number of constraints. But it is not efficient for problems with many constraints. An alternative is the use of an interior point method for the subproblem solution. This leads to more freedom in the definition of the linear systems where most of the computing time to solve the subproblems is spent. In consequence, large-scale problems can be handled more efficiently.     

Simulated annealing for the design of structures with time-varying constraints

The optimal design of structural systems with conventional members or systems with conventional as well as passive or active members is presented. The optimal sizes of the conventional members of structural systems are obtained for dynamic loads. A modified simulated annealing algorithm is presented which is used to solve the optimization problem with dynamic constraints. The present algorithm differs from existing simulated annealing algorithms in two respects; first, an automatic reduction of the search range is performed, and second, a sensitivity analysis of the design variables is utilized. The present method converges to the minimum in less iterations when compared to existing simulated annealing algorithms. The algorithm is advantageous over classical methods for optimization of structural systems with constraints arising from dynamic loads. For certain initial values of the design variables, classical optimization methods either fail to converge or produce designs which are local minima; the present algorithm seems to be successful in yielding the global minimum design.     

Formal and incremental construction of distributed algorithms: On the distributed reference counting algorithm

The development of distributed algorithms and, more generally, distributed systems, is a complex, delicate and challenging process. Refinement techniques of (system) models improve the process by using a proof assistant, and by applying a design methodology aimed at starting from the most abstract model and leading, in an incremental way, to the most concrete model, for producing a distributed solution. We show, using the distributed reference counting (DRC) problem as our study, how models can be produced in an elegant and progressive way, thanks to the refinement and how the final distributed algorithm is built starting from these models. The development is carried out within the framework of the event B method and models are validated with a proof assistant.     

Application of intelligent CAD paradigms to preliminary structural design

Structural design is the synthesis of structural systems and components in such a way that the system behaves as intended by the designer and meets the constraints imposed by physical laws and project requirements. The reasoning inherent in the design process is to be carried out on different levels and with different degrees of abstraction, uncertainty and impact on further design decisions. The nature of design operations ranges from schematic decisions based on heuristic considerations concerning system types and topology to parameter definitions concerning member material and geometry inferred from numerical computations. In our approach we explicitly distinguish between strategy and related expectations, design actions on a tactical level and local design modifications due to untypical conditions. Artificial intelligence techniques are applied such as planning methods, heuristic search and constraint programming which are used in a distinct manner on the different levels. The approach is discussed by examples taken from a prototype implementation for preliminary structural design.     

Decentralized control: Status and outlook

This paper reviews state of the art in the area of decentralized networked control systems with an emphasis on event-triggered approach. The models or agents with the dynamics of linear continuous-time time-invariant state-space systems are considered. They serve for the framework for network phenomena within two basic structures. The I/O-oriented systems as well as the interaction-oriented systems with disjoint subsystems are distinguished. The focus is laid on the presentation of recent decentralized control design and co-design methods which offer effective tools to overcome specific difficulties caused mainly by network imperfections. Such side-effects include communication constraints, variable sampling, time-varying transmission delays, packet dropouts, and quantizations. Decentralized time-triggered methods are briefly discussed. The review is deals mainly with decentralized event-triggered methods. Particularly, the stabilizing controller–observer event-based controller design as well as the decentralized state controller co-design are presented within the I/O-oriented structures of large scale complex systems. The sampling instants depend in this case only on a local information offered by the local feedback loops. Minimum sampling time conditions are discussed. Special attention is focused on interaction-oriented system architecture. Model-based approach combined with event-based state feedback controller design is presented, where the event thresholds are fully decentralized. Finally, several selected open decentralized control problems are briefly offered as recent research challenges.     

Constraint aggregation for large number of constraints in wing surrogate-based optimization

The method of aggregating a large number of constraints into one or few constraints has been successfully applied to wing structural design using gradient-based local optimization. However, numerical difficulties may occur in the case that the local curvatures of the aggregated constraint become extremely large and then ill-conditioned Hessian matrix may be yielded. This paper aims to test different methods of constraint aggregation within the framework of a gradient-free optimization, which makes use of cheap-to-evaluate surrogate models to find the global optimum. Three constraint aggregation approaches are investigated: the maximum constraint approach, the constant parameter Kreisselmeier-Steinhauser (KS) function, and the adaptive KS function. We also explore methods of aggregating constraints over the entire structure and within sub-domains. Examples of structural optimization and aero-structural optimization for a transport aircraft wing are employed and the results show that (1) the KS function with a larger constant parameter ρ can lead to better optimization results than the adaptive method, as the active constraints are approximated more accurately; (2) lumping the constraints within sub-domains instead of all together can improve the accuracy of the aggregated constraint and therefore helps find a better design. Finally, it is concluded from current test cases that the most efficient way of handling large-scale constraints for wing surrogate-based optimization is to aggregate constraints within sub-domains and with a relatively large constant parameter.

     

Design sensitivity analysis and optimization of dynamic response

The paper presents methods of design sensitivity analysis and optimization of dynamic response of mechanical and structural systems. A key feature of the paper is the development of procedures to handle point-wise state variable constraints. Difficulties with a previous treatment where such constraints were transformed to equivalent integral constraints are noted and explained from theoretical as well as engineering standpoints. An alternate treatment of such constraints is proposed, developed and evaluated. In this treatment each point-wise state variable constraint is replaced by several constraints that are imposed at all the local max-points for the original constraint function. The differential equations of motion are formulated in the first-order form so as to handle more general problems. The direct differentiation and adjoint variable methods of design sensitivity analysis to deal with the point-wise constraints are presented. With the adjoint variable methods, there are two ways of calculating design sensitivity coefficients. The first approach uses an impulse load and the second approach uses a step load for the corresponding adjoint equation. Since the adjoint variable methods are better for a large class of problems, an efficient computational algorithm with these methods is presented in detail. Optimum results for several problems are obtained and compared with those available in the literature. The new formulation works extremely well as precise optimum designs are obtained.     

A new computer graphics approach to parameter space design of control systems

This paper presents a new approach to parameter space design of linear multivariable control systems. The complete solution of a pole region assignment problem for single-input systems is obtained as an admissible region in then-dimensional parameter space of state feedback gains. We develop a new modeling technique for these admissible parameter space regions which is superior to previous ones because it permits unambiguous and efficient graphical display of slices in 2D and 3D subspaces. In an interactive computer graphics implementation, this method provides an environment where the influence of stability, performance, robustness, integrity, and control constraints on design parameters can be directly visualized and complex tradeoffs are resolved in an interactive way. By judicious combination of overlays, color, and/ or animation, admissible ranges of up to five or six design parameters can be displayed simultaneously. A sequential decomposition technique which selects slices for full parameter space design of lower dimensional subsystems such that the remaining eigenvalues are invariant is used for systems of arbitrarily high order. Parameter space design of unity rank feedback for multiinput systems is done in exactly the same fashion, while systematic sequential design of full rank feedback is achieved as the sum of dyadic stages to which the single-input modeling techniques apply. Examples are given for all presented methods to show the flexibility and potential as a computer-aided control system design framework with a novel integration of computer graphics technology.     

Sequential stability and optimization of large scale decentralized systems

The notion of sequential stability in the synthesis of decentralized control for large scale systems is introduced in this paper. This notion is concerned with the property of a synthesis technique which allows the decentralized controllers of a large scale system to be connected to the systems one at a time (in a sequential way) such that the controlled system remains stable at all times. The motivation for introducing this constraint is that in practical terms, it is generally impossible to connect all decentralized controllers to a system simultaneously (due to the difficulties of communication etc.). A practical design procedure for the synthesis of a decentralized robust regulator for the servomechanism problem, based on a sequential approach to system design, is then given. The design procedure proceeds in two stages: (1) decentralized controllers are initially connected to the system in a sequential way to guarantee stability; (2) the parameters of the decentralized controllers are then sequentially adjusted, in a way to guarantee stability, so as to optimize a given performance index for the system. Applications of the above procedure are then made to the synthesis of centralized multivariable controllers and to the decentralized robust control of unknown systems.A simple example is given to illustrate the design synthesis.     

An optimization-driven approach for computing geodesic paths on triangle meshes

There are many application scenarios where we need to refine an initial path lying on a surface to be as short as possible. A typical way to solve this problem is to iteratively shorten one segment of the path at a time. As local approaches, they are conceptually simple and easy to implement, but they converge slowly and have poor performance on large scale models. In this paper, we develop an optimization driven approach to improve the performance of computing geodesic paths. We formulate the objective function as the total length and adopt the L-BFGS solver to minimize it. Computational results show that our method converges with super-linear rate, which significantly outperforms the existing methods. Moreover, our method is flexible to handle anisotropic metric, non-uniform density function, as well as additional user-specified constraints, such as coplanar geodesics and equally-spaced geodesic helical curves, which are challenging to the existing local methods.     

Validated Constraint Solving—Practicalities,Pitfalls, and New Developments

Many constraint propagation techniques iterate through the constraints in a straightforward manner, but can fail because they do not take account of the coupling between the constraints.However, some methods of taking account of this coupling are local in nature, and fail if the initial search region is too large.We put into perspective newer methods, based on linear relaxations, that can often replace brute-force search with the solution of a large, sparse linear program.Robustness has been recognized as important in geometric computations and elsewhere for at least a decade, and more and more developers are including validation in the design of their systems. We provide citations to our work and to the work of others to-date in developing validated versions of linear relaxations.This work is in the form of a brief review and prospectus for future development. We give various simple examples to illustrate our points.     

An integrated model for strategic supply chain design: Formulation and ABC-based solution approach

This study develops a mixed integer nonlinear programming (MINLP) model to design supply chains. In view of the limitations of many available strategic supply chain design models, this model involves three major supply chain stages, including procurement, production, and distribution, and their interactions; it takes into account bill of materials constraints for modeling complex supply chain inter-relationships. In addition, in accordance with the fact that companies nowadays develop product families, our model addresses multi-product supply chain design to respond to diverse customer requirements. Recognizing their importance, this study identifies and formulates constraints related to facility pairwise relationships and supplier priority along with the classical constraints from the available literature. To efficiently solve such a highly constrained, large scale MINLP model, we develop an approach based on an artificial bee colony (ABC) algorithm. Bicycle design and production is used to demonstrate the potential of the MINLP model for designing supply chains and the performance of the ABC-based solution approach in solving the model. The proposed model and solution approach can be considered as two fundamental components of an expert system in the broad sense. Thus, this study is expected to stimulate more future research on the development of practical expert systems for designing supply chains.     

Designing secure databases

Security is an important issue that must be considered as a fundamental requirement in information systems development, and particularly in database design. Therefore security, as a further quality property of software, must be tackled at all stages of the development. The most extended secure database model is the multilevel model, which permits the classification of information according to its confidentiality, and considers mandatory access control. Nevertheless, the problem is that no database design methodologies that consider security (and therefore secure database models) across the entire life cycle, particularly at the earliest stages currently exist. Therefore it is not possible to design secure databases appropriately. Our aim is to solve this problem by proposing a methodology for the design of secure databases. In addition to this methodology, we have defined some models that allow us to include security information in the database model, and a constraint language to define security constraints. As a result, we can specify a fine-grained classification of the information, defining with a high degree of accuracy which properties each user has to own in order to be able to access each piece of information. The methodology consists of four stages: requirements gathering; database analysis; multilevel relational logical design; and specific logical design. The first three stages define activities to analyze and design a secure database, thus producing a general secure database model. The last stage is made up of activities that adapt the general secure data model to one of the most popular secure database management systems: Oracle9i Label Security. This methodology has been used in a genuine case by the Data Processing Center of Provincial Government. In order to support the methodology, we have implemented an extension of Rational Rose, including and managing security information and constraints in the first stages of the methodology.     

一种面向嵌入式实时系统的安全策略优化生成方法

由于受到系统资源和实时性的限制,对于嵌入式实时系统的安全扩展很难延用通用计算机系统的安全设计方法,因此需要对其进行专门的研究。为了在确保实时性的前提下使嵌入式实时系统的安全性达到最优,本文提出了一套完整的安全设计方法,包括安全任务图模型和安全评估模型,在此基础上,又提出了一种基于整数线性规划的安全策略优化生成方法ILPOS。该安全策略优化生成方法同时解决了安全算法选择和实时可调度性检测两方面的问题,克服了一般分阶段优化方法的不足,从而充分地利用系统可用时间来实现安全扩展。仿真实验结果表明,与传统的启发式安全设计算法相比,ILPOS方法在各种实时性约束条件下都能有效地提高系统的安全性。     

An Approach to Distributed Computing System Software Design

Distributed computing systems represent a wide variety of computer systems, ranging from a centralized star network to a completely decentralized computer system. The design of software for distributed computing systems is more complicated due to many design constraints and interactions of software components of the system.     

Output violation compensation for systems with output constraints

The problem of output constraints in linear systems is considered, and a new methodology which helps the closed loop respect these limits is described. The new methodology invokes ideas from the antiwindup literature in order to address the problem from a practical point of view. This leads to a design procedure very much like that found in antiwindup design. First, a linear controller ignoring output constraints is designed. Then, an additional compensation network which ensures that the output limits are, as far as possible, respected is added. As the constraints occur at the output, global results can be obtained for both stable and unstable plants.     

Cross-estimator design for coordinated systems: Constraints, covariance, and communications resource assignment

Coordinated systems interact via the exchange of information through communication. As the network of coordinated systems increases in the number of subsystems, natural limits on the available bandwidth of communication need to be imposed. Without this, the coordinated system does not scale properly and the interaction burden becomes unmanageable. Our aim in this paper is to develop estimation techniques for the coordinated systems including the allocation of communication resources. Central ideas involve: interaction via constraints imposed by neighbors, the tightening of these constraints to reflect state uncertainty, and the assignment of communications resources to manage this uncertainty in the estimator design. Linear matrix inequality methods are applied to develop a solution which links control objective, performance, and communication limits.