While formal verification has been successfully used to analyze several academic examples of controlled hybrid systems, the application to real-world processing systems is largely restricted by the complexity of model...
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While formal verification has been successfully used to analyze several academic examples of controlled hybrid systems, the application to real-world processing systems is largely restricted by the complexity of modeling and computation. This paper aims at improving the applicability by using decomposition and deduction techniques: A given system is first decomposed into a set of physical and/or functional units and modeled by communicating timed automata or linear hybrid automata. The so-called assumption/commitment method allows one to formulate requirements for the desired behavior of single modules or groups of modules. Model-checking is an appropriate technique to analyze whether the requirements (e.g. the exclusion of critical states) are fulfilled. By combining the analysis results obtained for single modules, properties of composed modules can be deduced. As illustrated for a laboratory plant, properties of the complete system for which direct model-checking is prohibitively expensive can be inferred by the iterative application of analysis and deduction.
Modeling and design of distributed real-time embedded systems tend to be a very complex work, especially when heterogeneous systems and task synchronization are involved. In this sense, a specific framework can help i...
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Modeling and design of distributed real-time embedded systems tend to be a very complex work, especially when heterogeneous systems and task synchronization are involved. In this sense, a specific framework can help in dealing with such complexity. The paper describes such a framework, which has been developed to help developers in the task of modeling and implementation of embedded real-time applications. The framework extends SIMOO-RT an object oriented software tool developed at UFRGS, with the possibility of using components. A component library template, the use of a deployment diagram for the configuration of a given component based solution to different target architectures, and a new code generator are the main extensions proposed. The paper gives an overview on the proposed extensions, explaining its use by means of some developed case studies.
An application of a special approach aiming at the development of a new branch of soft computing (SC) for the adaptive control of approximately and partially known electromechanical systems is reported. Like "tra...
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An application of a special approach aiming at the development of a new branch of soft computing (SC) for the adaptive control of approximately and partially known electromechanical systems is reported. Like "traditional" SC it uses "uniform structures" for modeling, but these structures are obtained from the symplectic group (SG). This approach can considerably reduce the number of free parameters in the model in comparison e.g. with that of the neural networks or ample sets of fuzzy rules. It also replaces the process of parameter tuning with simple, lucid, and explicit algebraic operations of limited steps. While in the previous approaches SG was utilized as an inner symmetry of classical mechanical systems, in the present one it is used in a formal way not utilizing mechanical symmetries. Furthermore, SG is not the internal symmetry of electrical, that is of electro-mechanical systems. In the present paper the new formal approach is demonstrated in the adaptive control of a 3 mechanical DOF SCARA-type robot arm actuated by DC motors together forming a 6 DOF electromechanical system. It is concluded on the basis of simulations that the control designed for the 3 DOF mechanical degrees of freedom can efficiently compensate for the behavior of the electrical degrees of freedom not modeled by the controller.
The aim of this paper is to investigate the behavior of a string in the cylindrically symmetric inhomogeneous cosmological model. It has been assumed that expansion θ in the model is proportional to σ11 of the eigen...
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The aim of this paper is to investigate the behavior of a string in the cylindrically symmetric inhomogeneous cosmological model. It has been assumed that expansion θ in the model is proportional to σ11 of the eigenvalue of the shear tensor σνmu;. Also, various physical and geometrical properties of the model have been discussed.
We present a scalable, low cost multiprocessor system, which is used in the area of measurement, regulation, controlling and soft computing. The system is an example of extremely modular hardware/software design. Modu...
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We present a scalable, low cost multiprocessor system, which is used in the area of measurement, regulation, controlling and soft computing. The system is an example of extremely modular hardware/software design. Modular in this context means that we can easily change or optimize individually the components in the system for a given problem. One of the most important aspects of our multiprocessor system is the fact that the user can dynamically change the communication topology by software 'on-the-fly'. Thus, the hardware can be (re)configured during operation in less than 1 ms. By this, the CPUs in the multiprocessor system can communicate directly without any invention of another processor preventing the typical bottleneck in parallel systems. First applications have been implemented in an embedded controller for a vote counting machine, with emphasis on high data security and high throughput.
Technology mapping for multiplexor (MUX) based field programmable gate arrays (FPGAs) has widely been considered. A new algorithm is proposed that applies techniques from logic synthesis during mapping. By this, the t...
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Technology mapping for multiplexor (MUX) based field programmable gate arrays (FPGAs) has widely been considered. A new algorithm is proposed that applies techniques from logic synthesis during mapping. By this, the target technology is considered in the minimization process. Binary decision diagrams (BDDs) are used as an underlying data structure due to the close relation between BDDs and MUX netlists. The algorithm uses local don't cares obtained by a greedy algorithm. The mapping is sped up by computing signatures. A trade-off quality versus runtime can be specified by the user by setting different parameters. Experimental results comparing the approach to the best known results show improvements of more than 30% for area and 40% for delay for many instances.
Multi-valued decision diagrams (MDDs) are a generalization of binary decision diagrams (BDDs). They often allow efficient representation of functions with multi-valued input variables similar to BDDs in the binary cas...
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Multi-valued decision diagrams (MDDs) are a generalization of binary decision diagrams (BDDs). They often allow efficient representation of functions with multi-valued input variables similar to BDDs in the binary case. Therefore they are suitable for several applications in synthesis and verification of integrated circuits. MDD sizes counted in number of nodes vary from linear to exponential dependent on the variable ordering used. In all these applications, minimization of MDDs is crucial. In many cases, multi-valued variables are composed by a certain number of binary variables, and so the multi-valued inputs arise by grouping binary variables. The selection of these groups, that is, the decision which variables to merge, has enormous impact on MDD sizes. Techniques for finding variable groupings before starting MDD minimization have been proposed recently. In this paper we present a new method that uses re-encoding, i.e. dynamic variable grouping. We don't choose one fixed variable grouping before minimizing MDDs, but allow to change the binary variables to be considered together during the minimization process. This is possible since MDDs are simulated on top of BDDs. By this, the underlying binary variables remain accessible throughout the minimization process. This technique is described in detail and we also show experimental results that demonstrate the efficiency of our approach.
Decision Diagrams (DDs) are a data structure for the representation and manipulation of discrete logic functions often applied in VLSI CAD. Common DDs to represent Boolean functions are Binary Decision Diagrams (BDDs)...
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Decision Diagrams (DDs) are a data structure for the representation and manipulation of discrete logic functions often applied in VLSI CAD. Common DDs to represent Boolean functions are Binary Decision Diagrams (BDDs). Multiple-valued logic functions can be represented by multiple-valued Decision Diagrams (MDDs). The effiency of a DD representation strongly depends on the variable ordering; the size may vary from linear to exponential. Finding a good ordering is an NP-hard problem that has received considerable attention resulting in many minimization methods. Sifting is the most popular heuristic for dynamic DD minimization. In this paper we give lower bounds for sifting of MDDs. Based on them, both lower bound sifting for MDD minimization and lower bound group sifting for BDD minimization are proposed. By the computation of good lower bounds large parts of the search space can be pruned resulting in very fast computations. This is demonstrated by experimental results.
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