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62
A Component-Based Approach to Modeling and Simulating Mixed-Signal and Hybrid Systems
- ACM Trans. on Modeling and Computer Simulation, special
, 2003
"... Systems with both continuous and discrete behaviors can be modeled using a mixed-signal style or a hybrid systems style. This paper presents a component-based modeling and simulation framework that supports both modeling styles. The component framework, based on an actor meta-model, takes a hierarch ..."
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Cited by 21 (9 self)
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Systems with both continuous and discrete behaviors can be modeled using a mixed-signal style or a hybrid systems style. This paper presents a component-based modeling and simulation framework that supports both modeling styles. The component framework, based on an actor meta-model, takes a hierarchical approach to manage heterogeneity in modeling complex systems. We describe how ordinary differential equations, discrete-event systems, and finite state machines can be built under this meta-model. A mixed-signal system is a hierarchical composition of continuous-time and discrete-event models, and a hybrid system is a hierarchical composition of continuous-time and finite-state-machine models. Hierarchical composition and information hiding help building clean models and efficient execution engines. Simulation technologies, in particular, the interaction between a continuous-time ODE solving engine and various discrete simulation engines are discussed. A signal type system is introduced to schedule hybrid components inside a continuous-time environment. Breakpoints are used to control the numerical integration step sizes so that discrete events are handled properly. A "refiring" mechanism and a "rollback" mechanism are designed to manage continuous components inside a discrete-event environment. The technologies are implemented in the Ptolemy II software environment. Examples are given to show the applications of this framework in mixed-signal and hybrid systems.
Toward the formal foundation of ant programming
- in Ant Algorithms – Proceedings of ANTS 2002 – Third International Workshop, ser. LNCS, M. Dorigo et al., Eds
, 2002
"... Abstract. This paper develops the formal framework of ant programming with the goal of gaining a deeper understanding on ant colony optimization and, more in general, on the principles underlying the use of an iterated Monte Carlo approach for the multi-stage solution of combinatorial optimization p ..."
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Cited by 15 (2 self)
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Abstract. This paper develops the formal framework of ant programming with the goal of gaining a deeper understanding on ant colony optimization and, more in general, on the principles underlying the use of an iterated Monte Carlo approach for the multi-stage solution of combinatorial optimization problems. Ant programming searches for the optimal policy of a multi-stage decision problem to which the original combinatorial problem is reduced. In order to describe ant programming we adopt on the one hand concepts of optimal control, and on the other hand the ant metaphor suggested by ant colony optimization. In this context, a critical analysis is given of notions such as state, representation, and sequential decision process under incomplete information. 1
Dynamics of Viscoelastic Structures—A Time Domain, Finite Element Formulation,”
- Journal of Applied Mechanics,
, 1985
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Approximate Identification and Control Design -- with application to a mechanical system
, 1992
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Global stabilization for linear continuous time-varying systems
"... In this paper, stabilization problem via static output feedback controls for linear time-varying systems is investigated. Based on the Lyapunov function techniques, we show that for linear timevarying systems the global null-controllability guarantees the output feedback stabilization. The verifiabl ..."
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Cited by 5 (2 self)
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In this paper, stabilization problem via static output feedback controls for linear time-varying systems is investigated. Based on the Lyapunov function techniques, we show that for linear timevarying systems the global null-controllability guarantees the output feedback stabilization. The verifiable stabilizability conditions and output feedback control design are stated. The result can be applicable to the output feedback stabilizability of a class of nonlinear time-varying systems. Numerical examples illustrated the conditions are given.
For a Formal Foundation of the Ant Programming Approach to Combinatorial Optimization -- Part 1: The problem, the representation, and the general solution strategy
- ATR HUMAN INFORMATION PROCESSING RESEARCH LABORATORIES
, 2000
"... This paper develops the formal framework of ant programming with the goal of gaining a deeper understanding on ant colony optimization, a heuristic method for combinatorial optimization problems inspired by the foraging behavior of ants. Indeed, ant programming allows a deeper insight into the gener ..."
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Cited by 4 (2 self)
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This paper develops the formal framework of ant programming with the goal of gaining a deeper understanding on ant colony optimization, a heuristic method for combinatorial optimization problems inspired by the foraging behavior of ants. Indeed, ant programming allows a deeper insight into the general principles underlying the use of an iterated Monte Carlo approach for the multi-stage solution of a combinatorial optimization problem. Such an insight
Invariant Subspace Methods in Linear Multivariable-Distributed Systems and Lumped-Distributed Network Synthesis
, 1976
"... Linear multivariable-distributed systems and synthesis problems for lumped-distributed networks are analyzed. The methgods used center around the invariant subspace theory of Helson-Lax and the theory of vectorial Hardy functions. State-space and transfer function models are studied and their relati ..."
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Cited by 4 (0 self)
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Linear multivariable-distributed systems and synthesis problems for lumped-distributed networks are analyzed. The methgods used center around the invariant subspace theory of Helson-Lax and the theory of vectorial Hardy functions. State-space and transfer function models are studied and their relations analyzed. We single out a class of systems and networks with nonrational transfer functions (scattering matrices), for which several of the well-kbown results for lumped systems and networks are generalized. In particular we develop the relations between singularities of transfer functions and "natural modes" of the systems, a degree theory for infinite-dimensional linear systems and a synthesis via lossless embedding of the scattering matrix. Finally coprime factorizations for this class of systems are developed.
BROCKETT’S PROBLEM IN THE THEORY OF STABILITY OF LINEAR DIFFERENTIAL EQUATIONS
"... Abstract. Algorithms for nonstationary linear stabilization are constructed. Com-bined with a nonstabilizabiity criterion, these algorithms result in the solution of the Brockett problem in a number of cases. In the book [1], R. Brockett formulated the following problem. For a triplet of matrices A, ..."
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Abstract. Algorithms for nonstationary linear stabilization are constructed. Com-bined with a nonstabilizabiity criterion, these algorithms result in the solution of the Brockett problem in a number of cases. In the book [1], R. Brockett formulated the following problem. For a triplet of matrices A, B, and C, what conditions ensure the existence of a matrix K(t) such that the system (1)
Generalizations for the eigenvalue and pole concept with respect to linear timevarying systems
- Proc. ProRisc/IEEE Workshop CSSP, Mierlo, the
, 1997
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Initial Conditions, Generalized Functions, and the Laplace Transform Troubles at the origin
"... Version 5.5 The unilateral Laplace transform is widely used to analyze signals, linear models, and control systems, and is consequently taught to most engineering undergraduates. In our courses at MIT in the departments of electrical engineering and computer science, mathematics, and mechanical engi ..."
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Cited by 3 (0 self)
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Version 5.5 The unilateral Laplace transform is widely used to analyze signals, linear models, and control systems, and is consequently taught to most engineering undergraduates. In our courses at MIT in the departments of electrical engineering and computer science, mathematics, and mechanical engineering, we have found some significant pitfalls associated with teaching our students to understand and apply the Laplace transform. We have independently concluded that one reason students find the Laplace transform difficult is that there are significant confusions present in many of the standard textbook presentations of this subject, in all three of our disciplines. A key issue is the treatment of the origin. Many texts [1]–[5] define the Laplace transform of a time function f(t) as L{f(t)} = f(t)e −st dt