Results 1  10
of
62
A ComponentBased Approach to Modeling and Simulating MixedSignal and Hybrid Systems
 ACM Trans. on Modeling and Computer Simulation, special
, 2003
"... Systems with both continuous and discrete behaviors can be modeled using a mixedsignal style or a hybrid systems style. This paper presents a componentbased modeling and simulation framework that supports both modeling styles. The component framework, based on an actor metamodel, takes a hierarch ..."
Abstract

Cited by 21 (9 self)
 Add to MetaCart
(Show Context)
Systems with both continuous and discrete behaviors can be modeled using a mixedsignal style or a hybrid systems style. This paper presents a componentbased modeling and simulation framework that supports both modeling styles. The component framework, based on an actor metamodel, takes a hierarchical approach to manage heterogeneity in modeling complex systems. We describe how ordinary differential equations, discreteevent systems, and finite state machines can be built under this metamodel. A mixedsignal system is a hierarchical composition of continuoustime and discreteevent models, and a hybrid system is a hierarchical composition of continuoustime and finitestatemachine models. Hierarchical composition and information hiding help building clean models and efficient execution engines. Simulation technologies, in particular, the interaction between a continuoustime ODE solving engine and various discrete simulation engines are discussed. A signal type system is introduced to schedule hybrid components inside a continuoustime 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 discreteevent environment. The technologies are implemented in the Ptolemy II software environment. Examples are given to show the applications of this framework in mixedsignal 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 multistage solution of combinatorial optimization p ..."
Abstract

Cited by 15 (2 self)
 Add to MetaCart
(Show Context)
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 multistage solution of combinatorial optimization problems. Ant programming searches for the optimal policy of a multistage 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
"... ..."
(Show Context)
Approximate Identification and Control Design  with application to a mechanical system
, 1992
"... ..."
Global stabilization for linear continuous timevarying systems
"... In this paper, stabilization problem via static output feedback controls for linear timevarying systems is investigated. Based on the Lyapunov function techniques, we show that for linear timevarying systems the global nullcontrollability guarantees the output feedback stabilization. The verifiabl ..."
Abstract

Cited by 5 (2 self)
 Add to MetaCart
(Show Context)
In this paper, stabilization problem via static output feedback controls for linear timevarying systems is investigated. Based on the Lyapunov function techniques, we show that for linear timevarying systems the global nullcontrollability 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 timevarying 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 ..."
Abstract

Cited by 4 (2 self)
 Add to MetaCart
(Show Context)
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 multistage solution of a combinatorial optimization problem. Such an insight
Invariant Subspace Methods in Linear MultivariableDistributed Systems and LumpedDistributed Network Synthesis
, 1976
"... Linear multivariabledistributed systems and synthesis problems for lumpeddistributed networks are analyzed. The methgods used center around the invariant subspace theory of HelsonLax and the theory of vectorial Hardy functions. Statespace and transfer function models are studied and their relati ..."
Abstract

Cited by 4 (0 self)
 Add to MetaCart
Linear multivariabledistributed systems and synthesis problems for lumpeddistributed networks are analyzed. The methgods used center around the invariant subspace theory of HelsonLax and the theory of vectorial Hardy functions. Statespace 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 wellkbown 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 infinitedimensional 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. Combined 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, ..."
Abstract

Cited by 4 (0 self)
 Add to MetaCart
(Show Context)
Abstract. Algorithms for nonstationary linear stabilization are constructed. Combined 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
"... ..."
(Show Context)
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 ..."
Abstract

Cited by 3 (0 self)
 Add to MetaCart
(Show Context)
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