Marius Giuclea

Semi-active suspension control : improved vehicle ride and road friendliness

Dampers and Vehicle Modelling.- Human Body Analysis.- Semi-active Control Algorithms.- Friction Dampers.- Magnetorheological Dampers.- Case Studies.

Probabilistic Cellular Automata

Cellular automata are binary lattices used for modeling complex dynamical systems. The automaton evolves iteratively from one configuration to another, using some local transition rule based on the number of ones in the neighborhood of each cell. With respect to the number of cells allowed to change per iteration, we speak of either synchronous or asynchronous automata. If randomness is involved to some degree in the transition rule, we speak of probabilistic automata, otherwise they are called deterministic. With either type of cellular automaton we are dealing with, the main theoretical challenge stays the same: starting from an arbitrary initial configuration, predict (with highest accuracy) the end configuration. If the automaton is deterministic, the outcome simplifies to one of two configurations, all zeros or all ones. If the automaton is probabilistic, the whole process is modeled by a finite homogeneous Markov chain, and the outcome is the corresponding stationary distribution. Based on our previous results for the asynchronous case-connecting the probability of a configuration in the stationary distribution to its number of zero-one borders-the article offers both numerical and theoretical insight into the long-term behavior of synchronous cellular automata.

Genetic Algorithms for Solving Systems of Fuzzy Relational Equations

We propose in this paper a unified method for approximating the solution of a System of Fuzzy Relational Equations (SFRE). The method is essentially based on the use of Genetic Algorithms (GA) and on a probabilistic algorithm for solving a SFRE — presented elsewhere. This approach is useful both in classical SFRE problems and in dynamic system identification. Some numerical results regarding both aspects show that our method can be successfully applied.

Predictability in Cellular Automata

Modelled as finite homogeneous Markov chains, probabilistic cellular automata with local transition probabilities in (0, 1) always posses a stationary distribution. This result alone is not very helpful when it comes to predicting the final configuration; one needs also a formula connecting the probabilities in the stationary distribution to some intrinsic feature of the lattice configuration. Previous results on the asynchronous cellular automata have showed that such feature really exists. It is the number of zero-one borders within the automatons binary configuration. An exponential formula in the number of zero-one borders has been proved for the 1-D, 2-D and 3-D asynchronous automata with neighborhood three, five and seven, respectively. We perform computer experiments on a synchronous cellular automaton to check whether the empirical distribution obeys also that theoretical formula. The numerical results indicate a perfect fit for neighbourhood three and five, which opens the way for a rigorous proof of the formula in this new, synchronous case.

A Genetic Algorithms Method for Fitting the Generalized Bouc-Wen Model to Experimental Asymmetric Hysteretic Loops

The Bouc-Wen class models are widely used to portray different types of hysteretic behavior. This paper presents an effective genetic algorithms-based method for fitting a generalized Bouc-Wen model, proposed by Song and Der Kiureghian [2006, “Generalized Bouc-Wen Model for Highly Asymmetric Hysteresis,” ASCE J. Eng. Mech., 132 (6), p. 610618], to highly asymmetric experimental hysteretic loops. The performance function is based on integral relationships derived from the generalized Bouc-Wen differential equation for each of the six different phases of asymmetric hysteretic loops. The conditions, which must be satisfied by the model parameters to obtain closed and smooth hysteretic loops, are specified. The method is applied to fit the generalized Bouc-Wen model to hysteretic loops, which are obtained in laboratory experiments for a new type of mounts used for base isolation of forging hammers. By using a single degree of freedom (SDOF) system with the predicted hysteretic characteristics, a remarkably close agreement between the measured and simulated vibrations of hammer was obtained.

Statistical Linearization of Hysteretic Systems Described by the Ramberg-Osgood Model

AbstractIn this paper, a statistical linearization method based on Rayleigh distribution is proposed for hysteretic systems described by the Ramberg-Osgood model. The method is based on the assumption that a set of hysteresis loops can be determined either from an analytical model or by laboratory experiments for imposed harmonic motion with different amplitudes, viewed as deviates from a Rayleigh distribution. A set of equivalent linear stiffness and damping coefficients, dependent on the distribution parameter, are assessed as functions of imposed motion amplitudes. Both the dissipated energy and stored elastic energy per cycle are determined using an accurate and simple analytical approximation of secant modulus, developed in the paper. The proposed method is applied for statistical linearization of a single-degree-of-freedom system equipped by hysteretic bracing devices with restrained buckling. The method is validated through numerical simulation of the output of the hysteretic and equivalent linear ...