Mechanistic models in biology often involve numerous parameters about which we do not have direct experimental information. The traditional approach is to fit these parameters using extensive numerical simulations (e.g. by the Monte-Carlo method), and eventually revising the model if the predictions do not correspond to the actual measurements. In this work we propose a methodology for hybrid a...

It is known that the restarted full orthogonalization method (FOM) outperforms the restarted generalized minimum residual method (GMRES) in several circumstances for solving shifted linear systems when the shifts are handled simultaneously. On the basis of theWeightedArnoldi process, aweighted version of the Restarted Shifted FOM is proposed, which can provide accelerating convergence rate with...

In this paper, a class of discrete-time uncertain linear hybrid systems, which is affected by both parameter variations and exterior disturbances, is considered. The goal here is to synthesize a hybrid control law, which includes the continuous variable control law and the discrete event control signal, so as to guarantee the controlled invariance for a specific region in the hybrid state space...

In this paper we compare four recently proposed procedures for the identification of PieceWise AutoRegressive eXogenous (PWARX) and switched ARX models. We consider the clustering-based procedure, the bounded-error procedure, and the Bayesian procedure which all identify PWARX models. We also study the algebraic procedure, which identifies switched linear models. We introduce quantitative measu...

We formally derive the standard deterministic linear program (LP) for bid-price control by making an affine functional approximation to the optimal dynamic programming value function. This affine functional approximation gives rise to a new LP that yields tighter bounds than the standard LP. Whereas the standard LP computes static bid prices, our LP computes a time trajectory of bid prices. We ...

Motivated by the design of observers with good performance and robustness to measurement noise, the problem of estimating the state of a linear time-invariant system in finite time and robustly with respect to measurement noise is considered. Using a hybrid systems framework, a hybrid observer producing an estimate that converges to the plant state in finite time, even under unknown piecewise-c...

We consider a hybrid system consisting on two exible beams connected by a point mass. We prove that the presence of the point mass aaects the spectral gap when the inertia term does not vanish. This allows us to show that the system is well-posed in as ymmetric spaces in which solutions have one more degree of regularity to one side of the mass. The proofs combine classical techniques from asym...

Credit scoring has become a very important task as the credit industry has been experiencing double-digit growth rate during the past few decades. The artificial neural network is becoming a very popular alternative in credit scoring models due to its associated memory characteristic and generalization capability. However, the decision of network’s topology, importance of potential input variab...

In this paper, we consider the hierarchical control problem for a class of uncertain hybrid dynamical systems. The continuous dynamics of this class of uncertain hybrid systems are described by linear difference state equations, whose right side functions are unknown but lie within some convex hulls of known functions. Our control objective is for the closed loop system to exhibit a desired beh...