131 research outputs found
Linear Temporal Logic for Hybrid Dynamical Systems: Characterizations and Sufficient Conditions
This paper introduces operators, semantics, characterizations, and
solution-independent conditions to guarantee temporal logic specifications for
hybrid dynamical systems. Hybrid dynamical systems are given in terms of
differential inclusions -- capturing the continuous dynamics -- and difference
inclusions -- capturing the discrete dynamics or events -- with constraints.
State trajectories (or solutions) to such systems are parameterized by a hybrid
notion of time. For such broad class of solutions, the operators and semantics
needed to reason about temporal logic are introduced. Characterizations of
temporal logic formulas in terms of dynamical properties of hybrid systems are
presented -- in particular, forward invariance and finite time attractivity.
These characterizations are exploited to formulate sufficient conditions
assuring the satisfaction of temporal logic formulas -- when possible, these
conditions do not involve solution information. Combining the results for
formulas with a single operator, ways to certify more complex formulas are
pointed out, in particular, via a decomposition using a finite state automaton.
Academic examples illustrate the results throughout the paper.Comment: 35 pages. The technical report accompanying "Linear Temporal Logic
for Hybrid Dynamical Systems: Characterizations and Sufficient Conditions"
submitted to Nonlinear Analysis: Hybrid Systems, 201
Dynamical Properties of a Two-gene Network with Hysteresis
A mathematical model for a two-gene regulatory network is derived and several
of their properties analyzed. Due to the presence of mixed continuous/discrete
dynamics and hysteresis, we employ a hybrid systems model to capture the
dynamics of the system. The proposed model incorporates binary hysteresis with
different thresholds capturing the interaction between the genes. We analyze
properties of the solutions and asymptotic stability of equilibria in the
system as a function of its parameters. Our analysis reveals the presence of
limit cycles for a certain range of parameters, behavior that is associated
with hysteresis. The set of points defining the limit cycle is characterized
and its asymptotic stability properties are studied. Furthermore, the stability
property of the limit cycle is robust to small perturbations. Numerical
simulations are presented to illustrate the results.Comment: 55 pages, 31 figures.Expanded version of paper in Special Issue on
Hybrid Systems and Biology, Elsevier Information and Computation, 201
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Sufficient Conditions for Temporal Logic Specifications in Hybrid Dynamical Systems.
In this paper, we introduce operators, semantics, and conditions that, when possible, are solution-independent to guarantee basic temporal logic specifications for hybrid dynamical systems. Employing sufficient conditions for forward invariance and finite time attractivity of sets for such systems, we derive such sufficient conditions for the satisfaction of formulas involving temporal operators and atomic propositions. Furthermore, we present how to certify formulas that have more than one operator. Academic examples illustrate the results throughout the paper
Interconnected Observers for Robust Decentralized Estimation with Performance Guarantees and Optimized Connectivity Graph
Motivated by the need of observers that are both robust to disturbances and
guarantee fast convergence to zero of the estimation error, we propose an
observer for linear time-invariant systems with noisy output that consists of
the combination of N coupled observers over a connectivity graph. At each node
of the graph, the output of these interconnected observers is defined as the
average of the estimates obtained using local information. The convergence rate
and the robustness to measurement noise of the proposed observer's output are
characterized in terms of bounds. Several optimization problems
are formulated to design the proposed observer so as to satisfy a given rate of
convergence specification while minimizing the gain from noise to
estimates or the size of the connectivity graph. It is shown that that the
interconnected observers relax the well-known tradeoff between rate of
convergence and noise amplification, which is a property attributed to the
proposed innovation term that, over the graph, couples the estimates between
the individual observers. Sufficient conditions involving information of the
plant only, assuring that the estimate obtained at each node of the graph
outperforms the one obtained with a single, standard Luenberger observer are
given. The results are illustrated in several examples throughout the paper.Comment: The technical report accompanying "Interconnected Observers for
Robust Decentralized Estimation with Performance Guarantees and Optimized
Connectivity Graph" to be published in IEEE Transactions on Control of
Network Systems, 201
On Minimum-time Paths of Bounded Curvature with Position-dependent Constraints
We consider the problem of a particle traveling from an initial configuration
to a final configuration (given by a point in the plane along with a prescribed
velocity vector) in minimum time with non-homogeneous velocity and with
constraints on the minimum turning radius of the particle over multiple regions
of the state space. Necessary conditions for optimality of these paths are
derived to characterize the nature of optimal paths, both when the particle is
inside a region and when it crosses boundaries between neighboring regions.
These conditions are used to characterize families of optimal and nonoptimal
paths. Among the optimality conditions, we derive a "refraction" law at the
boundary of the regions that generalizes the so-called Snell's law of
refraction in optics to the case of paths with bounded curvature. Tools
employed to deduce our results include recent principles of optimality for
hybrid systems. The results are validated numerically.Comment: Expanded version of paper in Automatic
A Technical Result for the Study of High-gain Observers with Sign-indefinite Gain Adaptation
International audienceWe address the problem of state observation for a system whose dynamics may involve poorly known, perhaps even nonlocally Lipschitz functions and whose output measurement may be corrupted by noise. It is known that one way to cope with all these uncertainties and noise is to use a high-gain observer with a gain adapted on-line. As a difference from most previous results, we study such a solution with an adaptation law allowing both increase and decrease of the gain. The proposed method, while presented for a particular case, relies on a “generic” analysis tool based on the study of differential inequalities involving quadratic functions of the error system in two coordinate frames plus the gain adaptation law. We establish that, for bounded system solutions, the estimated state and the gain are bounded. Moreover, we provide an upper bound for the mean value of the error signals as a function of the observer parameters
Robust Observer Design for Hybrid Dynamical Systems with Linear Maps and Approximately Known Jump Times
This paper proposes a general framework for the state estimation of plants given by hybrid systems with linear flow and jump maps, in the favorable case where their jump events can be detected (almost) instantaneously. A candidate observer consists of a copy of the plant's hybrid dynamics with continuous-time and/or discrete-time correction terms multiplied by two constant gains, and with jumps triggered by those of the plant. Assuming that the time between successive jumps is known to belong to a given closed set allows us to formulate an augmented system with a timer which keeps track of the time elapsed between successive jumps and facilitates the analysis. Then, since the jumps of the plant and of the observer are synchronized, the error system has time-invariant linear flow and jump maps, and a Lyapunov analysis leads to sufficient conditions for the design of the observer gains for uniform asymptotic stability in three different settings: continuous and discrete updates, only discrete updates, and only continuous updates. These conditions take the form of matrix inequalities, which we solve in examples including cases where the time between successive jumps is unbounded or tends to zero (Zeno behavior), and cases where either both the continuous and discrete dynamics, only one of them, or neither of them are detectable. Finally, we study the robustness of this approach when the jumps of the observer are delayed with respect to those of the plant. We show that if the plant's trajectories are bounded and the time between successive jumps is lower-bounded away from zero, the estimation error is bounded, and arbitrarily small outside the delay intervals between the plant's and the observer's jumps
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