4,360 research outputs found
Backstepping controller synthesis and characterizations of incremental stability
Incremental stability is a property of dynamical and control systems,
requiring the uniform asymptotic stability of every trajectory, rather than
that of an equilibrium point or a particular time-varying trajectory. Similarly
to stability, Lyapunov functions and contraction metrics play important roles
in the study of incremental stability. In this paper, we provide
characterizations and descriptions of incremental stability in terms of
existence of coordinate-invariant notions of incremental Lyapunov functions and
contraction metrics, respectively. Most design techniques providing controllers
rendering control systems incrementally stable have two main drawbacks: they
can only be applied to control systems in either parametric-strict-feedback or
strict-feedback form, and they require these control systems to be smooth. In
this paper, we propose a design technique that is applicable to larger classes
of (not necessarily smooth) control systems. Moreover, we propose a recursive
way of constructing contraction metrics (for smooth control systems) and
incremental Lyapunov functions which have been identified as a key tool
enabling the construction of finite abstractions of nonlinear control systems,
the approximation of stochastic hybrid systems, source-code model checking for
nonlinear dynamical systems and so on. The effectiveness of the proposed
results in this paper is illustrated by synthesizing a controller rendering a
non-smooth control system incrementally stable as well as constructing its
finite abstraction, using the computed incremental Lyapunov function.Comment: 23 pages, 2 figure
A Contraction Theory Approach to Stochastic Incremental Stability
We investigate the incremental stability properties of It\^o stochastic
dynamical systems. Specifically, we derive a stochastic version of nonlinear
contraction theory that provides a bound on the mean square distance between
any two trajectories of a stochastically contracting system. This bound can be
expressed as a function of the noise intensity and the contraction rate of the
noise-free system. We illustrate these results in the contexts of stochastic
nonlinear observers design and stochastic synchronization.Comment: 23 pages, 2 figure
Transverse exponential stability and applications
We investigate how the following properties are related to each other: i)-A
manifold is "transversally" exponentially stable; ii)-The "transverse"
linearization along any solution in the manifold is exponentially stable;
iii)-There exists a field of positive definite quadratic forms whose
restrictions to the directions transversal to the manifold are decreasing along
the flow. We illustrate their relevance with the study of exponential
incremental stability. Finally, we apply these results to two control design
problems, nonlinear observer design and synchronization. In particular, we
provide necessary and sufficient conditions for the design of nonlinear
observer and of nonlinear synchronizer with exponential convergence property
Unconstrained receding-horizon control of nonlinear systems
It is well known that unconstrained infinite-horizon optimal control may be used to construct a stabilizing controller for a nonlinear system. We show that similar stabilization results may be achieved using unconstrained finite horizon optimal control. The key idea is to approximate the tail of the infinite horizon cost-to-go using, as terminal cost, an appropriate control Lyapunov function. Roughly speaking, the terminal control Lyapunov function (CLF) should provide an (incremental) upper bound on the cost. In this fashion, important stability characteristics may be retained without the use of terminal constraints such as those employed by a number of other researchers. The absence of constraints allows a significant speedup in computation. Furthermore, it is shown that in order to guarantee stability, it suffices to satisfy an improvement property, thereby relaxing the requirement that truly optimal trajectories be found. We provide a complete analysis of the stability and region of attraction/operation properties of receding horizon control strategies that utilize finite horizon approximations in the proposed class. It is shown that the guaranteed region of operation contains that of the CLF controller and may be made as large as desired by increasing the optimization horizon (restricted, of course, to the infinite horizon domain). Moreover, it is easily seen that both CLF and infinite-horizon optimal control approaches are limiting cases of our receding horizon strategy. The key results are illustrated using a familiar example, the inverted pendulum, where significant improvements in guaranteed region of operation and cost are noted
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