128 research outputs found
Locally optimal controllers and globally inverse optimal controllers
In this paper we consider the problem of global asymptotic stabilization with
prescribed local behavior. We show that this problem can be formulated in terms
of control Lyapunov functions. Moreover, we show that if the local control law
has been synthesized employing a LQ approach, then the associated Lyapunov
function can be seen as the value function of an optimal problem with some
specific local properties. We illustrate these results on two specific classes
of systems: backstepping and feedforward systems. Finally, we show how this
framework can be employed when considering the orbital transfer problem
Composite control Lyapunov functions for robust stabilization of constrained uncertain dynamical systems
This work presents innovative scientific results on the robust stabilization of constrained uncertain dynamical systems via Lyapunov-based state feedback control.
Given two control Lyapunov functions, a novel class of smooth composite control Lyapunov functions is presented. This class, which is based on the R-functions theory, is universal for the stabilizability of linear differential inclusions and has the following property. Once a desired controlled invariant set is fixed, the shape of the inner level sets can be made arbitrary close to any given ones, in a smooth and non-homothetic way. This procedure is an example of ``merging'' two control Lyapunov functions.
In general, a merging function consists in a control Lyapunov function whose gradient is a continuous combination of the gradients of the two parents control Lyapunov functions.
The problem of merging two control Lyapunov functions, for instance a global control Lyapunov function with a large controlled domain of attraction and a local one with a guaranteed local performance, is considered important for several control applications. The main reason is that when simultaneously concerning constraints, robustness and optimality, a single Lyapunov function is usually suitable for just one of these goals, but ineffective for the others.
For nonlinear control-affine systems, both equations and inclusions, some equivalence properties are shown between the control-sharing property, namely the existence of a single control law which makes simultaneously negative the Lyapunov derivatives of the two given control Lyapunov functions, and the existence of merging control Lyapunov functions.
Even for linear systems, the control-sharing property does not always hold, with the remarkable exception of planar systems.
For the class of linear differential inclusions, linear programs and linear matrix inequalities conditions are given for the the control-sharing property to hold.
The proposed Lyapunov-based control laws are illustrated and simulated on benchmark case studies, with positive numerical results
Nonlinear control synthesis by convex optimization
A stability criterion for nonlinear systems, recently derived by the third author, can be viewed as a dual to Lyapunov's second theorem. The criterion is stated in terms of a function which can be interpreted as the stationary density of a substance that is generated all over the state-space and flows along the system trajectories toward the equilibrium. The new criterion has a remarkable convexity property, which in this note is used for controller synthesis via convex optimization. Recent numerical methods for verification of positivity of multivariate polynomials based on sum of squares decompositions are used
Input-to-State Safety With Control Barrier Functions
This letter presents a new notion of input-to-state safe control barrier
functions (ISSf-CBFs), which ensure safety of nonlinear dynamical systems under
input disturbances. Similar to how safety conditions are specified in terms of
forward invariance of a set, input-to-state safety (ISSf) conditions are
specified in terms of forward invariance of a slightly larger set. In this
context, invariance of the larger set implies that the states stay either
inside or very close to the smaller safe set; and this closeness is bounded by
the magnitude of the disturbances. The main contribution of the letter is the
methodology used for obtaining a valid ISSf-CBF, given a control barrier
function (CBF). The associated universal control law will also be provided.
Towards the end, we will study unified quadratic programs (QPs) that combine
control Lyapunov functions (CLFs) and ISSf-CBFs in order to obtain a single
control law that ensures both safety and stability in systems with input
disturbances.Comment: 7 pages, 7 figures; Final submitted versio
Control Barrier Function Based Quadratic Programs for Safety Critical Systems
Safety critical systems involve the tight coupling between potentially
conflicting control objectives and safety constraints. As a means of creating a
formal framework for controlling systems of this form, and with a view toward
automotive applications, this paper develops a methodology that allows safety
conditions -- expressed as control barrier functions -- to be unified with
performance objectives -- expressed as control Lyapunov functions -- in the
context of real-time optimization-based controllers. Safety conditions are
specified in terms of forward invariance of a set, and are verified via two
novel generalizations of barrier functions; in each case, the existence of a
barrier function satisfying Lyapunov-like conditions implies forward invariance
of the set, and the relationship between these two classes of barrier functions
is characterized. In addition, each of these formulations yields a notion of
control barrier function (CBF), providing inequality constraints in the control
input that, when satisfied, again imply forward invariance of the set. Through
these constructions, CBFs can naturally be unified with control Lyapunov
functions (CLFs) in the context of a quadratic program (QP); this allows for
the achievement of control objectives (represented by CLFs) subject to
conditions on the admissible states of the system (represented by CBFs). The
mediation of safety and performance through a QP is demonstrated on adaptive
cruise control and lane keeping, two automotive control problems that present
both safety and performance considerations coupled with actuator bounds
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