6 research outputs found
On stabilization of nonlinear systems with drift by time-varying feedback laws
This paper deals with the stabilization problem for nonlinear control-affine
systems with the use of oscillating feedback controls. We assume that the local
controllability around the origin is guaranteed by the rank condition with Lie
brackets of length up to 3. This class of systems includes, in particular,
mathematical models of rotating rigid bodies. We propose an explicit control
design scheme with time-varying trigonometric polynomials whose coefficients
depend on the state of the system. The above coefficients are computed in terms
of the inversion of the matrix appearing in the controllability condition. It
is shown that the proposed controllers can be used to solve the stabilization
problem by exploiting the Chen-Fliess expansion of solutions of the closed-loop
system. We also present results of numerical simulations for controlled Euler's
equations and a mathematical model of underwater vehicle to illustrate the
efficiency of the obtained controllers.Comment: This is the author's version of the manuscript accepted for
publication in the Proceedings of the 12th International Workshop on Robot
Motion Control (RoMoCo'19
Obstacle Avoidance Problem for Second Degree Nonholonomic Systems
In this paper, we propose a new control design scheme for solving the
obstacle avoidance problem for nonlinear driftless control-affine systems. The
class of systems under consideration satisfies controllability conditions with
iterated Lie brackets up to the second order. The time-varying control strategy
is defined explicitly in terms of the gradient of a potential function. It is
shown that the limit behavior of the closed-loop system is characterized by the
set of critical points of the potential function. The proposed control design
method can be used under rather general assumptions on potential functions, and
particular applications with navigation functions are illustrated by numerical
examples.Comment: This is the author's accepted version of the paper to appear in: 2018
IEEE Conference on Decision and Control (CDC), (c) IEE
On a class of generating vector fields for the extremum seeking problem: Lie bracket approximation and stability properties
In this paper, we describe a broad class of control functions for extremum
seeking problems. We show that it unifies and generalizes existing extremum
seeking strategies which are based on Lie bracket approximations, and allows to
design new controls with favorable properties in extremum seeking and
vibrational stabilization tasks. The second result of this paper is a novel
approach for studying the asymptotic behavior of extremum seeking systems. It
provides a constructive procedure for defining frequencies of control functions
to ensure the practical asymptotic and exponential stability. In contrast to
many known results, we also prove asymptotic and exponential stability in the
sense of Lyapunov for the proposed class of extremum seeking systems under
appropriate assumptions on the vector fields
Motion planning and stabilization of nonholonomic systems using gradient flow approximations
Nonlinear control-affine systems with time-varying vector fields are
considered in the paper. We propose a unified control design scheme with
oscillating inputs for solving the trajectory tracking and stabilization
problems. This methodology is based on the approximation of a gradient like
dynamics by trajectories of the designed closed-loop system. As an intermediate
outcome, we characterize the asymptotic behavior of solutions of the considered
class of nonlinear control systems with oscillating inputs under rather general
assumptions on the generating potential function. These results are applied to
examples of nonholonomic trajectory tracking and obstacle avoidance.Comment: submitte
Extremum Seeking Approach for Nonholonomic Systems with Multiple Time Scale Dynamics
In this paper, a class of nonlinear driftless control-affine systems
satisfying the bracket generating condition is considered. A gradient-free
optimization algorithm is developed for the minimization of a cost function
along the trajectories of the controlled system. The algorithm comprises an
approximation scheme with fast oscillating controls for the nonholonomic
dynamics and a model-free extremum seeking component with respect to the output
measurements. Exponential convergence of the trajectories to an arbitrary
neighborhood of the optimal point is established under suitable assumptions on
time scale parameters of the extended system. The proposed algorithm is tested
numerically with the Brockett integrator for different choices of generating
functions.Comment: This is the author's version of the manuscript accepted for
publication in the Proceedings of The 21st IFAC World Congress 2020 (IFAC
2020
Constrained Extremum Seeking: a Modified-Barrier Function Approach
info:eu-repo/semantics/publishe