1,606 research outputs found
Mobile Formation Coordination and Tracking Control for Multiple Non-holonomic Vehicles
This paper addresses forward motion control for trajectory tracking and
mobile formation coordination for a group of non-holonomic vehicles on SE(2).
Firstly, by constructing an intermediate attitude variable which involves
vehicles' position information and desired attitude, the translational and
rotational control inputs are designed in two stages to solve the trajectory
tracking problem. Secondly, the coordination relationships of relative
positions and headings are explored thoroughly for a group of non-holonomic
vehicles to maintain a mobile formation with rigid body motion constraints. We
prove that, except for the cases of parallel formation and translational
straight line formation, a mobile formation with strict rigid-body motion can
be achieved if and only if the ratios of linear speed to angular speed for each
individual vehicle are constants. Motion properties for mobile formation with
weak rigid-body motion are also demonstrated. Thereafter, based on the proposed
trajectory tracking approach, a distributed mobile formation control law is
designed under a directed tree graph. The performance of the proposed
controllers is validated by both numerical simulations and experiments
Formation Shape Control Based on Distance Measurements Using Lie Bracket Approximations
We study the problem of distance-based formation control in autonomous
multi-agent systems in which only distance measurements are available. This
means that the target formations as well as the sensed variables are both
determined by distances. We propose a fully distributed distance-only control
law, which requires neither a time synchronization of the agents nor storage of
measured data. The approach is applicable to point agents in the Euclidean
space of arbitrary dimension. Under the assumption of infinitesimal rigidity of
the target formations, we show that the proposed control law induces local
uniform asymptotic stability. Our approach involves sinusoidal perturbations in
order to extract information about the negative gradient direction of each
agent's local potential function. An averaging analysis reveals that the
gradient information originates from an approximation of Lie brackets of
certain vector fields. The method is based on a recently introduced approach to
the problem of extremum seeking control. We discuss the relation in the paper
Identification of Hessian matrix in distributed gradient-based multi-agent coordination control systems
Multi-agent coordination control usually involves a potential function that
encodes information of a global control task, while the control input for
individual agents is often designed by a gradient-based control law. The
property of Hessian matrix associated with a potential function plays an
important role in the stability analysis of equilibrium points in
gradient-based coordination control systems. Therefore, the identification of
Hessian matrix in gradient-based multi-agent coordination systems becomes a key
step in multi-agent equilibrium analysis. However, very often the
identification of Hessian matrix via the entry-wise calculation is a very
tedious task and can easily introduce calculation errors. In this paper we
present some general and fast approaches for the identification of Hessian
matrix based on matrix differentials and calculus rules, which can easily
derive a compact form of Hessian matrix for multi-agent coordination systems.
We also present several examples on Hessian identification for certain typical
potential functions involving edge-tension distance functions and
triangular-area functions, and illustrate their applications in the context of
distributed coordination and formation control
A time-varying matrix solution to the Brockett decentralized stabilization problem
This paper proposes a time-varying matrix solution to the Brockett
stabilization problem. The key matrix condition shows that if the system matrix
product is a Hurwitz H-matrix, then there exists a time-varying diagonal
gain matrix such that the closed-loop minimum-phase linear system with
decentralized output feedback is exponentially convergent. The proposed
solution involves several analysis tools such as diagonal stabilization
properties of special matrices, stability conditions of diagonal-dominant
linear systems, and solution bounds of linear time-varying integro-differential
systems. A review of other solutions to the general Brockett stabilization
problem (for a general unstructured time-varying gain matrix ) and a
comparison study are also provided
Optimal control of nonlinear partially-unknown systems with unsymmetrical input constraints and its applications to the optimal UAV circumnavigation problem
Aimed at solving the optimal control problem for nonlinear systems with
unsymmetrical input constraints, we present an online adaptive approach for
partially unknown control systems/dynamics. The designed algorithm converges
online to the optimal control solution without the knowledge of the internal
system dynamics. The optimality of the obtained control policy and the
stability for the closed-loop dynamic optimality are proved theoretically. The
proposed method greatly relaxes the assumption on the form of the internal
dynamics and input constraints in previous works. Besides, the control design
framework proposed in this paper offers a new approach to solve the optimal
circumnavigation problem involving a moving target for a fixed-wing unmanned
aerial vehicle (UAV). The control performance of our method is compared with
that of the existing circumnavigation control law in a numerical simulation and
the simulation results validate the effectiveness of our algorithm
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