## Journals

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DCDS

In this paper we provide a design methodology to compute control strategies for a primary dynamical system which is operating in a domain where other dynamical systems are present and the interactions between these systems and the primary one are of interest or are being pursued in some sense. The information from the other systems is available to the primary dynamical system only at discrete time instances and is assumed to be corrupted by noise. Having available only this limited and somewhat corrupted information which depends on the noise, the primary system has to make a decision based on the estimated behavior of other systems which may range from cooperative to noncooperative. This decision is reflected in a design of the most appropriate action, that is, control strategy of the primary system. The design is illustrated by considering some particular collision avoidance problem scenarios.

keywords:
stochastic processes
,
discrete observations.
,
control theory
,
estimation
,
robust control
,
Game theory

NACO

In this paper we consider a problem of designing control laws for
multiple mobile agents trying to accomplish three objectives. One
of the objectives is to sense a given compact domain while
satisfying the other objective which is to avoid collisions
between the agents themselves as well as with the obstacles. To
keep the communication links between the agents reliable, the
agents need to stay relatively close during the sensing operation
which is the third and final objective. The design of control laws
is based on carefully constructed objective functions and on an
assumption that the agents' dynamic models are nonlinear yet
affine in control laws. As an illustration of some performance
characteristics of the proposed control laws, a numerical example
is provided.

NACO

In paper [12] the problem of accomplishing multiple
objectives by a number of agents represented as dynamic systems is
considered. Each agent is assumed to have a goal which is to
accomplish one or more objectives where each objective is
mathematically formulated using an appropriate objective function.
Sufficient conditions for accomplishing objectives are formulated
using particular convergent approximations of minimum and maximum
functions depending on the formulation of the goals and
objectives. These approximations are differentiable functions and
they monotonically converge to the corresponding minimum or
maximum function. Finally, an illustrative pursuit-evasion game
example of a capture of two evaders by two pursuers is provided.

This note presents a preview of the treatment in [12].

This note presents a preview of the treatment in [12].

## Year of publication

## Related Authors

## Related Keywords

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