6,491 research outputs found
Algebraic Invariance Conditions in the Study of Approximate (Null-)Controllability of Markov Switch Processes
We aim at studying approximate null-controllability properties of a
particular class of piecewise linear Markov processes (Markovian switch
systems). The criteria are given in terms of algebraic invariance and are
easily computable. We propose several necessary conditions and a sufficient
one. The hierarchy between these conditions is studied via suitable
counterexamples. Equivalence criteria are given in abstract form for general
dynamics and algebraic form for systems with constant coefficients or
continuous switching. The problem is motivated by the study of lysis phenomena
in biological organisms and price prediction on spike-driven commodities.Comment: Mathematics of Control, Signals, and Systems, Springer Verlag
(Germany), 2015, online first
http://link.springer.com/article/10.1007/s00498-015-0146-
The power dissipation method and kinematic reducibility of multiple-model robotic systems
This paper develops a formal connection between the power dissipation method (PDM) and Lagrangian mechanics, with specific application to robotic systems. Such a connection is necessary for understanding how some of the successes in motion planning and stabilization for smooth kinematic robotic systems can be extended to systems with frictional interactions and overconstrained systems. We establish this connection using the idea of a multiple-model system, and then show that multiple-model systems arise naturally in a number of instances, including those arising in cases traditionally addressed using the PDM. We then give necessary and sufficient conditions for a dynamic multiple-model system to be reducible to a kinematic multiple-model system. We use this result to show that solutions to the PDM are actually kinematic reductions of solutions to the Euler-Lagrange equations. We are particularly motivated by mechanical systems undergoing multiple intermittent frictional contacts, such as distributed manipulators, overconstrained wheeled vehicles, and objects that are manipulated by grasping or pushing. Examples illustrate how these results can provide insight into the analysis and control of physical systems
An hybrid system approach to nonlinear optimal control problems
We consider a nonlinear ordinary differential equation and want to control
its behavior so that it reaches a target by minimizing a cost function. Our
approach is to use hybrid systems to solve this problem: the complex dynamic is
replaced by piecewise affine approximations which allow an analytical
resolution. The sequence of affine models then forms a sequence of states of a
hybrid automaton. Given a sequence of states, we introduce an hybrid
approximation of the nonlinear controllable domain and propose a new algorithm
computing a controllable, piecewise convex approximation. The same way the
nonlinear optimal control problem is replaced by an hybrid piecewise affine
one. Stating a hybrid maximum principle suitable to our hybrid model, we deduce
the global structure of the hybrid optimal control steering the system to the
target
Global controllability tests for geometric hybrid control systems
Hybrid systems are characterized by having an interaction between continuous
dynamics and discrete events. The contribution of this paper is to provide
hybrid systems with a novel geometric formulation so that controls can be
added. Using this framework we describe some new global controllability tests
for hybrid control systems exploiting the geometry and the topology of the set
of jump points, where the instantaneous change of dynamics take place.
Controllability is understood as the existence of a feasible trajectory for the
system joining any two given points. As a result we describe examples where
none of the continuous control systems are controllable, but the associated
hybrid system is controllable because of the characteristics of the jump set.Comment: 27 pages, 5 figure
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