With reference to an optimal control problem where the state has to approach asymptotically a closed target while paying a non-negative integral cost, we propose a generalization of the classical dissipative relation that defines a Control Lyapunov Function to a weaker differential inequality. The latter involves both the cost and the iterated Lie brackets of the vector fields in the dynamics up to a certain degree k = 1, and we call any of its (suitably defined) solutions a degree -k Minimum Restraint Function. We prove that the existence of a degree -k Minimum Restraint Function allows us to build a Lie-bracket-based feedback which sample stabilizes the system to the target while regulating (i.e., uniformly bounding) the cost
In this paper we develop a new approach to the design and analysis of state-feedback control laws ba...
For a broad class of nonlinear systems, we construct smooth control-Lyapunov functions. We assume ou...
This paper proposes an optimization with penalty-based feedback design framework for safe stabilizat...
For a given closed target we embed the dissipative relation that defines a control Lyapunov funct...
We extend the well known concepts of sampling and Euler solutions for control systems associated to...
We consider an optimal control problem where the state has to approach asymp -totically a closed tar...
AbstractThe problem considered is the existence and construction of an asymptotically stabilizing fe...
International audienceWe consider a control problem where the state must approach asymptotically a t...
International audienceGiven a locally defined, nondifferentiable but Lipschitz Lyapunov function, we c...
International audienceWe consider a control problem where the state must approach asymptotically a t...
International audienceGiven a locally defined, nondifferentiable but Lipschitz Lyapunov function, we c...
A new approach to feedback control design based on optimal control is proposed. Instead of expensive...
We consider a control problem where the state must approach asymptotically a target C while paying a...
We provide a formula for a stabilizing feedback law using a bounded control, under the assumption th...
International audienceGiven a locally defined, nondifferentiable but Lipschitz Lyapunov function, we c...
In this paper we develop a new approach to the design and analysis of state-feedback control laws ba...
For a broad class of nonlinear systems, we construct smooth control-Lyapunov functions. We assume ou...
This paper proposes an optimization with penalty-based feedback design framework for safe stabilizat...
For a given closed target we embed the dissipative relation that defines a control Lyapunov funct...
We extend the well known concepts of sampling and Euler solutions for control systems associated to...
We consider an optimal control problem where the state has to approach asymp -totically a closed tar...
AbstractThe problem considered is the existence and construction of an asymptotically stabilizing fe...
International audienceWe consider a control problem where the state must approach asymptotically a t...
International audienceGiven a locally defined, nondifferentiable but Lipschitz Lyapunov function, we c...
International audienceWe consider a control problem where the state must approach asymptotically a t...
International audienceGiven a locally defined, nondifferentiable but Lipschitz Lyapunov function, we c...
A new approach to feedback control design based on optimal control is proposed. Instead of expensive...
We consider a control problem where the state must approach asymptotically a target C while paying a...
We provide a formula for a stabilizing feedback law using a bounded control, under the assumption th...
International audienceGiven a locally defined, nondifferentiable but Lipschitz Lyapunov function, we c...
In this paper we develop a new approach to the design and analysis of state-feedback control laws ba...
For a broad class of nonlinear systems, we construct smooth control-Lyapunov functions. We assume ou...
This paper proposes an optimization with penalty-based feedback design framework for safe stabilizat...