
We study tracking control for stochastic differential equations of Langevin type and describe a new conceptual approach to the sampling problem for those systems. The objective is to guarantee the evolution of the mean value in a prescribed performance funnel around a given sufficiently smooth reference signal. To achieve this objective we design a novel funnel controller and show its feasibility under certain structural conditions on the potential energy. The control design does not require any specific knowledge of the shape of the potential energy. We illustrate the results by a numerical simulation for a double-well potential.
Optimization and Control (math.OC), FOS: Mathematics, Stochastic learning and adaptive control, adaptive control, Langevin dynamics, funnel control, Mathematics - Optimization and Control, Control/observation systems governed by ordinary differential equations, stochastic differential equations, Stochastic ordinary differential equations (aspects of stochastic analysis)
Optimization and Control (math.OC), FOS: Mathematics, Stochastic learning and adaptive control, adaptive control, Langevin dynamics, funnel control, Mathematics - Optimization and Control, Control/observation systems governed by ordinary differential equations, stochastic differential equations, Stochastic ordinary differential equations (aspects of stochastic analysis)
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