Abstract
We formulate and solve the control problem for stochastic nonlinear systems. The Lyapunov stability theory is applied to study the stability of closed-loop systems. The stabilizing controllers are designed using the information-theoretic approach. The results reported are applied to design control laws for an envisioned fluidic molecular electronic devices. By mimicking the brain neuron, we study the controlled propagation of Brownian particles (molecules) under the thermal, hydrodynamic, electrostatic and electromagnetic forces. The molecules are the information carriers in the fluidic gap junctions (cavity) of the considered molecular electronic devices. The molecule motion (evolution) and dynamics, which is described by the nonlinear stochastic differential equations, are controlled. The fundamental, analytical and numerical results are reported.
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