(Received ?? and in revised form ??) We study by a fully nonlinear, three-dimensional pseudospectral, time-splitting simulation the feedback control of a layer of fluid heated from below. The initial condition corresponds to a steady, large-amplitude, preferred convection state obtained at Prandtl number of 7.0 and Rayleigh number of 10 4 , which is about six times the Rayleigh critical value. ...

Semi-active base isolation system has been proposed mainly to mitigate the base drift of isolated structures while in most cases, its application causes the maximum acceleration of superstructure to be increased. In this paper, designing optimal semi-active base isolation system composed of linear base isolation system with low damping and magneto-rheological (MR) damper has been studied for co...

We study linear quadratic Gaussian (LQG) control design for port-Hamiltonian systems. To this end, we exploit the freedom in choosing weighting matrices and propose a specific choice which leads to an LQG controller is and, thus, particular stable passive. Furthermore, construct reduced-order via balancing subsequent truncation. This approach closely related classical balanced truncation shares...

We consider linear-quadratic Gaussian (LQG) games in which players have quadratic payoffs that depend on the players' actions and an unknown payoff-relevant state, signals state follow a distribution conditional realization. An information designer decides fidelity of revealed to order maximize social welfare or reduce disagreement among actions. Leveraging semi-definiteness design problem, we ...

Abstract A control design scheme is formulated for a pressurized water type nuclear power plant by integrating the optimal linear quadratic Gaussian (LQG) with robust integral sliding mode (ISM) technique. novel robust-optimal hybrid further proposed LQG-ISM technique loop transfer recovery approach to enhance effectiveness and robustness capability. The architecture offers performance minimum ...

We solve the linearly constrained linear-quadratic LQ and linear-quadratic-Gaussian LQG optimal control problems. Closed form expressions of the optimal controls are derived, and the Separation Theorem is generalized.

In this paper we study an imitation and transfer learning setting for Linear Quadratic Gaussian (LQG) control, where (i) the system dynamics, noise statistics cost function are unknown expert data is provided (that is, sequences of optimal inputs outputs) to learn LQG controller, (ii) multiple control tasks performed same but with different costs. We show that controller can be learned from a s...