Generative Adversarial Networks (GANs) have become a popular method to learn a probability model from data. Many GAN architectures with different optimization metrics have been introduced recently. Instead of proposing yet another architecture, this paper aims to provide an understanding of some of the basic issues surrounding GANs. First, we propose a natural way of specifying the loss functio...

Control of automotive exhaust emission has become an important research area to meet the more stringent automotive emission regulations. Beside the modification on internal combustion engine, control engineering is seen as another approach to improve and meet these requirements. This paper focuses on the design and development of a control system to reduce the harmful waste of automotive exhaus...

Based on a recently developed notion of physical realizability for quantum linear stochastic systems, we formulate a quantum LQG optimal control problem for quantum linear stochastic systems where the controller itself may also be a quantum system and the plant output signal can be fully quantum. Such a control scheme is often referred to in the quantum control literature as “coherent control.”...

An important problem in systems such as aerospace interiors, automobile passenger compartments and other cavities is the control of low frequency interior noise. Active control of this noise may offer a potentially better alternative to passive control due to constraints of weight and space. Active structural-acoustic control (ASAC) is considered as an attractive strategy especially for control...

Motivated by control applications over lossy packet networks, this paper considers the Linear Quadratic Gaussian (LQG) optimal control problem in the discrete time setting and when packet losses may occur between the sensors and the estimation-control unit and between the latter and the actuation points. Previous work [1] shows that, for protocols where packets are acknowledged at the receiver ...

We consider linear-quadratic-Gaussian (LQG) games with a major player and a large number of minor players. The major player has a significant influence on others. The minor players individually have negligible impact, but they collectively contribute mean field coupling terms in the individual dynamics and costs. To overcome the dimensionality difficulty and obtain decentralized strategies, the...

(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. ...

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 ...