Static controller for ventilation of highway tunnels

A control scheme for highway tunnels is proposed based on a static model of the highway tunnel. The controller is designed to keep the exhaust levels inside the tunnel below given limits. The controller is derived in two stages. First, a controller for an isolated ventilation section is found. Then a controller for a complex tunnel is obtained and the control is optimized by means of linear programming. The control is then simulated on a dynamical model of a highway tunnel

Entanglement of dark electron-nuclear spin defects in diamond

A promising approach for multi-qubit quantum registers is to use optically addressable spins to control multiple dark electron-spin defects in the environment. While recent experiments have observed signatures of coherent interactions with such dark spins, it is an open challenge to realize the individual control required for quantum information processing. Here we demonstrate the initialisation, control and entanglement of individual dark spins associated to multiple P1 centers, which are part of a spin bath surrounding a nitrogen-vacancy center in diamond. We realize projective measurements to prepare the multiple degrees of freedom of P1 centers - their Jahn-Teller axis, nuclear spin and charge state - and exploit these to selectively access multiple P1s in the bath. We develop control and single-shot readout of the nuclear and electron spin, and use this to demonstrate an entangled state of two P1 centers. These results provide a proof-of-principle towards using dark electron-nuclear spin defects as qubits for quantum sensing, computation and networks

Spinoza

"Spinoza", second edition. Encyclopedia entry for the Springer Encyclopedia of EM Phil and the Sciences, ed. D. Jalobeanu and C. T. Wolfe

Discretization of variational regularization in Banach spaces

Consider a nonlinear ill-posed operator equation $F(u)=y$ where $F$ is defined on a Banach space $X$. In general, for solving this equation numerically, a finite dimensional approximation of $X$ and an approximation of $F$ are required. Moreover, in general the given data \yd of $y$ are noisy. In this paper we analyze finite dimensional variational regularization, which takes into account operator approximations and noisy data: We show (semi-)convergence of the regularized solution of the finite dimensional problems and establish convergence rates in terms of Bregman distances under appropriate sourcewise representation of a solution of the equation. The more involved case of regularization in nonseparable Banach spaces is discussed in detail. In particular we consider the space of finite total variation functions, the space of functions of finite bounded deformation, and the $L^\infty$--space

Robust Smith Predictor Design for Time-Delay Systems with H∞ Performance

A new method for robust fixed-order H∞ controller design for uncertain time-delay systems is presented. It is shown that the H∞ robust performance condition can be represented by a set of convex constraints with respect to the parameters of a linearly parameterized primary controller in the Smith predictor structure. Therefore, the parameters of the primary controller can be obtained by convex optimization. The proposed method can be applied to stable SISO and MIMO models with uncertain dead-time and with multimodel and frequency-dependent uncertainty. It is also shown that how the design method can be extended to unstable SISO models. The design of robust gain-scheduled dead-time compensators is also investigated. The performance of the method is illustrated for both SISO and MIMO systems by simulation examples

L2 sampled signal reconstruction with causality constraints - Part I: Setup and solutions

This paper studies the problem of reconstructing an analog signal from its sampled measurements, in which the sampler (acquisition device) is given and the reconstructor (interpolator/hold) is the design parameter. We formulate this problem as an L2 (Wiener/Kalman filtering like) optimization problem and place the main emphasis on a systematic incorporation of causality constraints into the design procedure. Specifically, the optimization problem is solved under the constraint that the interpolation kernel is l-causal for a given l in N, i.e., that its impulse response is zero in the time interval (-infty,-lh), where h is the sampling period. We present a closed-form state-space solution of the problem, which can be efficiently calculated and implemented

L2 sampled signal reconstruction with causality constraints - Part II: Theory

This paper provides the theoretic foundation for the design of optimal reconstructors (also known as interpolators/holds) with a prescribed degree of causality. A compact frequency- domain solution is derived that mimics known interpolation tech- niques for ordinary transfer functions. In parallel, an extensive state space solution is documented. It complements the frequency- domain solution in that it constructively proves the various claims, and it also makes the solution concrete. The state space solution re- quires the solution of one Riccati and one Lyapunov matrix equation