http://ieeexplore.ieee.org TOC Alert for Publication# 9 2012 February 10 57 2 C1 C4 38 57 2 C2 C2 38 57 2 273 274 37 57 2 275 290 1113 57 2 291 301 729 $nu$ -gap metric sense. As such, the development includes the extension of $nu$-gap metric concepts to an irrational setting and the study of uncertainty-set connectedness in these terms. The main IQC based robust stability result is established for constantly-proper transfer functions in the Callier-Desoer algebra; i.e. finitely many unstable poles and a constant limit at infinity. Problems of structured robust stability analysis and robust performance analysis are considered to illustrate use of the main result. Several numerical examples are also presented. These include stability analysis of an autonomous system with uncertain time-delay and a closed-loop control system, accounting for both the gain and phase characteristics of the distributed-parameter uncertainty associated with the nominal rational plant model used for controller synthesis.]]> 57 2 302 317 862 $Sigma $ of a linear filter is needed to initialize the spectral estimation technique. The sample covariance estimate $ {mathhat {Sigma }}$, however, is usually not compatible with the filter. In this paper, we present a new, systematic way to overcome this difficulty. The new estimate $Sigma _{circ} $ is obtained by solving an ancillary problem with an entropic-type criterion. Extensive scalar and multivariate simulation shows that this new approach consistently leads to a significant improvement of the spectral estimators performances.]]> 57 2 318 329 590 57 2 330 343 976 57 2 344 359 672 $SE(3)$ . We first develop a passivity-based distributed velocity input law to achieve pose synchronization. We next show that the pose synchronizes exponentially fast under an assumption on the initial states of the bodies, with an exponential convergence rate given by algebraic connectivity of interconnection graphs. We also prove pose synchronization in the presence of communication delays and topology switches. We moreover give further extensions of the present law, where desirable velocities and collision avoidance are taken into account. Finally, the effectiveness of the present inputs is demonstrated through numerical simulations and experiments on a planar (2D) test bed.]]> 57 2 360 375 1480 57 2 376 391 1067 57 2 392 404 452 57 2 405 420 690 57 2 421 434 821 57 2 435 449 731 , a complete analysis was carried out for the case that sensor measurements and control inputs are delivered into a single packet to the estimator and to the actuators respectively. Here, a nontrivial generalization for MIMO systems is presented under the assumption that each sensor and each actuator exchange data with the control unit in an independent way by using their own data packet (no aggregation). In such a framework, it is shown that the separation principle still holds in the case where packet arrivals are acknowledged by the receiver. Moreover, the optimal LQG control is a linear function of the state that explicitly depends on the loss probabilities of the actuator channels. Such a dependence is not present in the single channel case considered in mean-square. In the infinite horizon case, stability conditions on the packet arrival probabilities are provided in terms of linear matrix inequalities (LMIs).]]> 57 2 450 456 477 57 2 457 462 200 57 2 462 467 245 $5n+1$ is designed to identify all the $3n+1$ parameters including the frequency, amplitude and phase for each of $n$ sinusoids, and the overall offset. As an alternative, a fifth-order parameter estimator is also derived for a biased single sinusoid. The derivations of the estimators are straightforward by using some treatments in the existing frequency estimators and the standard gradient algorithm. Global asymptotic convergence of the parameter estimation is verified. The originality of the work is the proposal of a first solution to the problem of identifying full parameters of a biased multi-sinusoidal signal with globally asymptotic convergence of the parameter estimation.]]> 57 2 467 472 253 57 2 472 477 206 57 2 478 483 310 57 2 484 489 218 57 2 489 494 244 57 2 494 499 324 57 2 500 505 299 ${cal L}_{2}$ gain of the ReO dealing with noise-corrupted systems is presented.]]> 57 2 506 511 243 57 2 511 516 266 57 2 517 522 277 57 2 522 528 427 57 2 528 534 404 57 2 534 539 324 57 2 540 540 205 57 2 C3 C3 42