Jump state estimation with multiple sensors with packet dropping and delaying channels

Abstract

PostprintThis work addresses the design of a state observer for systems whose outputs are measured through a communication network. The measurements from each sensor node are assumed to arrive randomly, scarcely and with a time-varying delay. The proposed model of the plant and the network measurement scenarios cover the cases of multiple sensors, out-of-sequence measurements, buffered measurements on a single packet and multi-rate sensor measurements. A jump observer is proposed, that selects a different gain depending on the number of periods elapsed between successfully received measurements and on the available data. A finite set of gains is precalculated off-line with a tractable optimization problem, where the complexity of the observer implementation is a design parameter. The computational cost of the observer implementation is much lower than in the Kalman filter, whilst the performance is similar. Several examples illustrate the observer design for different measurements scenarios and observer complexity and show the achievable performance.

Co-design of jump estimators and transmission policies for wireless multi-hop networks with fading channels

“…[24,28]). Motivated by offering low cost alternatives, we explore in this work the use of precalculated gains that alleviate the computing requirements [8,13,30]. As background to our current work, the authors in [30] proposed a jump linear estimator whose gains depend on the history of measurement transmission outcomes.…”

Networked gain‐scheduled fault diagnosis under control input dropouts without data delivery acknowledgment

“…Generally, when dealing with dropouts, the existing observer‐based fault detection and estimation algorithms only consider measurement losses either by focusing on filter design or by assuming that the control input being applied at the plant is known when updating the observer . Concerning measurements dropouts, the use of jump observers whose modes are related to the measurement transmission outcome improves estimation performances (with respect to gain‐invariant approaches) and has been employed to fault detection in . But, when the controller and fault diagnoser are collocated, and the controller to actuator link is offered by a network without successful delivery acknowledgment (motivated by reducing the network resource consumption, e.g., power and bandwidth), the aforementioned methods are not applicable and lead to poor performances.…”

Co-design ofH∞jump observers for event-based measurements over networks

“…The gains are computed off-line once, and the centralized observer chooses the applicable gain depending on the availability of new measurements (see Smith and Seiler (2003); Dolz et al (2014) for other jump observers applicable on networked control systems). With the estimator defined by (3) and (7), we obtain the state estimation error dynamics given byx…”