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

Abstract

Summary This paper investigates the fault diagnosis problem for discrete‐time networked control systems under dropouts in both control and measurement channel with no delivery acknowledgment. We propose to use a proportional integral observer‐based fault diagnoser collocated with the controller. The observer estimates the faults and computes a residual signal whose comparison with a threshold alarms the fault appearance. We employ the expected value of the arriving control input for the open‐loop estimation and the measurement reception scenario for the correction with a jump observer. The jumping gains are scheduled in real time with rational functions depending on a statistic of the difference between the control command being applied in the plant and the one being used in the observer. We design the observer, the residual, and the threshold to maximize the sensitivity under faults while guaranteeing some minimum detectable faults under a predefined false alarm rate. Exploiting sum‐of‐squares decomposition techniques, the design procedure becomes an optimization problem over polynomials. Copyright © 2015 John Wiley & Sons, Ltd.

Event-triggered predictor-based control with gain-Scheduling and extended state observer for networked control systems

“…Thus, the measurement data packets will be transmitted from the local sensor to the remote controller if the condition (19) is satisfied. We emphasize that the control and observer gains K w , K and L defined in (10), (11) and (14) respectively, together with the event-triggered parameters Ω u , σ u , Ω y , σ y defined in (9) and (19), are designed not only to stabilize the closed-loop control system, but also to reduce the bandwidth usage as far as possible, while satisfying different performance criterions: maximum disturbance attenuation in the sense of H ∞ norm, steady-state rejection of mismatched disturbances with known dynamics, and robustness against timevarying delays. Remark 1.…”

“…For instance, the effect of time-varying delays has been tackled under different control schemes: via state-feedback control [4], multi-rate control [33], state estimators [26], [30], and reset-based control in [2], [31]. Packet dropouts have been faced using predictive control [20], predictor-observer methods [5,8], gain scheduling [9], etc. Packet disordering has also been investigated in [22,23,37] by introducing different packet reordering mechanisms, and in [33,7,6] by using dual-rate control.…”

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

“…n y ). In order to make the problem numerically tractable we use the sum of squares (SOS) decomposition (Chesi (2010); Peñarrocha et al (2013Peñarrocha et al ( , 2014; Dolz et al (2015)) to define sufficient conditions to accomplish with the previous guaranteed performance. The idea is to consider the probabilities β i [t] on the previous LMI constraint as new variables of the problem and thus transform it into a polynomial matrix inequality (PMI).…”

Robust nonlinear filter for nonlinear systems with multiplicative noise uncertainties, unknown external disturbances, and packet dropouts

“…In , the fault diagnosis problem for discrete‐time networked control systems under dropouts in both control and measurement channel with no delivery acknowledgment is investigated. In , the authors investigate the linear minimum mean square error (MSE) estimation problem for ‐type differential equation systems with random delays. It is worth mentioning that in , the filtering problems for linear system with uncertain measurements are concerned.…”

“…In , the authors investigate the linear minimum mean square error (MSE) estimation problem for ‐type differential equation systems with random delays. It is worth mentioning that in , the filtering problems for linear system with uncertain measurements are concerned. However, the nonlinear filtering problem for nonlinear systems with packet dropouts is not addressed.…”