Inferential networked control with accessibility constraints in both the sensor and actuator channels

Quevedo

IFAC Proceedings Volumes

et al. 2014

This paper addresses the design of a state observer for networked systems with random delays and dropouts. The model of plant and network covers the cases of multiple sensors, out-of-sequence and buffered measurements. The measurement outcomes over a finite interval model the network measurement reception scenarios, which follow a Markov distribution. We present a tractable optimization problem to precalculate off-line a finite set of gains of jump observers. The proposed procedure allows us to trade the complexity of the observer implementation for achieved performance. Several examples illustrate that the online computational cost of the observer implementation is lower than that of the Kalman filter, whilst the performance is similar.

“…We address this problem with the cone complementarity linearization algorithm ( [3]) over a bisection algorithm. The algorithm is omitted for brevity; an example can be found in [7].…”

Section: B Numerical Issuesmentioning

confidence: 99%

Performance vs complexity trade-offs for Markovian networked jump estimators

Quevedo

IFAC Proceedings Volumes

et al. 2014

“…If the set of gains is also a function of the history of measurement availabilities (called finite loss history estimator in Smith and Seiler (2003)) a better performance is achieved at the cost of more implementation complexity in the selection of the appropriate gain. An intermediate approach in terms of storage and selector complexity consists of a dependency on the actual available measurements and on the number of consecutive dropouts since last available measurement (Peñarrocha et al (2012); Peñarrocha et al (2014)). …”

Section: Introductionmentioning

confidence: 99%

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

International Journal of Systems Science

Sanchis

2014

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.

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

Intl J Robust & Nonlinear

Sanchis

2015

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.