Search

SUMMARY In this paper, a novel fault estimation strategy is proposed for a network of dynamical systems at a supervisory monitoring level. The network nodes include linear and Lipschitz nonlinear dynamics and time-varying coupling strength. The aim is to enhance the autonomy level of this class of systems by means of this inherently robust, nonlinear strategy based on sliding mode ideas. The faults are reconstructed from the equivalent output error injection signal which is used to maintain sliding. A key facet of the strategy is that the synthesis of the sliding mode observer for the network depends solely on the dynamics of an individual node of the network. The theoretical results developed in the paper are demonstrated with an example consisting of a network of pendulums. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper investigates the attack-resilient state estimation problem for linear systems with adversarial attacks and unknown inputs, where the upper bound of the unknown inputs is unknown. It is assumed that the attacker has limited resources and can only manipulate a certain number of sensors. In most of the existing observer design approaches for the systems with unknown inputs even in the absence of attacks, the observer matching condition should be satisfied. To overcome this restriction, a novel switched observer is proposed, where the matched unknown inputs will be completely compensated by means of the outputs and the mismatched part will be suppressed in terms of L2-gain rejection property. Meanwhile, the observer can provide an attack-resilient state estimation. Compared with the existing results, the proposed observer can guarantee that the resulting observer error system is stable with unknown input attenuation level γ that can be optimized. Finally, a simulation example of an unmanned ground vehicle is provided to show the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

This paper deals with estimation of total output of solar photovoltaic (PV) generators widely distributed in future power systems. In the proposed framework of estimation, the estimated signal in each frequency band is a linear combination of observed signals. The observation gain for each observed signal in each frequency band is designed through following two steps. First, an estimation error function is defined using assumed root mean square of output of PVs, predicted distribution of future PVs in the area, and correlation coefficients, which are identified in advance based on actual synchronized measurements of PVs. Second, observation gain in each frequency band is designed so as to minimize the estimation error function. The appropriateness of the proposed framework of estimation is demonstrated in small- and large-scale examples. [ABSTRACT FROM AUTHOR]