In this paper, we treat the fundamental problem of state estimation for a class of linear impulsive systems with time-driven impulsive effects. We show that a strong observability property enables an impulsive observer to be constructed that yields uniformly exponentially stable estimation error dynamics. This approach accommodates impulsive systems with arbitrarily-spaced impulse times and singular state transition matrices in a manner reminiscent of well-known results for time-varying discrete-time linear systems. As an example, an observer is constructed for an impulsive system that produces general cubic spline signals.
This paper presents the results of a demonstration featuring the application of a validation protocol to a vibration-based structural damage sensing system. The results of the full validation study highlight the general protocol feasibility, emphasize the importance of evaluating key application characteristics prior to the POD study, and demonstrate an approach to quantify varying sensor durability on the POD performance. Challenges remain to properly address long time-scale effects with accelerated testing and large testing requirements due to the independence of the inspection of each flaw location.
This paper shows that if output regulation with internal stability is achievable via continuous-time error feedback then the same is true using sampled error feedback, discrete-time compensation, and a generalized hold device that generates the continuous-time control signal. In this scheme, the memoryless generalized hold together with the dynamic discrete-time compensator act as a continuous-time internal model of the exosystem. The approach involves casting the hybrid sampled-data system as a continuous-time system with periodically occurring jumps. Basic geometric concepts of invariant and controlled invariant subspaces are developed for linear systems with jumps to facilitate the analysis and the construction of compensators that solve the problem.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.