Sentence examples for both the system state from inspiring English sources

An asymptotic observer is first developed for the estimation of both the system state and unknown input.

Then, to tackle this design task, we begin by constructing an adaptive observer that allows estimating both the system state and the unknown catenary equivalent stiffness.

In this paper, a globally optimal filtering framework is developed for unbiased minimum-variance state estimation for systems with unknown inputs that affect both the system state and the output.

The motivation behind this innovation is that the resource management system has a holistic view of both the system state and jobs' activities and can dynamically control the jobs' status or allocate resource on the fly during their execution.

Thus, in the next Section, the aim is to compute an estimate of the state (varvec{z}), the catenary equivalent stiffness k, and the actual contact force F. In this section, we propose to design an observer that estimates both the system state z and the stiffness k.

This paper is concerned with the stabilization problem for a class of discrete-time Markovian jump linear systems with time-delays both in the system state and in the mode signal.

We consider the case that the random communication delays exist both in the system state and in the mode signal which are modeled as a Markov chain.

The system matrices are assumed to be uncertain within given intervals, the time delays appear in both the system states and the nonlinear disturbances, and the stochastic perturbation is in the form of a Brownian motion.

The designed filter estimates both the system states and the unknown input simultaneously and does not have many of the restrictive assumptions and restrictions that the existing unknown input filters do.

In the proposed approach, the optimal desired output trajectory for the transition sections is designed through a direct minimization of the output energy, and the needed control input that maintains the smoothness of both the output and the system state across all tracking transition switching is obtained through a preview-based stable-inversion approach.

The proposed solution is based on the backstepping control and an adaptive observer that estimates both the (unknown) catenary parameters and the system state.