Upon satisfying some conditions, the observer design problem can be solved via a Riccati inequality or a LMI-based technique with asymptotic estimation guaranteed.
This RUL estimation should: guarantee safe operation to EoL; output multiple RULs due to different failure modes; combine RULs with an uncertainty index to be trusted.
In the modified method, gain errors are first estimated and compensated before the other errors' estimation, which guarantees the position error estimation accuracy to be higher than that in the conventional method.
This paper investigates the state estimation with guaranteed performance for a class of switching fuzzy neural networks.
In all cases, proper tuning of the design parameters, i.e., the penalties on the states at the beginning of the estimation horizon, guarantees convergence of the estimation error to zero.
Results show that for tracking applications with severe accuracy constraints, the localization algorithms need to improve their estimations to guarantee the performance of target tracking algorithms.
Motivated by this consideration, in this paper we aim to establish some new sufficient conditions for the existence of state estimations which guarantee the error system for the discrete-time BAM neural networks with time-varying delays to be globally exponentially stable.
Furthermore, it is proved that the proposed estimator protocol can guarantee accurate estimation of the weighted average of the velocities and positions of the leaders in the finite-time.
The aim of the addressed problem is to design a state estimator such that the estimation performance is guaranteed in the mean-square sense against admissible stochastic time-delays, stochastic noises as well as stochastic fading signals.
AP information with low RSSI should be filtered (i.e., zero or very low weight on the AP with low RSSI) to guarantee estimation quality.
In this paper, we propose a distributed neighbor coordinated adaptive power control estimation mechanism to guarantee a reliable protection for primary users.
