The parameter-dependent Lyapunov function approach and linear matrix inequality (LMI) technique are applied to solve the filtering problem.
Based on a singular system approach and linear matrix inequality (LMI), a sufficient condition which guarantees the existence of linear switching surface and the stochastic stability of sliding mode dynamics is given.
By using Lyapunov function approach and linear matrix inequality techniques, a state feedback controller is designed to guarantee that the resulted closed-loop system is finite-time bounded and satisfies a given H∞ constraint condition.
The stabilization performance of the designed PSSs (by the proposed approach and linear power system model) on the LFO modes have been verified in two multi-machine power system standard models (IEEE 9-bus and 14-bus).
Based on free-weighting matrix approach and linear matrix inequality theory, a new set of sufficient conditions that guaranteeing the robust stochastic stability is presented by choosing an appropriate Lyapunov Krasovskii functional candidate.
Further, based on Lyapunov functional approach and linear matrix inequality technique, sufficient conditions are derived for the existence of the desired state feedback controller ensuring the stochastic finite-time bounded with prescribed H∞ performance index.
Furthermore, an average approach and linear model are proposed to isolate the receiver-dependent Uncalibrated Phase Delays (UPDs) from the SD ambiguities for CDMA Code Division Multiplee Access and FDMA Frequency Division Multiple Accessss) GNSS systems, respectively, to address ambiguity resolution.
The main objective in this study was to develop a rapid protein structure alignment tool by combining two fruitful strategies: geometry-based approach and linear encoding approach.
Longitudinal data analyses will be conducted, including the use of life table methods and person-time approaches, and generalized linear models will be developed using backward stepwise regression methods to identify factors associated with various health related outcomes.
The experimental investigation includes shake table experiments using a flexible laminar container, whereas the analytical component involves 1-D dynamic ground response analysis using linear approach and equivalent linear approach.
