one of the most important economic factors is potential output. in macroeconomic models and structural studies, the estimation of potential output is necessary for projections and analyzing policy performances. there exist several methods for estimating potential output. meanwhile, its estimation is a difficult and complicated matter. empirical studies and researches show that using various tec...

tthe uncertainty estimation and compensation are challenging problems for the robust control of robot manipulators which are complex systems. this paper presents a novel decentralized model-free robust controller for electrically driven robot manipulators. as a novelty, the proposed controller employs a simple gaussian radial-basis-function network as an uncertainty estimator. the proposed netw...

The application of state-space-based subspace system identification methods to training-based estimation for timevarying MIMO frequency-selective channels is explored with the motivation of possible parsimonious parametrization and direct model complexity control. The comparison between the statespace-based channel estimation algorithm and the FIR-based RLS algorithm shows the former is a more ...

This paper develops a framework for state-space estimation when the parameters of the underlying linear model are subject to uncertainties. Compared with existing robust filters, the proposed filters perform regularization rather than de-regularization. It is shown that, under certain stabilizability and detectability conditions, the steady-state filters are stable and that, for quadratically-s...

A robust algorithm is developed for jointly controlling the power and rate of flow in a distributed wireless network. The dynamics of the network is modelled as a discrete-time state-delayed system with uncertainties and the proposed algorithm achieves better SIR performance than a conventional power control scheme. keywords: Robust estimation, congestion control, power control, rate control, w...

This paper deals with actuator fault estimation for a class of discrete-time Linear Parameter-Varying (LPV) descriptor systems. By considering the fault as an auxiliary state vector, an augmented system is established. Then, a fault estimation observer is designed based on the augmented system. In this paper, the fault estimation observer design is formulated as a Linear Matrix Inequality (LMI)...