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...

Slope stability analysis is a geotechnical engineering problem characterized by many sources ofuncertainty. In slope stability computations, some of these sources are encountered, such as geologicaldetails missed in the exploration program, estimation of soil properties that are difficult to quantifyand many other relevant factors. Therefore, accurate reproduction of the spatial variability in ...

-As an alternative to Kalman filtering, a risk-sensitive filtering is proposed for a linear time-varying fading channel estimation problem and its robustness against the parameter and process noise uncertainty in the channel model is explored. The time-varying channel estimation problem is formulated as time varying Finite Impulse Response (FIR) filter with a known rectangular pulse at input an...

Portion size estimation is expected to be one of the largest sources of uncertainty in dietary assessment of the individual. Therefore, we demonstrated a method to quantify uncertainty due to portion size estimation in the usual intake distributions of vegetables, fruit, bread, protein, and potassium. Dutch participants of the European Food Consumption Validation study completed 2 nonconsecutiv...

The goal of geoacoustic inversion is to estimate environmental parameters from measured acoustic fields from e.g. a towed array. Though the inversion results have some uncertainty, inversion is an efficient technique to estimate environment parameters. Based on the a posteriori probability density of environmental parameters obtained from inversion, we perform statistical estimation of transmis...

The estimation of reward outcomes for action candidates is essential for decision making. In this study, we examined whether and how the uncertainty in reward outcome estimation affects the action choice and learning rate. We designed a choice task in which rats selected either the left-poking or right-poking hole and received a reward of a food pellet stochastically. The reward probabilities o...

In this paper, a parameter and uncertainty bound estimation functions for adaptive-robust control of robot manipulators are developed. A Lyapunov function is defined and parameters and uncertainty bound estimation functions are developed based on the Lyapunov function. Thus, stability of an uncertain system is guaranteed and uniform boundedness of the tracking error is achieved. As distinct fro...

The probability hypothesis density (PHD) methodology is widely used by the research community for the purposes of multiple object tracking. This problem consists in the recursive state estimation of several targets by using the information coming from an observation process. The purpose of this paper is to investigate the potential of the PHD filters for real-time traffic state estimation. This...