We present a common framework for Bayesian emulation methodologies for multivariate output simulators, or computer models, that employ either parametric linear models or non-parametric Gaussian processes. Novel diagnostics suitable for multivariate covariance separable emulators are developed and techniques to improve the adequacy of an emulator are discussed and implemented. A variety of emula...

Reliable spatial uncertainty evaluation of object detection models is special interest and has been subject recent work. In this work, we review the existing definitions for calibration probabilistic regression tasks. We inspect properties common networks extend state-of-the-art recalibration methods. Our methods use a Gaussian process (GP) scheme that yields parametric distributions as output ...

In this paper, a synthetic jet actuators (SJA)-based nonlinear robust controller is developed, which is capable of completely suppressing limit cycle oscillations (LCO) in UAV systems with parametric uncertainty in the SJA dynamics and unmodeled external disturbances. Specifically, the control law compensates for uncertainty in an input gain matrix, which results from the unknown airflow dynami...

Most of the practical systems are characterized by high uncertainty which makes it difficult to maintain good stability margins and performance properties for closed loop system. In case of conventional control, if plant parameter changes we cannot assure about the system performance hence it is necessary to design robust control for uncertain plant. Among the various strategies proposed to tac...

We present a novel approach for solving the probabilistic bounded reachability problem of hybrid systems with parameter uncertainty. Standard approaches to this problem require numerical solutions for large optimization problems, and become unfeasible for systems involving nonlinear dynamics over the reals. Our approach combines randomized sampling of probabilistic system parameters, SMT-based ...

We consider the effect of parametric uncertainty on properties of Linear Time Invariant systems. Traditional approaches to this problem determine the worst-case gains of the system over the uncertainty set. Whilst such approaches are computationally tractable, the upper bound obtained is not necessarily informative in terms of assessing the influence of the parameters on the system performance....

The problem of performing iterative detection (ID)—a technique originally introduced for the decoding of turbo codes—for systems having parametric uncertainty has received relatively little attention in the open literature. In this paper, the problem of adaptive ID (AID) for serial and parallel concatenated convolutional codes (SCCC’s and PCCC’s or turbo codes) in the presence of carrier-phase ...