This paper is concerned with the problem of robust stability of a class of uncertain linear systems, where the system state-matrices considered are affinely dependent on the uncertain parameters. Affine parameter-dependent Lyapunov functions are exploited to prove stability, and a robust stability criterion for the above class of systems to be affinely quadratically stable (AQS) is given in ter...

Heliophysics is the branch of physics that investigates the interactions and correlation of different events across the Solar System. The mathematical models that describe and predict how physical events move across the solar system (ie. Propagation Models) are of great relevance. These models depend on parameters that users must set, hence the ability to correctly set the values is key to reli...

In this paper, a bond graph model based approach for robust FDI (Fault Detection and Isolation) in presence of parameter uncertainties is presented. Due to the energetic and multi physical properties of the Bond Graph, the whole of nonlinear model, structural analysis, residual with adaptive thresholds generations, and residual sensitivity analysis, can be synthesized using only one tool. This ...

Optimal control problems in batch distillation involve finding a trajectory for the reflux ratio so as to maximize a performance index. Then the controller is asked to follow this trajectory in an open loop fashion. It is important to minimize the effect of uncertainties in thermodynamic models on the optimal control profiles to achieve a better operating performance. The nonlinear parameter es...

[This corrects the article on p. 433 in vol. 107.].

We estimate the effect of the experimental uncertainty in the measurement of the temperature of the cosmic microwave background (CMB) on the extraction of cosmological parameters from future CMB surveys. We find that even for an ideal experiment limited only by cosmic variance up to l = 2500 for both the temperature and polarisation measurements, the projected cosmological parameter errors are ...

Higlights ► Interval analysis is proposed to study error propagation in MAP modelling for 3 fresh produce ► Results are compared to a probabilistic Monte-Carlo approach ► Low computational costs to estimate upper and lower O2 and CO2 limits ► MAP optimisation generates robust solutions for O2 and CO2 permeabilities, expressed as fuzzy sets ► Experimental efforts should focus on produce physiolo...

We propose a novel iterative algorithm for estimating a de-terministic but unknown parameter vector in the presence of Gaussian model uncertainties. This iterative algorithm is based on a system model where an overall noise term describes both, the measurement noise and the noise resulting from the model uncertainties. This overall noise term is a function of the true parameter vector. The prop...

Optimal control problems in batch distillation involve finding a trajectory for the reflux ratio so as to maximize a performance index. Then the controller is asked to follow this trajectory in an open loop fashion. It is important to minimize the effect of uncertainties in thermodynamic models on the optimal control profiles to achieve a better operating performance. The non-linear parameter e...

Abstract: The paper addresses the problem of output feedback guaranteed cost controller design for NCSs with time-delay and polytopic uncertainties. By constructing a new parameter-dependent Lyapunov functional and applying the free-weighting matrices technique, the parameter-dependent, delay-dependent design method will be obtained to synthesize a PID controllers achieving a guaranteed cost su...