Filetype
Modern industrial robots are fast and have very good repetitional accuracy, which have made them indispensable in many manufacturing applications. However, they are usually programmed to follow desired trajectories and only get feedback from position sensors. This works fine as long as the environment is very well structured, but does not give good robustness to objects not being positioned or gri
This contribution reviews theory, algorithms, and validation results for system identification of continuous-time state-space models from finite input-output sequences. The algorithms developed are autoregressive methods, methods of subspace-based model identification and stochastic realization adapted to the continuous-time context. The resulting model can be decomposed into an input-output model
The focus of this article is to undertake a comparative analysis of multi-step-ahead linear multivariate predictors. The approach considered for the estimation will be based on geometrically reliable linear algebra tools, resorting to subspace identification methods. A crucial issue is quantification of both bias error and variance affecting the estimate of the prediction for increasing values of
In this thesis, a class of linear time-invariant systems is identified for which a particular type of H-infinity optimal control problem can be solved explicitly. It follows that the synthesized controller can be given on a simple explicit form. More specifically, the controller can be written in terms of the matrices of the system’s state-space representation. The result has applications in the c
Despite the creativity of the scientific community and the funding agencies, the underlying model of computation behind IoT, WSN, cloud, edge, fog, and mist is fundamentally the same; Computational nodes which are dynamically interconnected to form a system in where both processing capacity and connectivity may vary over time. On top of such a system, we consider applications that need packets to
We extend the generalized information criteria for high-dimensional penalizedmodels to sparse statistical jump models, a new class of statistically robust and computationally efficient alternatives to hidden Markov models. In a simulation study, we demonstrate that the new generalized information criteria selects the correct hyperparameters with high probability. Finally, providing an empirical ap
We apply the statistical sparse jump model, a recently developed, interpretable and robust regime-switching model, to infer key features that drive the return dynamics of the largest cryptocurrencies. The algorithm jointly performs feature selection, parameter estimation, and state classification. Our large set of candidate features are based on cryptocurrency, sentiment and financial market-based
Introduction Knee muscles are commonly labeled as flexors or extensors and aptly stabilize the knee against sagittal plane loads. However, how these muscles stabilize the knee against adduction-abduction and rotational loads remains unclear. Our study sought 1) to classify muscle roles as they relate to joint stability by quantifying the relationship between individual muscle activation patterns a
Land remediation is an important part of restoration measures after a radioactive fallout containing long-lived fission products such as 137Cs. In this multidisciplinary study, we focused on three main issues related to remediation of contaminated urban areas. First, we assessed how much decontamination contributes to reducing resident radiation exposure and how much this reduction depends on the
Event-based sampling provides a way of lowering the resource utilization in sensing and communication applications. By sending a sample only when some triggering condition is fulfilled, we can ensure that the transmitted samples actually carry innovation. However, in an event-based system, the state estimation problem becomes complicated, as the information of not receiving a measurement must be t
The real-time implementation of periodic controllers requires solving a co-design problem, in which the choice of the controller sampling period is a crucial element. Classic design techniques limit the period exploration to safe values, that guarantee the correct execution of the controller alongside the remaining real-time load, i.e., ensuring that the controller worst-case response time does no
This paper presents JitterTime, a small Matlab toolbox for calculating the transient performance of a control system in non-ideal timing scenarios.Such scenarios arise in networked and embedded systems, where several applications share a set of limited and varying resources.Technically, the toolbox evaluates the time-varying state covariance of a mixed continuous/discrete linear system driven by w
Controlled invariant set and viability regulation of dynamical control systems have played important roles in many control and coordination applications. In this paper we develop a \textit{temporal} viability regulation theory for general dynamical control systems, and in particular for control affine systems. The time-varying viable set is parameterized by time-varying constraint functions, with
The IEEE Std. P1687.1 working group is currently exploring alternatives to IEEE Std. 1149.1 test access port (TAP) as the interface between the boundary of integrated circuits (ICs) and IEEE Std. 1687 networks. In this paper, we investigate the use of universal asynchronous receiver-transmitter (UART) to access IEEE Std. 1687 networks. We have developed a protocol to describe the information trans
Devices sharing a network compete for bandwidth, being able to transmit only a limited amount of data. This is for example the case with a network of cameras, that should record and transmit video streams to a monitor node for video surveillance. Adaptive cameras can reduce the quality of their video, thereby increasing the frame compression, to limit network congestion. In this paper, we exploit
With growing traffic demands, transportation networks become more and more congested and prone to disruptions. In this paper, we study how different perturbations affect the free flow equilibria, i.e., equilibria where no congestion effects are present, in transportation networks. More specifically, if and when the equilibrium of the perturbed dynamics is still in free flow. A generalized cell tra
This technical report describes JitterTime, a Matlab toolbox for calculating the time-varying state covariance of a mixed continuous/discrete linear system driven by white noise. It also integrates a quadratic cost function for the system. The passing of time and the updating of the discrete-time systems are explicitly managed by the user in a simulation run. Since the timing is completely handled
