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We investigate the out-of-sequence measurements particle filtering problem for a set of conditionally linear Gaussian state-space models, known as mixed linear/nonlinear state-space models. Two different algorithms are proposed, which both exploit the conditionally linear substructure. The first approach is based on storing only a subset of the particles and their weights, which implies low memory
A numerical model of undertow due to random waves is developed. The model includes three sub-models: (i) a model for multi-directional and multi-frequency random wave transformation, (ii) a surface roller evolution model, and (iii) a model for calculating the vertical distribution and the mean value of the undertow velocity. The calculation of wave trough level is performed based on a theory for t
The notion of omnipotence has proved to be quite recalcitrant to analysis. Still, during the last three decades or so, there has resurfaced a clever argument to the effect that, whatever omnipotence is, it cannot be exemplified in God: an allegedly impeccable and all-perfect being. Scrutinizing this argument, however, I find it less than convincing. Moreover, and more importantly, I venture a posi
Estimation-based iterative learning control (ILC) is applied to a parallel kinematic manipulator known as the Gantry-Tau parallel robot. The system represents a control problem where measurements of the controlled variables are not available. The main idea is to use estimates of the controlled variables in the ILC algorithm, and in the paper this approach is evaluated experimentally on the Gantry-
At subzero temperatures, cloud particles can contain both ice and liquid water fractions. Wet growth of precipitation particles occurs when supercooled cloud liquid is accreted faster than it can freeze on impact. With a flexible framework, the theory of wet growth of hail is extended to the case of the inhomogeneities of surface temperature and of liquid coverage over the surface of the particle.
In embedded real-time systems, task priorities are often assigned to meet deadlines. However, in control tasks, a late completion of a task has no catastrophic consequence. Rather, it has a quantifiable impact in the control performance achieved by the task. In this paper, we address the problem of determining the optimal assignment of priorities and periods of sampled-data control tasks that run
An important new development within the European ENSEMBLES project has been to explore performance-based weighting of regional climate models (RCMs). Until now, although no weighting has been applied in multi-RCM analyses, one could claim that an assumption of ‘equal weight’ was implicitly adopted. At the same time, different RCMs generate different results, e.g. for various types of extremes, and
Bundle adjustment for multi-view reconstruction is traditionally done using the Levenberg-Marquardt algorithm with a direct linear solver, which is computationally very expensive. An alternative to this approach is to apply the conjugate gradients algorithm in the inner loop. Tins is appealing since the main computational step of the CG algorithm involves only a simple matrix-vector multiplication
This work investigates the predictability of seasonal to inter-annual streamflow over several river basins in Norway through the use of multi-model ensembles. As general circulation models (GCMs) do not explicitly simulate streamflow, a statistical link is made between GCM-forecast fields generated in December and average streamflow in the melting season May-June. By using the Climate Predictabili
A mathematical model of spit growth and barrier elongation adjacent to an inlet (of arbitrary width), supplied by sediment coming from longshore sediment transport, was developed based on the spit growth model proposed by Kraus (1999). The fundamental governing equation is the conservation equation for sand, where the width of the spit is assumed constant during growth. The portion of the longshor
The traditional way of controlling an industrial robot is to program it to follow desired trajectories. This approach is sufficient as long as the accuracy of the robot and the calibration of the workcell is good enough. In robotic assembly these conditions are usually not fulfilled, because of uncertainties, e.g., variability in involved parts and objects not gripped accurately. Using force contr
Classical control theory does not scale well for large systems such as power networks, traffic networks and chemical reaction networks. However, many such applications in science and engineering can be efficiently modeled using the concept of positive systems and the nonlinear counterpart monotone systems. It is therefore of great interest to see how such models can be used for control. This paper
Particles containing soot, or black carbon, are generally considered to contribute to global warming. However, large uncertainties remain in the net climate forcing resulting from anthropogenic emissions of black carbon (BC), to a large extent due to the fact that BC is co-emitted with gases and primary particles, both organic and inorganic, and subject to atmospheric ageing processes. In this stu
The performance of the linear consensus algorithm is studied by using a linear quadratic (LQ) cost. The objective is to understand how the communication topology influences this algorithm. This is achieved by exploiting the analogy between Markov chains and electrical resistive networks. Indeed, this allows us to uncover the relation between the LQ performance cost and the average effective resist
Stochastic differential equations have been shown useful in describing random continuous time processes. Biomedical experiments often imply repeated measurements on a series of experimental units and differences between units can be represented by incorporating random effects into the model. When both system noise and random effects are considered, stochastic differential mixed-effects models ensu
Regional climate models are used by a large number of groups, for more or less all regions of the world. Regional climate models are complementary to global climate models. A typical use of regional climate models is to add further detail to global climate analyses or simulations, or to study climate processes in more detail than global models allow. The relationship between global and regional cl
The turbidity variation in time and space is investigated in the downstream stretch of the river Gota Alv in Sweden. The river is heavily regulated and carries the discharge from the largest fresh water lake in Sweden, Lake Vanern, to the outflow point in Goteborg Harbour on the Swedish west coast. The river is an important waterway and serves as a fresh-water supply for 700 000 users. Turbidity i
This paper considers the problem of performing mid-ranging control of two closed-loop controlled systems that have internal saturations. The problem originates from previous work in machining with industrial robots, where an external compensation mechanism is used to compensate for position errors. Because of the limited workspace and the considerably higher bandwidth of the compensator, a mid-ran
The flexibility demands in manufacturing are severe, e.g., for rapid-change-over to new product variants, while robots are flexible machines that potentially can be adapted to a large variety of production tasks. Task definitions such as explicit robot programs are hardly reusable from an application point-of-view. To improve the situation, a knowledge-based approach exploiting distributed declara
