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While good physiological models of the glucose metabolism in type 1 diabetic patients are well known, their parameterisation is difficult. The high intra-patient variability observed is a further major obstacle. This holds for data-based models too, so that no good patient-specific models are available. Against this background, this paper proposes the use of interval models to cover the different
We introduce a new multi-region model for simultaneous segmentation of the left and right ventricles, myocardium and the left ventricular papillary muscles in MRI. The model enforces geometric constraints such as inclusion and exclusion between the regions, which makes it possible to correctly segment different regions even though the intensity distributions are identical. We efficiently optimize
This paper addresses the out-of-sequence measurement (OOSM) problem for mixed linear/nonlinear state-space models, which is a class of nonlinear models with a tractable, conditionally linear substructure. We develop two novel algorithms that utilize the linear substructure. The first algorithm effectively employs the Rao-Blackwellized particle filtering framework for updating with the OOSMs, and i
We consider the problem of reliable communication over multiple-access channels (MAC) where the channel is driven by an independent and identically distributed state process and the encoders and the decoder are provided with various degrees of asymmetric (noisy or partial) channel state information (CSI). Namely, we provide a single letter characterization for the capacity region when the encoders
Stability of Wardrop equilibria is analyzed for dynamical transportation networks in which the drivers' route choices are influenced by information at multiple temporal and spatial scales. The considered model involves a continuum of nonatomic indistinguishable drivers commuting between a common origin-destination pair in an acyclic transportation network. The drivers' route choices are affected b
Lately, much work in the area of voltage stability assessment has been focused on finding post-contingency corrective controls. In this article a contribution to this area will be presented where we investigate the surface of maximal loadability while allowing for post-contingency corrective controls. This objective is different from the usual, where the aim is to include the post-contingency cont
In this paper we consider the classical problem of finding a low rank approximation of a given matrix. In a least squares sense a closed form solution is available via factorization. However, with additional constraints, or in the presence of missing data, the problem becomes much more difficult. In this paper we show how to efficiently compute the convex envelopes of a class of rank minimization
This paper discusses the significance of physical models in engineering education. Obvious assets, drawbacks and the educational role of such models are discussed, and the idea of 'open physical models' is introduced. A couple of sophisticated open physical models (an unmanned rotorcraft and an inverted pendulum robot), used in control engineering courses, are presented. Basic ideas and concepts,
We propose a structure and motion estimation scheme based on a dynamic systems approach, where states and parameters in a perspective system are estimated. An online method for structure and motion estimation in densely sampled image sequences is presented. The proposed method is based on an extended Kalman filter and a novel parametrization. We derive a dynamic system describing the motion of the
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
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
tThe PID controller is by far the most common controller, and to ensure good behavior under all circumstances, a PID implementation must consider many practical aspects such as integrator windup,derivative kick, and bumpless parameter and mode changes. In this paper, an entirely new issue for the derivative part is introduced and has been named derivative backoff. It occurs when the process value
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
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
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
We present a stopping condition to the duality based distributed optimization algorithm presented in [1] when used in a distributed model predictive control (DMPC) context. To enable distributed implementation, the optimization problem has neither terminal constraints nor terminal cost that has become standard in model predictive control (MPC). The developed stopping condition guarantees a prespec
System-theoretical methods are already used for the control of computing systems, but much more can be done exploiting said methods for their design. This requires to express in control-theoretical terms desires and specifications that originate in the computer science do- main, which may not be immediate. It also requires to accept that part of the addressed system be modified, which may pose som
