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This paper deals with the real-time implementation of feedback controllers. In particular, it provides an analysis of the stability property of closed-loop systems that include a controller that can sporadically miss deadlines. In this context, the weakly hard m-K computational model has been widely adopted and researchers used it to design and verify controllers that are robust to deadline misses
One of the basic requirements of today's sophisticated world is the availability of electrical energy, and neglect of this matter may have irreparable damages such as an extensive blackout. The problems which were introduced about the traditional power grid, and also, the growing advances in smart technologies make the traditional power grid go towards smart power grid. Although widespread utilisa
Fitting a matrix of a given rank to data in a least squares sense can be done very effectively using 2nd order methods such as Levenberg-Marquardt by explicitly optimizing over a bilinear parameterization of the matrix. In contrast, when applying more general singular value penalties, such as weighted nuclear norm priors, direct optimization over the elements of the matrix is typically used. Due t
In this paper, bilateral teleoperation of multiple slaves coupled to a single master under scheduling communication is investigated. The sampled-data transmission between the master and the multiple slaves is fulfilled over a delayed communication network, and at each sampling instant, only one slave is allowed to transmit its current information to the master side according to some scheduling pro
Handling of critical situations is an important part in the architecture of an autonomous vehicle. A controller for autonomous collision avoidance is developed based on a wary strategy that assumes the least tireroad friction for which the maneuver is still feasible. Should the friction be greater, the controller makes use of this and performs better. The controller uses an acceleration-vector ref
Segmenting a motion-planning problem into smaller subproblems could be beneficial in terms of computational complexity. This observation is used as a basis for a new sub-maneuver decomposition approach investigated in this paper in the context of optimal evasive maneuvers for autonomous ground vehicles. The recently published alternating augmented Lagrangianmethod is adopted and leveraged on, whic
Methane emissions from natural wetlands tend to increase with temperature and therefore may lead to a positive feedback under future climate change. However, their temperature response includes confounding factors and appears to differ on different time scales. Observed methane emissions depend strongly on temperature on a seasonal basis, but if the annual mean emissions are compared between sites
Plants release to the atmosphere reactive gases, so-called volatile organic compounds (VOCs). The release of VOCs from vegetation is temperature-dependent and controlled by vegetation composition because different plant species release a distinct blend of VOCs. We used modelling approaches on ecosystem VOC release data collected across the Arctic, which is experiencing both rapid warming and veget
In this paper the sum of an orthogonal matrix and an outer product is studied, and a relation between the norms of the vectors forming the outer product and the singular values of the resulting matrix is presented. The main result may be found in Theorem 1.
We propose a methodology for studying the performance of common splitting methods through semidefinite programming. We prove tightness of the methodology and demonstrate its value by presenting two applications of it. First, we use the methodology as a tool for computerassisted proofs to prove tight analytical contraction factors for Douglas-Rachford splitting that are likely too complicated for a
We present a framework for measurement dimension reduction in Gaussian filtering, defined in terms of a linear operator acting on the measurement vector. This operator is optimized to minimize the Cramér-Rao bound of the estimate's mean squared error (MSE), yielding a measurement subspace from which elements minimally worsen the filter MSE performance, as compared to filtering with the original me
Safety evaluations made in the city Helsingborg indicate a decreased risk of being exposed to crime, but an increased feeling of unsafe. Damage in the form of scribbling (graffiti) is one of several indicators contributing to feeling unsafe. In this paper we investigate whether the use of Internet-of-things technology, where a sensor monitors a walking and cycling tunnel, makes it possible to re
Event-based control is a promising concept for the design of resource-efficient feedback systems, where events such as sampling, actuation, and data transmissions are triggered reactively based on monitored control performance rather than a periodic timer. In this thesis, we investigate how sampling and communication events should be triggered to fully exploit the potential of event-based control
A neural-network-based adaptive control scheme is developed for bilateral teleoperation systems with single-master-multiple-slaves in the presence of dynamic uncertainties and communication constraint. Discrete-time data transmitting communication network with bandwidth limitation and time-varying communication delays is considered and the Round-Robin scheduling protocol is used to orchestrate the
Ship traffic is a major source of aerosol particles, particularly near shipping lanes and harbours. In order to estimate the contribution to exposure downwind of a shipping lane, it is important to be able to measure the ship emission contribution at various distances from the source. We report on measurements of atmospheric particles 7-20 km downwind of a shipping lane in the Baltic Se
It is proved that network realizability of controllers can be enforced without conservatism using convex constraints on the closed loop transfer function. Once a network realizable closed loop transfer matrix has been found, a corresponding controller can be implemented using a network structured version of Internal Model Control.
Atomic norms occur frequently in data science and engineering problems such as matrix completion, sparse linear regression, system identification and many more. These norms are often used to convexify non-convex optimization problems, which are convex apart from the solution lying in a non-convex set of so-called atoms. For the convex part being a linear constraint, the ability of several atomic n
We propose an efficient algorithm, that given a strictly proper, second-order system, finds a sparse input signal so that the system's output optimally approximates a given trajectory in least-squares sense. As an illustration, we apply the algorithm to an estimation problem from medicine.
A numerical method based on radial basis functions (RBF) has been developed to find the optimal event-based sampling policy in an LQG problem setting. The optimal sampling problem can be posed as a stationary partial differential equation with a free boundary, which is solved by reformulatingthe optimal RBF approximation as a linear complementarity problem (LCP). The LCP can be efficiently solved
We present a novel predictive control scheme for linear constrained systems that uses the alternating direction method of multipliers (ADMM) for online optimization. In contrast to existing works on ADMM-based model predictive control (MPC), we only consider a single ADMM-iteration in every time step. The resulting real-time ADMM scheme is tailored for embedded and fast MPC implementations. The ma
