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Today, the majority of control applications in embedded systems, e.g., in the automotive domain, are implemented as software tasks on shared platforms. Ignoring implementation impacts during the design of embedded control systems results in complex timing behaviors that may lead to poor performance and, in the worst case, instability of control applications. This article presents a methodology for
The European Spallation Source will, once fully operational in 2025, be the world's brightest neutron source. The neutrons will be generated by bombarding a tungsten target with protons accelerated to 96\% the speed of light by electromagnetic fields confined in 155 radio-frequency cavities along the world's most powerful linear accelerator.This thesis has been motivated by the strict control spec
The goal of this work is to explore ways of generating state trajectories for dynamical systems subject to computational constraints, obstacles and priority assignment. The algorithms are developed for a miniature unmanned aerial vehicle (UAV) in a modular fashion and include (1) a genetic algorithm (GA) for solving the traveling salesman problem (TSP) with respect to priorities and obstacle avoid
An implementation of the spectral estimation method presented in Bagge Carlson et al. "Linear Parameter-Varying Spectral Decomposition." 2017 American Control Conference.
Provides implementations of Ijspeert et al. 2013 and of Martin Karlsson, Fredrik Bagge Carlson, et al. 2017
A Julia toolbox for approximation of functions using basis function expansions (BFEs).BFEs are useful when one wants to estimate an arbitrary/unknown/complicated functional relationship between (in the simple case) two variables, y and v. In simple linear regression, we might consider a functional relationship y = ϕ(v) = αv + β, with parameters α and β. However, if the function ϕ has an arbitrary
Solves the same problem as iLQG, with an added constraint on the KL-divergence between the new trajectory distribution and the distribution induced by a previous controller. This feature can be used in an outer loop with repeated experiments between the iterations if the model used for optimization is uncertain.
This toolbox works similar to that of other major computer-aided control systems design (CACSD) toolboxes. Systems can be created in either a transfer function or a state space representation. These systems can then be combined into larger architectures, simulated in both time and frequency domain, and analyzed for stability/performance properties.
Future district heating systems (so called 4th Generation District Heating (4GDH) systems) have to address challenges such as integration of (de)centralized renewable energy sources and storage, low system temperatures and high fluctuation of the supply temperature. This paper presents a novel framework for representing and simplifying on-grid energy systems as well as for dynamic thermo-hydraulic
In conventional seismic surveys, there is a waiting time between sequentially fired shots. This time is determined such that the deepest reflection of interest is recorded before the following source is fired. In a survey with simultaneous or blended sources, the waiting time between the firing of shots is not dependent on the deepest reflection of interest, it is usually much shorter and/or can h
An algorithm for high-performance path tracking for robot manipulators in the presence of model uncertainties and actuator constraints is presented. The path to be tracked is assumed given, and the nominal trajectories are computed using, for example, well-known algorithms for time-optimal path tracking. For online path tracking, the nominal, feedforward trajectories are combined with feedback in
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
In digital control systems, the state is sampled at given sampling instants and the input is kept constant between two consecutive instants. With the optimal sampling problem, we mean the selection of sampling instants and control inputs, such that a given function of the state and input is minimized. In this paper, we formulate the optimal sampling problem and we derive a necessary condition of t
Stochastic optimal power flow can provide the system operator with adequate strategies for controlling the power flow to maintain secure operation under stochastic parameter variations. One limitation of stochastic optimal power flow has been that only limits on lineflows have been used as stability constraints. In many systems voltage stability and small-signal stability also play an important role i
Lyapunov methods and density functions provide dual characterizations of the solutions of a nonlinear dynamic system. This work exploits the idea of combining both techniques, to yield stability results that are valid for almost all the solutions of the system. Based on the combination of Lyapunov and density functions, analysis methods are proposed for the derivation of almost input-to-state stab
Stochastic optimal power flow can provide the system operator with adequate strategies for controlling the power flow to maintain secure operation under stochastic parameter variations. One limitation of stochastic optimal power flow has been that only line flows have been used as security constraints. In many systems voltage stability and small-signal stability also play an important role in constrai
