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A multi-variable PI (proportional integrating) controller is proved to be optimal for an important class of control problems where performance is specified in terms of frequency weighted H-infinity norms. The problem class includes networked systems with a subsystem in each node and control action along each edge. For such systems, the optimal PI controller is decentralized in the sense that contr
This paper develops a novel framework for power system stability analysis, that allows for the decentralised design of inverter based controllers. The method requires that each individual inverter satisfies a standard H∞ design requirement. Critically each requirement depends only on the dynamics of the components and inverters at each individual bus, and the aggregate susceptance of the transmiss
Modeling of robot motion as dynamical movement primitives (DMPs) has becomean important framework within robot learning and control. The ability of DMPs to adapt online with respect to the surroundings, e.g., to moving targets, has been used and developed by several researchers. In this work, a method for handling perturbations during execution of DMPs on robots was developed. Two-degree-of-freedo
We show how to minimize the energy required to build up the electromagnetic field in radio-frequency cavities, which will allow power savings for pulsed particle accelerators. By formulating an optimal control problem for a first-order system we obtain a solution on state-feedback form. We numerically compare the optimal solution to previous approaches.
This paper presents an algorithm for Model Predictive Control of SISO systems. Based on a quadratic objective in addition to (hard) input constraints it features soft upper as well as lower constraints on the output and an input rate-of-change penalty term. It keeps the deterministic and stochastic model parts separate. The controller is designed based on the deterministic model, while the Kalman
The fast-increasing demand and relatively slow growth of infrastructure capacity are providing a strong motivation for research in real-time urban traffic controls that make the best use of novel sensing in order to increase efficiency and resilience of the transportation system. In our contribution, we focus on a class of dynamic feedback traffic signal control policies that are based on a genera
Relay autotuning has proven very successful for single-input single-output systems. This paper proposes an identification method for relay autotuning of systems with two inputs and two outputs (TITO systems). The combination of asymmetric relay feedback and output error identification admits short tuning time, without the need for limit cycle convergence. The method is successfully demonstrated on
Control and scheduling co-design becomes an issue when several controller tasks share the same execution platform and disrupt the ideal sampling and actuation patterns. In co-design the objective is to optimize the combined performance of all the controllers on the platform, subject to schedulability constraints. In the paper four LQG-based co-design methods are reviewed and evaluated: delay-aware
The paper presents conditions for the stability of a dynamical network described by a directed graph, whose nodes represent dynamical systems characterised by the same transfer function F(s) and whose edges account for the interactions between pairs of nodes. In turn, these interactions depend via a transference G(s) on the outputs of the subsystems associated with the connected nodes. The stabili
In wavefield signal apparition, acquisition with periodic variations in source activation parameters shifts all or part of a signal cone out to, e.g., the Nyquist wavenumber, enabling perfect separation of simultaneous-source (sim-source) data in a diamond-shaped region below a certain temporal frequency. Cyclic convolution in the spatial frequency domain can be exploited to separate data with kno
Having multiple control tasks concurrently running on a single computing platform increases the processor utilization but degrades the control performance due to delay and jitter. In scheduling and control codesign, the objective is to optimize the combined performance of all the controllers, subject to a schedulability constraint. The codesign procedure consists of selecting task parameters, e.g.
We give closed-form expressions for H-infinity optimal state feedback laws applicable to linear time-invariant discrete time systems with symmetric and Schur state matrix. This class includes networked systems with local dynamics in each node and control action along each edge. Furthermore, the structure of the controllers mimics that of the system, which makes them suitable for distributed contro
The first study with a PID controller based automatic drug delivery system for propofol anesthesia in children is presented. It is shown that a robustly tuned PID controller is capable of delivering safe and adequate anesthesia. The design process of the control system is reviewed. Results are discussed and compared to those of two previous studies in adults.
An augmented version of the traditional relay feedback experiment is proposed. It aims at producing an input with energy concentrated to a frequency band, corresponding to a certain phase sector of the Nyquist curve of the process to be identified. A non-convex problem is formulated. Sub-optimal, but efficient, algorithms are developed.
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
