Bo Bernhardsson

Bio: Bo Bernhardsson is an academic researcher from Lund University. The author has contributed to research in topics: Signal & Linear system. The author has an hindex of 31, co-authored 156 publications receiving 6160 citations. Previous affiliations of Bo Bernhardsson include Hong Kong University of Science and Technology & Ericsson.

Comparison of Riemann and Lebesgue sampling for first order stochastic systems

Abstract: The normal approach to digital control is to sample periodically in time. Using an analog of integration theory we can call this Riemann sampling. Lebesgue sampling or event based sampling is an alternative to Riemann sampling. It means that signals are sampled only when measurements pass certain limits. In this paper it is shown that Lebesgue sampling gives better performance for some simple systems.

Stochastic analysis and control of real-time systems with random time delays

Abstract: The paper discusses modeling and analysis of realtime systems subject to random time delays in the communication network. A new method for analysis of different control schemes is presented. The method is used to evaluate different schemes suggested from the literature. A new scheme, using so-called timestamps, for handling the random time delays is then developed and successfully compared with previous schemes. The new scheme is based on stochastic control theory and a separation property is shown to hold for the optimal controller.

Comparison of Periodic and Event Based Sampling for First-Order Stochastic Systems

Abstract: Event based sampling is an alternative to traditional equidistant sampling. This means that signals are sampled only when measurements pass certain limits. Systems with event based sampling are much harder to analyze than systems with periodic sampling because the time varying nature of the closed loop system can not be avoided. In this paper we investigate some simple first order systems with event based sampling and compare achieved closed loop variance and sampling rate with results from periodic sampling. The analysis shows that event based sampling gives better performance than periodic sampling.

Stochastic Analysis and Control of Real-Time Systems with Random Time Delays

Abstract: The paper discusses modeling and analysis of real-time systems subject to random time delays in the communication network. A new method for analysis of existing schemes is presented. The method is used to evaluate different suggested schemes from the literature. A new scheme for handling the random time delays is then developed and successfully compared with previous schemes. The new scheme is based on stochastic control theory and a separation property is shown to hold for the optimal controller.

Feedback–Feedforward Scheduling of Control Tasks

Abstract: A scheduling architecture for real-time control tasks is proposed. The scheduler uses feedback from execution-time measurements and feedforward from workload changes to adjust the sampling periods of the control tasks so that the combined performance of the controllers is optimized. The performance of each controller is described by a cost function. Based on the solution to the optimal resource allocation problem, explicit solutions are derived for linear and quadratic approximations of the cost functions. It is shown that a linear rescaling of the nominal sampling frequencies is optimal for both of these approximations. An extensive inverted pendulum example is presented, where the performance obtained with open-loop, feedback, combined feedback and feedforward scheduling, and earliest-deadline first scheduling are compared. The performance under earliest-deadline first scheduling is explained by studying the behavior of periodic tasks under overload conditions. It is shown that the average values of the sampling periods equal the nominal periods, rescaled by the processor utilization.

Pattern Recognition and Machine Learning

Abstract: Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

A Survey of Recent Results in Networked Control Systems

Abstract: Networked control systems (NCSs) are spatially distributed systems for which the communication between sensors, actuators, and controllers is supported by a shared communication network. We review several recent results on estimation, analysis, and controller synthesis for NCSs. The results surveyed address channel limitations in terms of packet-rates, sampling, network delay, and packet dropouts. The results are presented in a tutorial fashion, comparing alternative methodologies

Event-Triggered Real-Time Scheduling of Stabilizing Control Tasks

Abstract: In this note, we revisit the problem of scheduling stabilizing control tasks on embedded processors. We start from the paradigm that a real-time scheduler could be regarded as a feedback controller that decides which task is executed at any given instant. This controller has for objective guaranteeing that (control unrelated) software tasks meet their deadlines and that stabilizing control tasks asymptotically stabilize the plant. We investigate a simple event-triggered scheduler based on this feedback paradigm and show how it leads to guaranteed performance thus relaxing the more traditional periodic execution requirements.

Basic problems in stability and design of switched systems

Abstract: By a switched system, we mean a hybrid dynamical system consisting of a family of continuous-time subsystems and a rule that orchestrates the switching between them. The article surveys developments in three basic problems regarding stability and design of switched systems. These problems are: stability for arbitrary switching sequences, stability for certain useful classes of switching sequences, and construction of stabilizing switching sequences. We also provide motivation for studying these problems by discussing how they arise in connection with various questions of interest in control theory and applications.