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We propose a distributed optimization algorithm for mixed L_1/L_2-norm optimization based on accelerated gradient methods using dual decomposition. The algorithm achieves convergence rate O(1/k^2), where k is the iteration number, which significantly improves the convergence rates of existing duality-based distributed optimization algorithms that achieve O(1/k). The performance of the developed al
In manipulation tasks, motion trajectories are characterized by a set of key phases (i.e., motion primitives). It is therefore important to learn the motion primitives embedded in such tasks from a complete demonstration. In this paper, we propose a core framework that autonomously segments motion trajectories to support the learning of motion primitives. For this purpose, a set of segmentation po
This paper suggests an extension of an existing, clinically evaluated, closed-loop drug delivery system for hypnotic depth control using propofol. The extension introduces closed-loop administration of the analgesic drug remifentanil, thus forming a multiple input–single output (MISO) control system. Remifentanil acts and is metabolized at a significantly faster time scale than propofol. Direct co
The management of resources among competing QoS-aware applications is often solved by a resource manager (RM) that assigns both the resources and the application service levels. However, this approach requires all applications to inform the RM of the available service levels. Then, the RM has to maximize the "overall quality" by comparing service levels of different applications which are not nece
Two main topics are considered in this thesis: Machining with industrial robot manipulators and optimal motion control of robots and vehicles. The motivation for research on the first subject is the need for flexible and accurate production processes employing industrial robots as their main component. The challenge to overcome here is to achieve high-accuracy machining solutions, in spite of the
Industrial robots are traditionally programmed using only the internal joint position sensors, in a sense leaving the robot blind and numb. Using external sensors, such as cameras and force sensors, allows the robot to detect the existence and position of objects in an unstructured environment, and to handle contact situations not possible using only position control. This thesis presents work on
Force sensing provides robots the capability to accomplish tasks where physical interaction with the environment is required, such as assembly. Small position uncertainties can then be corrected for by sensing the contact forces. This thesis considers the problem of force-controlled assembly, including how tasks can be specified in a simple and intuitive way and how robust task execution under unc
Two mixed-phase precipitation events were observed on 21 September and 20 October 2010 over the southern part of Finland during the Light Precipitation Validation Experiment (LPVEx). These events have been simulated using the Weather Research and Forecasting Model coupled with spectral bin microphysics (WRF-SBM). The detailed ice-melting scheme with prognosis of the liquid water fraction during me
Resource allocation in clouds is mostly done assuming hard requirements, applications either receive the requested resources or fail. Given the dynamic nature of workloads, guaranteeing on-demand allocations requires large spare capacity. Hence, one cannot have a system that is both reliable and efficient. To solve this issue, we introduce Service Level (SL) awareness in clouds, assuming applicati
Robust and reliable formulas for predicting bed load and suspended load were developed for application in the nearshore zone where waves and currents may transport sediment separately or in combination. Also, a routine was included to determine the sediment transport in the swash zone, both in the longshore and cross-shore directions. An important objective of the development was to arrive at gene
In this paper, we explore positivity preserving model reduction. The reduction is performed by truncating the states of the original system without balancing in the classical sense. This may result in conservatism, however, this way the physical meaning of the individual states is preserved. The reduced order models can be obtained using simple matrix operations or using distributed optimization m
The Auxiliary Particle Filter is a variant of the common particle filter which attempts to incorporate information from the next measurement to improve the proposal distribution in the update step. This paper studies how this can be done for Mixed Linear/Nonlinear Gaussian models, it builds on a previously suggested method and introduces two new variants which tries to improve the performance by u
A tracking problem for a mechanical system is considered. We start with a feedback controller that is designed without attention to disturbances, which are assumed to be adequately described by a dynamic LuGre friction model. We are interested in deriving a superimposed observer-based compensator to annihilate or reduce the influence of such a disturbance. We exploit a recently suggested approach
Submerged breakwaters (SBWs) are becoming a popular option for coastal protection, mainly due to their low aesthetic impact on the natural environment. However, SBWs have rarely been employed for coastal protection in the past and therefore, their efficacy remains largely unknown. The main objective of the present study was to investigate the structural and environmental conditions that govern the
This paper presents a novel control architecture for hybrid stiff and compliant control for minimally invasive surgery which satisfies the constraints of zero lateral velocity at the entry point for serial manipulators. For minimally invasive surgery it is required that there is no sideways motion at the point where the robots enter the abdomen. This is necessary to avoid any damage to the patient
In this paper, optimization problems arising in model predictive control (MPC) and in distributed MPC aresolved by applying a fast gradient method to the dual of the MPC optimization problem. Although the development of fast gradient methods has improved the convergence rate of gradient-based methods considerably, they are still sensitive to ill-conditioning of the problem data. Since similar opti
This paper proposes an individualized approach to closed-loop control of depth of hypnosis during propofol anesthesia. The novelty of the paper lies in the individualization of the controller at the end of the induction phase of anesthesia, based on a patient model identified from the dose-response relationship during induction of anesthesia. The proposed approach is shown to be superior to admini
Many cyber-physical systems comprise several control applications implemented on a shared platform, for which stability is a fundamental requirement. This is as opposed to the classical hard real-time systems where often the criterion is meeting the deadline. The stability of control applications depends on not only the delay experienced, but also the jitter. Therefore, the notion of deadline is c
Five recent techniques from hybrid and optimal control are evaluated on two power electronics benchmark problems. The benchmarks involve a number of practically interesting operating scenarios for fixed-frequency synchronous dc-dc converters. The specifications are defined such that good performance can only be obtained if the switched and nonlinear nature of the problem is accounted for during th
