Roy Smith


Last Name

Smith

First Name

Roy

ORCID

0000-0002-8139-4683

Organisational unit

01209 - Lehre Inf.technologie u. Elektrotechnik

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Publications 1 - 10 of 258
  • Model Predictive Control of a Swiss Office Building
    Item type: Conference Paper
    Sturzenegger, David; Gyalistras, Dimitrios; Gwerder, Markus; et al. (2013)
    Clima 2013
    The research project OptiControl (www.opticontrol.ethz.ch) deals with the development of novel, predictive control strategies for buildings. The strategies are tested on a fully occupied, well instrumented typical Swiss office building. This work presents our experience with the application of Model Predictive Control (MPC). The application of novel rule-based control (RBC) strategies on the same building is presented in a companion paper (Integrated Predictive Rule-Based Control of a Swiss Office Building). Here we describe, first, the implementation and key aspects of model predictive building control. Second, we report on our experience with running the MPC controller on the building for three months. Third, we compare the controller’s performance in terms of comfort compliance and energy use to the previously installed industry standard RBC strategy using whole-year simulations with the EnergyPlus software. The experimental data show that the MPC operated reliably and successfully satisfied comfort constraints during a period of three months in summer. The simulation study suggests a superior control performance with respect to the original control strategy.
  • Eigenvalue Perturbation Models for Flexible Structures
    Item type: Conference Paper
    Smith, Roy (1991)
    Proceedings of the 30th IEEE Conference on Decision and Control
    Uncertainty in flexible structures is often modeled as real parametric variations in modal frequency and damping. Robust control theory provides powerful design methodologies (H∞ and µ-synthesis) which are readily applied to systems modeled with complex valued perturbations. This paper looks at one method of obtaining such a model for systems with uncertain lightly damped modes.
  • The Design of H-infinity Controllers for an Experimental Non-collocated Flexible Structure Problem
    Item type: Journal Article
    Smith, Roy; Chu, Cheng-Chih; Fanson, James L. (1994)
    IEEE Transactions on Control Systems Technology
    This paper describes results in applying robust control techniques to achieve vibration suppression of an active precision truss structure. The active structure incorporates piezoelectric members which serve as both structural and actuation elements. The problem considered is multiple-input, multiple-output with non-collocated actuators and sensors. Several characterizations of uncertainty are studied and the resulting controllers are compared experimentally. One characterization uses a novel approach involving eigenvalue perturbation descriptions.
  • Distributed Dual Quaternion Extended Kalman Filtering for Spacecraft Pose Control
    Item type: Working Paper
    Hudoba de Badyn, Mathias; Binz, Jonas; Iannelli, Andrea; et al. (2023)
    In this paper, we analyze a distributed dual-quaternion multiplicative extended Kalman filter for the estimation of poses and velocities of individual satellites in a fleet of spacecraft. Our proposed algorithm uses both absolute and relative pose measurements between neighbouring satellites in a network, allowing each individual satellite to estimate its own pose and that of its neighbours. By utilizing the distributed Kalman consensus filter, we propose a novel sensor and state-estimate fusion procedure that allows each satellite to improve its own state estimate by sharing data with its neighbours over a communication link. We also examine a leader-follower approach, whereby only a subset of the satellites have access to an absolute pose measurement. In this case, followers rely solely on the information provided by their neighbours, as well as relative pose measurements to those neighbours. The algorithm is tested extensively via numerical simulations, and it is shown that the approach provides a substantial improvement in performance over the scenario in which the satellites do not cooperate. A case study of satellites swarming an asteroid is presented, and the performance in the leader-follower scenario is also analyzed.
  • Power System Upgrade Planning with On-load Tap-changing Transformers, Switchable Topology and Operating Policies
    Item type: Conference Paper
    Merkli, Sandro; Smith, Roy (2019)
    2019 18th European Control Conference (ECC)
    Renewable energy sources are leading to undesired local voltage rise in power distribution systems. One way to reduce such voltage excursions is to upgrade the power system with stronger links or on-load tap-changing transformers (OLTC). While such hardware is readily available, it is costly to deploy and hence optimization-based planning approaches are desired to explore the design space in a systematic way. The approach presented in this work extends earlier power system planning work to a more general formulation. This formulation supports operationally switched devices such as OLTCs as well as lines that can be opened or closed at different operation times, both of which are devices that are already in common use in practice.
  • Optimization algorithms for nuclear norm based subspace identification with uniformly spaced frequency domain data
    Item type: Conference Paper
    Graf Plessen, Mogens; Semeraro, Vito; Wood, Tony A.; et al. (2015)
    2015 American Control Conference (ACC)
    We compare two iterative frequency domain subspace identification methods using nuclear norm minimization to more commonly used non-iterative methods by means of an artificially created test problem involving very noisy uniformly spaced frequency data. The two corresponding optimization problems are motivated and their first-order algorithmic solutions based on the alternating direction method of multipliers and the dual accelerated gradient-projection method are stated and compared.
  • Graph-theoretic optimization for edge consensus
    Item type: Conference Paper
    Hudoba de Badyn, Mathias; Foight, Dillon R.; Calderone, Daniel; et al. (2021)
    IFAC-PapersOnLine ~ 24th International Symposium on Mathematical Theory of Networks and Systems (MTNS 2020)
    We consider network structures that optimize the H2 norm of weighted, time scaled consensus networks, under a minimal representation of such consensus networks described by the edge Laplacian. We show that a greedy algorithm can be used to find the minimum-H2 norm spanning tree, as well as how to choose edges to optimize the H2 norm when edges are added back to a spanning tree. In the case of edge consensus with a measurement model considering all edges in the graph, we show that adding edges between slow nodes in the graph provides the smallest increase in the H2 norm.
  • Air Charge Estimation for Turbocharged Diesel Engines
    Item type: Conference Paper
    Storset, Ove F.; Stefanopoulou, Anna; Smith, Roy (2000)
    Proceedings of the 2000 American Control Conference (ACC)
    The paper presents adaptive observers for in-cylinder air charge estimation for turbocharged diesel engines based on a mean value engine model. We assess the observability from various engine measurements. The performance of the observers is compared to existing schemes analytically and in simulations. Specifically, it is shown that the designed observers perform better than the conventional schemes during fast step changes in engine fueling level. Furthermore, the estimate is less sensitive to changes in engine parameters than the existing schemes.
  • Improved day ahead heating demand forecasting by online correction methods
    Item type: Journal Article
    Bünning, Felix; Heer, Philipp; Smith, Roy; et al. (2020)
    Energy and Buildings
    Novel control strategies to reduce the heating and cooling energy consumption of buildings and districts are constantly being developed. Control on higher system levels, for example demand side management, usually requires forecasts for the future energy demand of buildings or entire districts. Such forecasts can be done with Artificial Neural Networks. However, the prediction performance of Artificial Neural Networks suffers from high variance. This means that two parameter-wise identical networks fitted to the same training data set perform differently well in forecasting the testing set. Here, we use two correction methods, one based on the forecasting error autocorrelation, and one based on online learning, to obtain reliable forecasting models. The approach is tested in the frame of day-ahead sub-hourly heating demand forecasting in a case study of a complex building, which has properties of a district heating system. It is demonstrated that the methods significantly reduce variance in prediction performance and also increase average prediction accuracy. When compared to other grey-box and black-box forecasting models, the approach performs well.
  • Visual control of steering in curve driving
    Item type: Journal Article
    Macuga, Kristen L.; Beall, Andrew C.; Smith, Roy; et al. (2019)
    Journal of Vision
    This pair of studies investigated steering in the absence of continuous visual information. In a driving simulator, participants steered a curving path that was displayed either continuously or intermittently. Optic flow conditions were manipulated to alter the nature of the heading information with respect to the path being steered. Removing or biasing heading information had little effect on steering even during long and frequent path occlusions as long as turn rate was available. This demonstrates that participants can use intermittent views of the path to plan their steering actions and optic flow to accurately update vehicle turns with respect to that path.
Publications 1 - 10 of 258