Journal: IEEE Transactions on Control Systems Technology

Abbreviation

IEEE trans. control syst. technol.

Publisher

IEEE

Journal Volumes

ISSN

1063-6536
1558-0865

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Publications 1 - 10 of 81
  • Iterative Learning Control for the Radio Frequency Subsystems of a Free-Electron Laser
    Item type: Journal Article
    Rezaeizadeh, Amin; Smith, Roy (2018)
    IEEE Transactions on Control Systems Technology
    In linear particle accelerators used for free electron lasers, it is often required that the electron bunches experience the same electric field as they pass through the accelerating structures. For radio frequency (RF) pulsed mode machines, like the SwissFEL, this means that the amplitude and phase of the radio frequency pulses feeding the structures through the waveguides should be kept constant over the pulse length. This raises an interesting problem that can be addressed by an Iterative Learning Control (ILC) technique. This method manipulates the input waveforms iteratively, in order to generate flat amplitude and phase pulses at the output of the system. In this paper, we introduce two ILC algorithms, one with a model and one without, which have been tested on three different high-power RF subsystems, namely: the klystron, pulse compressor and RF Gun.
  • Model Predictive Climate Control of a Swiss Office Building: Implementation, Results and Cost-Benefit Analysis
    Item type: Journal Article
    Sturzenegger, David; Gyalistras, Dimitrios; Morari, Manfred; et al. (2016)
    IEEE Transactions on Control Systems Technology
    This paper reports the final results of the predictive building control project OptiControl-II that encompassed seven months of model predictive control (MPC) of a fully occupied Swiss office building. First, this paper provides a comprehensive literature review of experimental building MPC studies. Second, we describe the chosen control setup and modeling, the main experimental results, as well as simulation-based comparisons of MPC to industry-standard control using the EnergyPlus simulation software. Third, the costs and benefits of building MPC for cases similar to the investigated building are analyzed. In the experiments, MPC controlled the building reliably and achieved a good comfort level. The simulations suggested a significantly improved control performance in terms of energy and comfort compared with the previously installed industry-standard control strategy. However, for similar buildings and with the tools currently available, the required initial investment is likely too high to justify the deployment in everyday building projects on the basis of operating cost savings alone. Nevertheless, development investments in an MPC building automation framework and a tool for modeling building thermal dynamics together with the increasing importance of demand response and rising energy prices may push the technology into the net benefit range.
  • Approximate Nonlinear Model Predictive Control With Safety-Augmented Neural Networks
    Item type: Journal Article
    Hose, Henrik; Köhler, Johannes; Zeilinger, Melanie N.; et al. (2025)
    IEEE Transactions on Control Systems Technology
    Model predictive control (MPC) achieves stability and constraint satisfaction for general nonlinear systems but requires computationally expensive online optimization. This brief studies approximations of such MPC controllers via neural networks (NNs) to achieve fast online evaluation. We propose safety augmentation that yields deterministic guarantees for convergence and constraint satisfaction despite approximation inaccuracies. We approximate the entire input sequence of the MPC with NNs, which allows us to verify online if it is a feasible solution to the MPC problem. We replace the NN solution by a safe candidate based on standard MPC techniques whenever it is infeasible or has worse cost. Our method requires a single evaluation of the NN and forward integration of the input sequence online, which is fast to compute on resource-constrained systems, typically within 0.2 ms. The proposed control framework is illustrated using three numerical nonlinear MPC benchmarks of different complexities, demonstrating computational speedups that are orders of magnitude higher than online optimization. In the examples, we achieve deterministic safety through the safety-augmented NNs, where a naive NN implementation fails.
  • An MPC/Hybrid System Approach to Traction Control
    Item type: Journal Article
    Borrelli, Francesco; Bemporad, Alberto; Fodor, Michael; et al. (2006)
    IEEE Transactions on Control Systems Technology
  • Backstepping Control of Variable Stiffness Robots
    Item type: Journal Article
    Petit, Florian; Daasch, Andreas; Albu-Schaffer, Alin (2015)
    IEEE Transactions on Control Systems Technology
  • A Decentralized Explicit Predictive Control Paradigm for Parallelized DC-DC Circuits
    Item type: Journal Article
    Beccuti, Andrea G.; Kvasnica, M.; Papafotiou, G.; et al. (2013)
    IEEE Transactions on Control Systems Technology
  • Nonlinear robust approaches to study stability and post-critical behaviour of an aeroelastic plant
    Item type: Journal Article
    Iannelli, Andrea; Marcos, Andrés; Lowenberg, Mark (2019)
    IEEE Transactions on Control Systems Technology
    Two approaches to tackle the nonlinear robust stability problem of an aerospace system are compared. The first employs a combination of the describing function method and μ analysis, while the second makes use of integral quadratic constraints (IQCs). The model analyzed consists of an open-loop wing's airfoil subject to free play and linear time-invariant parametric uncertainties. The key steps entailed by the application of the two methodologies and their main features are critically discussed. Emphasis is put on the available insight on the nonlinear postcritical behavior known as limit cycle oscillation. It is proposed a strategy to apply IQCs, typically used to find absolute stability certificates, in this scenario, based on a restricted sector bound condition for the nonlinearity. Another contribution of this paper is to understand how the conservatism usually associated with the IQCs multipliers selection can be overcome by using information coming from the first approach. Nonlinear time domain simulations showcase the prowess of these approaches in estimating qualitative trends and quantitative response's features.
  • Implementation of a nonlinear attitude estimator for aerial robotic vehicles
    Item type: Journal Article
    Hua, M.-D.; Ducard, G.; Hamel, T.; et al. (2014)
    IEEE Transactions on Control Systems Technology
  • On Sensor Fusion for Airborne Wind Energy Systems
    Item type: Journal Article
    Fagiano, Lorenzo; Huynh, Khanh; Bamieh, Bassam; et al. (2014)
    IEEE Transactions on Control Systems Technology
  • HYSDEL
    Item type: Journal Article
    Torrisi, Fabio Danilo; Bemporad, Alberto (2004)
    IEEE Transactions on Control Systems Technology
Publications 1 - 10 of 81