Control Applications

Optimizing the lead time of operational flexibility trading from distributed industrial energy systems in future energy and flexibility markets

  • Daniel Bull
    • Categories (Mixed) Integer Linear Programming, Control Applications, Energy Tags , , , ,

    To meet the challenges of increasing volatile and distributed renewable energy generation in the electric grid, local flexibility and energy markets are currently investigated. These markets aim to encourage prosumers to trade their available flexible power locally, to be used if a grid congestion is being predicted. The markets are emerging, but the characterizing parameter … Read more

    Trajectory Optimization of Unmanned Aerial Vehicles in the Electromagnetic Environment

  • Alain Zemkoho
  • Jörg Fliege
    • Categories Control Applications, Nonlinear Optimization, Telecommunications

    We consider a type of routing problems common in defence and security, in which we control a fleet of unmanned aerial vehicles (UAVs) that have to reach one or more target locations without being detected by an adversary. Detection can be carried out by a variety of sensors (radio receivers, cameras, personnel, etc) placed by … Read more

    Switching Time Optimization for Binary Quantum Optimal Control

  • Xinyu Fei
  • Lucas Brady
  • Jeffrey Larson
  • Sven Leyffer
  • Siqian Shen
    • Categories (Mixed) Integer Nonlinear Programming, Basic Sciences Applications, Control Applications Tags , ,

    Quantum optimal control is a technique for controlling the evolution of a quantum system and has been applied to a wide range of problems in quantum physics. We study a binary quantum control optimization problem, where control decisions are binary-valued and the problem is solved in diverse quantum algorithms. In this paper, we utilize classical … Read more

    Distributionally Robust Linear Quadratic Control

  • Bahar Tașkesen
  • Dan Iancu
  • Çağıl Koçyiğit
  • Daniel Kuhn
    • Categories Control Applications, Dynamic Programming, Robust Optimization

    Linear-Quadratic-Gaussian (LQG) control is a fundamental control paradigm that is studied in various fields such as engineering, computer science, economics, and neuroscience. It involves controlling a system with linear dynamics and imperfect observations, subject to additive noise, with the goal of minimizing a quadratic cost function for the state and control variables. In this work, … Read more

    Safely Learning Dynamical Systems

  • Abraar Chaudhry
  • Amir Ali Ahmadi
  • Vikas Sindhwani
  • Stephen Tu
    • Categories Control Applications, Linear, Cone and Semidefinite Programming, Robust Optimization Tags , , , ,

    \(\) A fundamental challenge in learning an unknown dynamical system is to reduce model uncertainty by making measurements while maintaining safety. In this work, we formulate a mathematical definition of what it means to safely learn a dynamical system by sequentially deciding where to initialize the next trajectory. In our framework, the state of the … Read more

    A Voronoi-Based Mixed-Integer Gauss-Newton Algorithm for MINLP Arising in Optimal Control

  • Andrea Ghezzi
  • LeoS
  • Adrian Bürger
  • Clemens Zeile
  • Sebastian Sager
  • Moritz Diehl
    • Categories (Mixed) Integer Nonlinear Programming, Control Applications, Nonlinear Systems and Least-Squares Tags ,

    We present a new algorithm for addressing nonconvex Mixed-Integer Nonlinear Programs (MINLPs) where the cost function is of nonlinear least squares form. We exploit this structure by leveraging a Gauss-Newton quadratic approximation of the original MINLP, leading to the formulation of a Mixed-Integer Quadratic Program (MIQP), which can be solved efficiently. The integer solution of the … Read more

    Dual solutions in convex stochastic optimization

  • Teemu Pennanen
  • Ari-Pekka Perkkiö
    • Categories Control Applications, Finance and Economics, Stochastic Programming Tags , , ,

    This paper studies duality and optimality conditions for general convex stochastic optimization problems. The main result gives sufficient conditions for the absence of a duality gap and the existence of dual solutions in a locally convex space of random variables. It implies, in particular, the necessity of scenario-wise optimality conditions that are behind many fundamental … Read more

    Multi-fidelity robust controller design with gradient sampling

  • Steffen W. R. Werner
  • Michael L. Overton
  • Benjamin Peherstorfer
    • Categories Control Applications, Nonsmooth Optimization Tags , , , ,

    Robust controllers that stabilize dynamical systems even under disturbances and noise are often formulated as solutions of nonsmooth, nonconvex optimization problems. While methods such as gradient sampling can handle the nonconvexity and nonsmoothness, the costs of evaluating the objective function may be substantial, making robust control challenging for dynamical systems with high-dimensional state spaces. In … Read more

    A Gauss-Newton-based Decomposition Algorithm for Nonlinear Mixed-Integer Optimal Control Problems

  • Adrian Bürger
  • Clemens Zeile
  • Angelika Altmann-Dieses
  • Sebastian Sager
  • Moritz Diehl
    • Categories (Mixed) Integer Nonlinear Programming, Control Applications, Systems governed by Differential Equations Optimization Tags , ,

    For the fast approximate solution of Mixed-Integer Non-Linear Programs (MINLPs) arising in the context of Mixed-Integer Optimal Control Problems (MIOCPs) a decomposition algorithm exists that solves a sequence of three comparatively less hard subproblems to determine an approximate MINLP solution. In this work, we propose a problem formulation for the second algorithm stage that is … Read more

    Distributionally Robust Modeling of Optimal Control

  • Alexander Shapiro
    • Categories Control Applications, Dynamic Programming, Stochastic Programming Tags , , , , , , ,

    The aim of this paper is to formulate several questions related to distributionally robust Stochastic Optimal Control modeling. As an example, the distributionally robust counterpart of the classical inventory model is discussed in details. Finite and infinite horizon stationary settings are considered. Article Download View Distributionally Robust Modeling of Optimal Control