Journal: IFAC-PapersOnLine

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Publisher

Elsevier

Journal Volumes

ISSN

2405-8963

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2015 - 2019842020 - 202594
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Publications 1 - 10 of 178
  • Withdrawn: Rethinking the Micro-Foundation of Opinion Dynamics: Rich Consequences of an Inconspicuous Change
    Item type: Conference Paper
    Mei, Wenjun; Bullo, Francesco; Chen, Ge; et al. (2020)
    IFAC-PapersOnLine ~ 3rd IFAC Workshop on Cyber-Physical & Human Systems, CPHS 2020. Proceedings
  • Payoff-based approach to learning Nash Equilibria in Convex Games
    Item type: Conference Paper
    Tatarenko, Tatiana; Kamgarpour, Maryam (2017)
    IFAC-PapersOnLine ~ 20th IFAC World Congress. Proceedings
    We consider multi-agent decision making, where each agent optimizes its cost function subject to constraints. Agents’ actions belong to a compact convex Euclidean space and the agents’ cost functions are coupled. We propose a distributed payoff-based algorithm to learn Nash equilibria in the game between agents. Each agent uses only information about its current cost value to compute its next action. We prove convergence of the proposed algorithm to a Nash equilibrium in the game leveraging established results on stochastic processes. The performance of the algorithm is analyzed with a numerical case study.
  • An Approximate Dynamic Programming approach for Dual Stochastic Model Predictive Control
    Item type: Conference Paper
    Arcari, Elena; Hewing, Lukas; Zeilinger, Melanie N. (2020)
    IFAC-PapersOnLine ~ 21st IFAC World Congress
    Dual control explicitly addresses the problem of trading off active exploration and exploitation in the optimal control of partially unknown systems. While the problem can be cast in the framework of stochastic dynamic programming, exact solutions are only tractable for discrete state and action spaces of very small dimension due to a series of nested minimization and expectation operations. We propose an approximate dual control method for systems with continuous state and input domain based on a rollout dynamic programming approach, splitting the control horizon into a dual and an exploitation part. The dual part is approximated using a scenario tree generated by sampling the process noise and the unknown system parameters, for which the underlying distribution is updated via Bayesian estimation along the horizon. In the exploitation part, we fix the resulting parameter estimate of each scenario branch and compute an open-loop control sequence for the remainder of the horizon. The key benefit of the proposed sampling-based approximation is that it enables the formulation as one optimization problem that computes a collection of control sequences over the scenario tree, leading to a dual model predictive control formulation.
  • Linear vs nonlinear mpc for trajectory tracking applied to rotary wing micro aerial vehicles
    Item type: Conference Paper
    Kamel, Mina; Burri, Michael; Siegwart, Roland (2017)
    IFAC-PapersOnLine ~ 20th IFAC World Congress. Proceedings
    Precise trajectory tracking is a crucial property for Micro Air Vehicles (MAVs) to operate in cluttered environment or under disturbances. In this paper we present a detailed comparison between two state-of-the-art model-based control techniques for MAV trajectory tracking. A classical Linear Model Predictive Controller (LMPC) is presented and compared against a more advanced Nonlinear Model Predictive Controller (NMPC) that considers the full system model. In a careful analysis we show the advantages and disadvantages of the two implementations in terms of speed and tracking performance. This is achieved by evaluating hovering performance, step response, and aggressive trajectory tracking under nominal conditions and under external wind disturbances.
  • Embedded optimization methods for industrial automatic control
    Item type: Conference Paper
    Ferreau, Hand Joachim; Almer, Stefan; Verschueren, Robin; et al. (2017)
    IFAC-PapersOnLine ~ 20th IFAC World Congress. Proceedings
    Starting in the late 1970s, optimization-based control has built up an impressive track record of successful industrial applications, in particular in the petrochemical and process industries. More recently, optimization methods for automatic control are more and more deployed on so-called embedded hardware to cater for application-specific needs such as guaranteed communication latency, low energy consumption or cost effectiveness. This development greatly broadens the scope of applications to which optimization methods can be applied to sectors such as robotics, automotive, aerospace or power electronics. However, it also poses additional challenges regarding both the algorithmic concepts and their actual implementations for a given computing hardware. This survey paper discusses key challenges for using embedded optimization methods and summarizes their main use cases in current industrial practice. Motivated by this discussion, a number of dedicated embedded optimization algorithms and their actual implementations are reviewed. The presentation is organized according to the mathematical structure of the embedded optimization problem, ranging from convex quadratic programming over more general convex and nonconvex problems to formulations comprising discrete optimization variables.
  • Energy-balancing dual-port grid-forming control for VSC-HVDC systems
    Item type: Conference Paper
    Subotic, Irina; Gross, Dominic (2023)
    IFAC-PapersOnLine
    This work examines energy-balancing dual port grid-forming (GFM) control for high-voltage direct current (HVDC) transmission. In contrast to the state-of-the-art, HVDC converters controlled in this way do not require assigning GFM and grid-following roles to different converters. Moreover, this control enables primary frequency control and inertia support through HVDC links. A detailed stability and steady-state analysis results in conditions on the control gains such that i) the overall hybrid dc/ac system is stable, ii) asynchronous ac areas are quasi-synchronous, and iii) circulating power in cyclic topologies is avoided. Finally, a high-fidelity case study is used to illustrate and verify the analytical results
  • On the steady-state behavior of a nonlinear power network model
    Item type: Conference Paper
    Arghir, Catalin; Groß, Dominic; Dörfler, Florian (2016)
    IFAC-PapersOnLine ~ 6th IFAC Workshop on Distributed Estimation and Control in Networked Systems, NECSYS 2016. Proceedings
    In this paper, we consider a dynamic model of a three-phase power system including nonlinear generator dynamics and transmission line dynamics. We derive conditions under which the power system admits a steady-state behavior characterized by an operation of the grid at a synchronous frequency as well as a power balance for each single device. Based on this, we specify a set on which the dynamics of the power grid match the desired steady-state behavior and show that this set is control-invariant if and only if the control inputs to the generators are constant. Moreover, we constructively obtain network balance equations typically encountered in power flow analysis and subsequently show that the power system can be operated at the desired steady-state if and only if the network balance equations can be solved.
  • Optimal service station design for traffic mitigation via genetic algorithm and neural network
    Item type: Conference Paper
    Cenedese, Carlo; Cucuzzella, Michele; Cotta Ramusino, Adriano; et al. (2023)
    IFAC-PapersOnLine ~ 22nd IFAC World Congress
    This paper analyzes how the presence of service stations on highways affects traffic congestion. We focus on the problem of optimally designing a service station to achieve beneficial effects in terms of total traffic congestion and peak traffic reduction. We propose a genetic algorithm based on the recently proposed Cell Transmission Model with service station (CTM-s), that efficiently describes the dynamics of a service station. Then, we leverage the algorithm to train a neural network capable of solving the same problem, avoiding to implement the CTM-s. Finally, we validate the performance of our algorithms by using real data from Dutch highways.
  • Data-driven safety verification of stochastic systems via barrier certificates
    Item type: Conference Paper
    Salamati, Ali; Lavaei, Abolfazl; Soudjani, Sadegh; et al. (2021)
    IFAC-PapersOnLine ~ 7th IFAC Conference on Analysis and Design of Hybrid Systems (ADHS 2021)
    In this paper, we propose a data-driven approach to formally verify the safety of (potentially) unknown discrete-time continuous-space stochastic systems. The proposed framework is based on a notion of barrier certificates together with data collected from trajectories of unknown systems. We first reformulate the barrier-based safety verification as a robust convex problem (RCP). Solving the acquired RCP is hard in general because not only the state of the system lives in a continuous set, but also and more problematic, the unknown model appears in one of the constraints of RCP. Instead, we leverage a finite number of data, and accordingly, the RCP is casted as a scenario convex problem (SCP). We then relate the optimizer of the SCP to that of the RCP, and consequently, we provide a safety guarantee over the unknown stochastic system with a priori guaranteed confidence. We apply our approach to an unknown room temperature system by collecting sampled data from trajectories of the system and verify formally that temperature of the room lies in a comfort zone for a finite time horizon with a desired confidence.
  • Feedback stabilization of forming processes
    Item type: Conference Paper
    Bambach, Markus; Herty, Michael; Imran, Muhammad (2021)
    IFAC-PapersOnLine
    We develop online feedback control for forming processes governed by nonlinear material models. A novel approach based on a description using partial differential equation governing time-dependent viscoplastic deformations is proposed. The derivation of the feedback control law is based on a Lyapunov analysis of the linearised partial differential equation. Analytically and in the spatially one-dimensional setting exponential decay of the time evolution of perturbations to desired stress–strain states is established. Also, a similar performance of the feedback control is observed when implemented in a three–dimensional finite element simulation of titanium alloy forming.
Publications 1 - 10 of 178