Journal: IFAC-PapersOnLine
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Elsevier
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Publications 1 - 10 of 179
- Augmenting ultra-wideband localization with computer vision for accurate flightItem type: Conference Paper
IFAC-PapersOnLine ~ 20th IFAC World Congress. ProceedingsHoeller, David; Ledergerber, Anton; Hamer, Michael; et al. (2017)Ultra-wideband radio networks enable low-cost, low-computation robot localization in semi-structured environments; however, previous results have shown that these localization systems suffer from spatially-varying measurement biases, leading to a spatially-varying offset between the physical and the estimated position. In tasks where absolute positioning or high tracking accuracy is required, this offset can lead to failure of the task. This paper proposes augmenting ultra-wideband-based localization with visual localization to improve estimation accuracy for critical tasks. It also presents a control strategy that takes the camera measurement process into account, and allows the ultra-wideband system’s measurement biases to be learned and compensated over multiple executions of the task. This bias compensation can be used to improve the accuracy of the task in the case of visual impairment. The effectiveness of the proposed framework is demonstrated by accurately flying a quadrocopter to a landing platform using on-board estimation and control. - A distributed voltage stability margin for power distribution networksItem type: Conference Paper
IFAC-PapersOnLine ~ 20th IFAC World Congress. ProceedingsAolaritei, Liviu; Bolognani, Saverio; Dörfler, Florian (2017)We consider the problem of characterizing and assessing the voltage stability in power distribution networks. Different from previous formulations, we consider the branch-flow parametrization of the power system state, which is particularly effective for radial networks. Our approach to the voltage stability problem is based on a local, approximate, yet highly accurate characterization of the determinant of the power flow Jacobian. Our determinant approximation allows us to construct a voltage stability index that can be computed in a fully scalable and distributed fashion. We provide an upper bound on the approximation error, and we show how the proposed index outperforms other voltage indices recently proposed in the literature. - Payoff-based approach to learning Nash Equilibria in Convex GamesItem type: Conference Paper
IFAC-PapersOnLine ~ 20th IFAC World Congress. ProceedingsTatarenko, Tatiana; Kamgarpour, Maryam (2017)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. - Withdrawn: Rethinking the Micro-Foundation of Opinion Dynamics: Rich Consequences of an Inconspicuous ChangeItem type: Conference Paper
IFAC-PapersOnLine ~ 3rd IFAC Workshop on Cyber-Physical & Human Systems, CPHS 2020. ProceedingsMei, Wenjun; Bullo, Francesco; Chen, Ge; et al. (2020) - Embedded optimization methods for industrial automatic controlItem type: Conference Paper
IFAC-PapersOnLine ~ 20th IFAC World Congress. ProceedingsFerreau, Hand Joachim; Almer, Stefan; Verschueren, Robin; et al. (2017)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 systemsItem type: Conference Paper
IFAC-PapersOnLineSubotic, Irina; Gross, Dominic (2023)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 modelItem type: Conference Paper
IFAC-PapersOnLine ~ 6th IFAC Workshop on Distributed Estimation and Control in Networked Systems, NECSYS 2016. ProceedingsArghir, Catalin; Groß, Dominic; Dörfler, Florian (2016)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 networkItem type: Conference Paper
IFAC-PapersOnLine ~ 22nd IFAC World CongressCenedese, Carlo; Cucuzzella, Michele; Cotta Ramusino, Adriano; et al. (2023)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 certificatesItem type: Conference Paper
IFAC-PapersOnLine ~ 7th IFAC Conference on Analysis and Design of Hybrid Systems (ADHS 2021)Salamati, Ali; Lavaei, Abolfazl; Soudjani, Sadegh; et al. (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 processesItem type: Conference Paper
IFAC-PapersOnLineBambach, Markus; Herty, Michael; Imran, Muhammad (2021)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 179