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Model-based electron density profile estimation and control, applied to ITER

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arXiv 2021年

作者： Bosman, Thomas van Berkel, M. de Baar, M.R. DIFFER - Dutch Institute for Fundamental Energy Research PO Box 6336 Eindhoven5600HH Netherlands Eindhoven University of Technology Dept. of Mechanical Engineering Control Systems Technology Group PO Box 513 Eindhoven5600MB Netherlands

In contemporary magnetic confinement devices, the density distribution is sensed with interferometers and actuated with feedback controlled gas injection and open-loop pellet injection. This is at variance with the density control for ITER and DEMO, that will depend mainly on pellet injection as an actuator in feed-back control. This paper presents recent developments in state estimation and control of the electron density profile for ITER using relevant sensors and actuators. As a first step, Thomson scattering is included in an existing dynamic state observer. Second, model predictive control is developed as a strategy to regulate the density profile while avoiding limits associated with the total density (Greenwald limit) or gradients in the density distribution (e.g. neoclassical impurity transport). Simulations show that high quality density profile estimation can be achieved with Thomson Scattering and that the controller is capable of regulating the distribution as desired. Copyright © 2021, The Authors. All rights reserved.

关键词： Light scattering

Strong current-state and initial-state opacity of discrete-event systems

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arXiv 2021年

作者： Han, Xiaoguang Zhang, Kuize Zhang, Jiahui Li, Zhiwu Chen, Zengqiang College of Electronic Information and Automation Tianjin University of Science and Technology Tianjin300222 China Control Systems Group Technical University of Berlin Berlin10587 Germany Institute of Systems Engineering Macau University of Science and Technology Taipa519020 China School of Electro-Mechanical Engineering Xidian University Xi'an710071 China College of Artificial Intelligence Nankai University Tianjin300350 China

Opacity, as an important property in information-flow security, characterizes the ability of a system to keep some secret information from an intruder. In discrete-event systems, based on a standard setting in which an intruder has the complete knowledge of the system's structure, the standard versions of current-state opacity and initial-state opacity cannot perfectly characterize high-level privacy requirements. To overcome such a limitation, in this paper we propose two stronger versions of opacity in partially-observed discrete-event systems, called strong current-state opacity and strong initial-state opacity. Strong current-state opacity describes that an intruder never makes for sure whether a system is in a secret state at the current time, that is, if a system satisfies this property, then for each run of the system ended by a secret state, there exists a non-secret run whose observation is the same as that of the previous run. Strong initial-state opacity captures that the visit of a secret state at the initial time cannot be inferred by an intruder at any instant. Specifically, a system is said to be strongly initial-state opaque if for each run starting from a secret state, there exists a non-secret run of the system that has the same observation as the previous run has. To verify these two properties, we propose two information structures using a novel concurrent-composition technique, which has exponential-time complexity O(|X|4|Σo||Σuo||Σ|2|X|), where |X| (resp., |Σ|, |Σo|, |Σuo|) is the number of states (resp., events, observable events, unobservable events) of a system. Copyright © 2021, The Authors. All rights reserved.

关键词： Discrete event simulation

Walking control Based on Step Timing Adaptation

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Walking Control Based on Step Timing Adaptation

作者： Khadiv, Majid Herzog, Alexander Moosavian, S. Ali. A. Righetti, Ludovic Righetti, Ludovic Movement Generation and Control Group Max-Planck Institute for Intelligent Systems Tuebingen72076 Germany Google X Mountain ViewCA94043 United States Department of Mechanical Engineering K. N. Toosi University of Technology Tehran*** Iran Department of Electrical and Computer Engineering New York University BrooklynNY11201 United States

Step adjustment can improve the gait robustness of biped robots;however, the adaptation of step timing is often neglected as it gives rise to nonconvex problems when optimized over several footsteps. In this article, we argue that it is not necessary to optimize walking over several steps to ensure gait viability and show that it is sufficient to merely select the next step timing and location. Using this insight, we propose a novel walking pattern generator that optimally selects step location and timing at every control cycle. Our approach is computationally simple compared to standard approaches in the literature, yet guarantees that any viable state will remain viable in the future. We propose a swing foot adaptation strategy and integrate the pattern generator with an inverse dynamics controller that does not explicitly control the center of mass nor the foot center of pressure. This is particularly useful for biped robots with limited control authority over their foot center of pressure, such as robots with point feet or passive ankles. Extensive simulations on a humanoid robot with passive ankles demonstrate the capabilities of the approach in various walking situations, including external pushes and foot slippage, and emphasize the importance of step timing adaptation to stabilize walking. © 2004-2012 IEEE.

关键词： Anthropomorphic robots

Accuracy of voltage unbalance source assessment in three-phase three-wire electrical networks

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Accuracy of voltage unbalance source assessment in three-pha...

2020 Ural Smart Energy Conference, USEC 2020

作者： Bolgov, Viktor Kalyuzhniy, Dmitry Mechanical Engineering and Energy Technology Processes Control Work Group Centre for General and Basic Studies TalTech Virumaa College TalTech Estonian Maritime Academy Tallinn Estonia O.M. Beketov National University of Urban Economy in Kharkiv Dept. Systems of Urban of Electricity Supply and Power Consumption Kharkiv Ukraine

ISBN: (纸本)9781728197067

The power quality and related losses are topical problems in modern power engineering. There is a need to identify disturbing sources and assess their impact onto power quality in a point of evaluation on the basis of online measurements. The paper describes the accuracy of a brand new method for the assessment of voltage unbalance emissions in three-phase three-wire networks. Although power supply usually relies on the four-wire grids, the medium-voltage and maritime networks are based on the three-wire configuration. The modern techniques assessing voltage unbalance emission may generally be applied only to the cases with a single dominating emission or need invasive tests. The paper proposes a way to assess voltage unbalance emission from multiple sources by means of voltage and current measurements in a single point of evaluation and data about network configuration and component parameters. The paper describes the method in general terms and demonstrates high accuracy of the proposed solution as regards a methodological error and an impact of input data uncertainty. © 2020 IEEE.

关键词： Power quality

Linear Parameter-Varying control of Nonlinear systems based on Incremental Stability ⁎

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IFAC-PapersOnLine 2019年第28期52卷 38-43页

作者： P.J.W. Koelewijn R. Tóth H. Nijmeijer Control Systems Group Department of Electrical Engineering Dynamics and Control Group Department of Mechanical Engineering Eindhoven University of Technology 5612 AE Eindhoven The Netherlands

The Linear Parameter-Varying (LPV) framework has long been used to guarantee performance and stability requirements of nonlinear (NL) systems mainly through the L 2 -gain concept. However, recent research has pointed out that current L 2 -gain based LPV synthesis methods can fail to guarantee these requirements if stabilization of a non-zero operating condition (e.g. reference tracking, constant disturbance rejection, etc.) is required. In this paper, an LPV based synthesis method is proposed which is able to guarantee incremental performance and stability of an NL system even with reference and disturbance rejection objectives. The developed approach and the current L 2 LPV synthesis method are compared in a simulation study of the position control problem of a Duffing oscillator, showing performance improvements of the proposed method compared to the current L 2 -based approach for tracking and disturbance rejection.

关键词： Nonlinear systems Stability Stabilization Optimal control

Heterogeneous multi-agent resource allocation through multi-bidding with applications to precision agriculture⁎

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IFAC-PapersOnLine 2018年第23期51卷 194-199页

作者： Cobbenhagen, A.T.J.R. Antunes, D.J. van de Molengraft, M.J.G. Heemels, W.P.M.H. Control Systems Technology group Dept. of Mechanical Engineering Eindhoven University of Technology Eindhoven Netherlands

In this paper we consider the problem of allocating multiple resources to a number of clients by a group of heterogeneous agents over time such that the clients can produce products while maximizing a profit function. We propose an approximate optimization framework in which every client provides multiple bids from which the agents choose such that an allocation is feasible and that the profit function is maximized over time. The proposed framework exploits decomposition techniques that can be used for large-scale multi-agent resource allocation problems in which the cost objective is additive, the dynamics of product generation is non-linear and the agents have different capabilities. Interestingly, the decomposition can be solved in a distributed fashion, enabling application to large-scale problems. We apply this decomposition to the management of resources and agents in precision agriculture as an inspirational and important application domain of the obtained results. We show that our framework can be used in order to schedule the time, location and quantity of resources that every agent must provide whilst optimizing the profit of the entire farm over the growing season. © 2018

关键词： Dynamic programming Agriculture Multi agent systems Precision agriculture Profitability Resource allocation Approximate dynamic programming Approximate optimization Decomposition technique Distributed optimization Heterogeneous agents Multi agent Optimal controls Resource allocation problem

Urgency-aware optimal routing in repeated games through artificial currencies

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arXiv 2020年

作者： Salazar, Mauro Paccagnan, Dario Agazzi, Andrea Heemels, W.P.M.H. Control Systems Technology Group Department of Mechanical Engineering Eindhoven University of Technology Netherlands Computational Optimization Group Department of Computing Imperial College London United Kingdom Department of Mathematics Duke University United States

When people choose routes minimizing their individual delay, the aggregate congestion can be much higher compared to that experienced by a centrally-imposed routing. Yet centralized routing is incompatible with the presence of self-interested agents. How can we reconcile the two? In this paper we address this question within a repeated game framework and propose a fair incentive mechanism based on artificial currencies that routes selfish agents in a system-optimal fashion, while accounting for their temporal preferences. We instantiate the framework in a parallel-network whereby agents commute repeatedly (e.g., daily) from a common start node to the end node. Thereafter, we focus on the specific two-arcs case whereby, based on an artificial currency, the agents are charged when traveling on the first, fast arc, whilst they are rewarded when traveling on the second, slower arc. We assume the agents to be rational and model their choices through a game where each agent aims at minimizing a combination of today’s discomfort, weighted by their urgency, and the average discomfort encountered for the rest of the period (e.g., a week). We show that, if prices of artificial currencies are judiciously chosen, the routing pattern converges to a system-optimal solution, while accommodating the agents’ urgency. We complement our study through numerical simulations. Our results show that it is possible to achieve a system-optimal solution whilst reducing the agents’ perceived discomfort by 14-20% when compared to a centralized optimal but urgency-unaware policy. Copyright © 2020, The Authors. All rights reserved.

关键词： Optimal systems

On the Role of Models in Learning control: Actor-Critic Iterative Learning control

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arXiv 2020年

作者： Poot, Maurice Portegies, Jim Oomen, Tom Control Systems Technology Group Dept. of Mechanical Engineering Eindhoven University of Technology Eindhoven Netherlands CASA Dept. of Mathematics and Computer Science Eindhoven University of Technology Eindhoven Netherlands

关键词： Learning algorithms

Learning event-triggered control from data through joint optimization

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arXiv 2020年

作者： Funk, Niklas Baumann, Dominik Berenz, Vincent Trimpe, Sebastian Intelligent Control Systems Group Max Planck Institute for Intelligent Systems Stuttgart Germany Empirical Inference Department Max Planck Institute for Intelligent Systems Tübingen Germany Institute for Data Science in Mechanical Engineering RWTH Aachen University Aachen Germany

We present a framework for model-free learning of event-triggered control strategies. Event-triggered methods aim to achieve high control performance while only closing the feedback loop when needed. This enables resource savings, e.g., network bandwidth if control commands are sent via communication networks, as in networked control systems. Event-triggered controllers consist of a communication policy, determining when to communicate, and a control policy, deciding what to communicate. It is essential to jointly optimize the two policies since individual optimization does not necessarily yield the overall optimal solution. To address this need for joint optimization, we propose a novel algorithm based on hierarchical reinforcement learning. The resulting algorithm is shown to accomplish high-performance control in line with resource savings and scales seamlessly to nonlinear and high-dimensional systems. The method's applicability to real-world scenarios is demonstrated through experiments on a six degrees of freedom real-time controlled manipulator. Further, we propose an approach towards evaluating the stability of the learned neural network policies. © 2020, CC BY-NC-ND.

关键词： Reinforcement learning