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arXiv 2018年

作者： Mammarella, Martina Lorenzen, Matthias Capello, Elisa Park, Hyeongjun Dabbene, Fabrizio Guglieri, Giorgio Romano, Marcello Allgöwer, Frank Department of Mechanical and Aerospace Engineering Politecnico di Torino Torino Italy Institute for Systems Theory and Automatic Control University of Stuttgart Germany Department of Mechanical and Aerospace Engineering Department of Mechanical and Aerospace Engineering New Mexico State University Las CrucesNM United States CNR-IEIIT Politecnico di Torino Torino Italy Department of Mechanical and Aerospace Naval Postgraduate School MontereyCA United States

In this paper, a sampling-based Stochastic Model Predictive control algorithm is proposed for discrete-time linear systems subject to both parametric uncertainties and additive disturbances. One of the main drivers for the development of the proposed control strategy is the need of reliable and robust guidance and control strategies for automated rendezvous and proximity operations between spacecraft. To this end, the proposed control algorithm is validated on a floating spacecraft experimental testbed, proving that this solution is effectively implementable in real-time. Parametric uncertainties due to the mass variations during operations, linearization errors, and disturbances due to external space environment are simultaneously considered. The approach enables to suitably tighten the constraints to guarantee robust recursive feasibility when bounds on the uncertain variables are provided. Moreover, the offline sampling approach in the control design phase shifts all the intensive computations to the offline phase, thus greatly reducing the online computational cost, which usually constitutes the main limit for the adoption of Stochastic Model Predictive control schemes, especially for low-cost on-board hardware. Numerical simulations and experiments show that the approach provides probabilistic guarantees on the success of the mission, even in rather uncertain and noise situations, while improving the spacecraft performance in terms of fuel consumption. Copyright © 2018, The Authors. All rights reserved.

关键词： Stochastic systems

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Numerical Evaluation of a Robust Self-Triggered MPC Algorithm

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IFAC-PapersOnLine 2016年第22期49卷 151-156页

作者： Brunner, Florian D. Heemels, W.P.M.H. Allgöwer, Frank Institute for Systems Theory and Automatic Control University of Stuttgart Pfaffenwaldring 9 Stuttgart70569 Germany Control System Technology Group Department of Mechanical Engineering Eindhoven University of Technology Netherlands

We present numerical examples demonstrating the efficacy of a recently proposed self-triggered model predictive control scheme for disturbed linear discrete-time systems with hard constraints on the input and state. In order to reduce the amount of communication between the controller and the actuator, the control input is not re-computed at each point in time but only at certain sampling instances. These instances are determined in a self-triggered fashion in the sense that at every sampling instant the next sampling instant is computed as a function of the current system state. A compact set in the state space, whose size is a design parameter in the control scheme, is stabilized. © 2016

关键词： Discrete time control systems Digital control systems Model predictive control Predictive control systems Robustness (control systems) control inputs control schemes Design parameters Hard constraints Linear discrete time systems Predictive control Sampling instants Self triggered controls

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Finding the proper node ranking method for complex networks

arXiv

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arXiv 2018年

作者： Yu, Senbin Gao, Liang Wang, Yi-Fan Institute of Transportation Systems Science and Engineering MOE Key Laboratory of Urban Transportation System Theory and Technology State Key Laboratory of Rail Traffic Control and Safety Center of Cooperative Innovation for Beijing Metropolitan Transportation Beijing Jiaotong University Beijing100044 China Yinchuan Municipal Bureau of Big Data Management and Service Yinchuan750011 China

Ranking node importance is crucial in understanding network structure and function on complex networks. Degree, h-index and coreness are widely used, but which one is more proper to a network associated with a dynamical process, e.g. SIR spreading process, is still unclear. To fill this gap, a, which is extracted from the fitting 1 function (f(x) = 1 − e2a(x−b)+1) of the average number of nodes in each radius of the neighborhood of a node, is proposed. Experiment results which are carried out on twenty real-world networks show that a can classify which of the three measures (degree, h-index and coreness) is more proper to a network in ranking node importance. We also find that [b/3] is a good indicator for forecasting the optimal radius of the neighborhood of a node in ranking node importance for a given network. To the best of our knowledge, it is the first solution of this interesting and open issue. Furthermore, by extending the range of neighborhood where we construct an operator ℋ on of a node, we propose a new method to quantify the importance of a node. The ranking accuracies of most networks can be improved when the radius is increased from 0 to its forecasting optimal radius and the improvement, for the best case, reaches up to 111%. The performances will reduce on half of the networks studied in this paper if we roughly extend the radius of the neighborhood. Our work deepens the understanding of how to find out the proper node ranking method for complex networks. The proposed methods bridge the gaps among network structure and node importance, and may have potential applications in controlling the outbreak of disease, designing of optimal information spreading *** Codes Game theory, economics, social and behavioral sciences Copyright © 2018, The Authors. All rights reserved.

关键词： Complex networks

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Local articulation points in complex networks

arXiv

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arXiv 2018年

作者： Yu, Senbin Gao, Liang Song, Rongqiu Institute of Transportation Systems Science and Engineering MOE Key Laboratory of Urban Transportation System Theory and Technology State Key Laboratory of Rail Traffic Control and Safety Center of Cooperative Innovation for Beijing Metropolitan Transportation Beijing Jiaotong University Beijing100044 China Yinchuan Municipal Bureau of Big Data Management and Service Yinchuan750011 China

An articulation point (AP) is any node whose removal increases the number of connected components of a graph. There is no doubt that this kind of node which occupies a non-ignorable fraction of real-world networks plays a key role in ensuring the connectivity. However, we should not thus neglect the impacts of non-APs nodes. In this paper, we define a local AP (LAP) whose removal will increase the number of connected components within its r-step neighborhood. Through investigating the fraction of LAPs in forty-five real networks, we find a critical proportion Scr, which is equal to 0.5 (S = r/D, D is the diameter of a network), and this result can also be turned out in ER networks. In addition, we present a unique advantage of LAPs in dismantling networks under the process of targeted attack, compared with APs, which provide another way of thinking to improve the calculation efficiency of APs and design better targeted attack strategy of network *** Codes Game theory, economics, social and behavioral sciences Copyright © 2018, The Authors. All rights reserved.

关键词： Complex networks

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Model Predictive Planning and control Applied to Critical Traffic Situations

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ATZ worldwide 2016年第9期118卷 64-69页

作者： Götte, Christian Keller, Martin Haß, Carsten Bertram, Torsten Institute of Control Theory and Systems Engineering of the TU Dortmund Dortmund Germany ZF TRW Düsseldorf Germany

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Final-state constrained optimal control via a projection operator approach

arXiv

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arXiv 2017年

作者： Notarnicola, Ivano Bayer, Florian A. Notarstefano, Giuseppe Allgöwer, Frank Department of Engineering Università del Salento Lecce Italy Institute for Systems Theory and Automatic Control University of Stuttgart Stuttgart70550 Germany

In this paper we develop a numerical method to solve nonlinear optimal control problems with final-state constraints. Specifically, we extend the PRojection Operator based Netwon's method for Trajectory Optimization (PRONTO), which was proposed by Hauser for unconstrained optimal control problems. While in the standard method final-state constraints can be only approximately handled by means of a terminal penalty, in this work we propose a methodology to meet the constraints exactly. Moreover, our method guarantees recursive feasibility of the final-state constraint. This is an appealing property especially in realtime applications in which one would like to be able to stop the computation even if the desired tolerance has not been reached, but still satisfy the constraints. Following the same conceptual idea of PRONTO, the proposed strategy is based on two main steps which (differently from the standard scheme) preserve the feasibility of the final-state constraints: (i) solve a quadratic approximation of the nonlinear problem to find a descent direction, and (ii) get a (feasible) trajectory by means of a feedback law (which turns out to be a nonlinear projection operator). To find the (feasible) descent direction we take advantage of final-state constrained Linear Quadratic optimal control methods, while the second step is performed by suitably designing a constrained version of the trajectory tracking projection operator. The effectiveness of the proposed strategy is tested on the optimal state transfer of an inverted pendulum. Copyright © 2017, The Authors. All rights reserved.

关键词： Numerical methods

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Relative dynamics estimation of non-cooperative spacecraft with unknown orbit elements and inertial tensor

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Chinese Journal of Aeronautics 2016年第2期29卷 479-491页

作者： Yu Han Zhang Xiujie Liu Lingyu Wang Shuo Song Shenmin Beijing Institute of Astronautical Systems Engineering Beijing 100076 China center for control theory and guidance technology harbin institute of technology Harbin 150001 China Academy of Fundamental and Interdisciplinary Science Harbin Institute of Technology Harbin 150001 China

The state estimation for relative motion with respect to non-cooperative spacecraft in ren- dezvous and docking （RVD） is a challenging problem. In this paper, a completely non-cooperative case is considered, which means that both orbit elements and inertial tensor of target spacecraft are unknown. By formulating the equations of relative translational dynamics in the orbital plane of chaser spacecraft, the issue of unknown orbit elements is solved. And for the problem for unknown inertial tensor, we propose a novel robust estimator named interaction cubature Kalman filter （InCKF） to handle it. The novel filter consists of multiple concurrent CKFs interlacing with a max- imum a posteriori （MAP） estimator. The initial estimations provided by the multiple CKFs are used in a Bayesian framework to form description of posteriori probability about inertial tensor and the MAP estimator is applied to giving the optimal estimation. By exploiting special property of spherical-radial （SR） rule, a novel method with respect to approximating the likelihood probability of inertial tensor is presented. In addition, the issue about vision sensor＇s location inconformity with center mass of chaser spacecraft is also considered. The performance of this filter is demonstrated by the estimation problem of RVD at the final phase. And the simulation results show that the perfor- mance of InCKF is better than that of extended Kalman filter （EKF） and the estimation accuracy of oose and attitude is relatively high even in the comoletely non-coooerative case.

关键词： Cubature Kalman filter MAP estimator Non-cooperative spacecraft Relative motion Stereo vision

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Consensus analysis of systems with time-varying interactions : An event-triggered approach

arXiv

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arXiv 2017年

作者： Kumar, S. Arun Chowdhury, N.R. Srikant, S. Raisch, J. Department of Systems and Control Engineering Indian Institute of Technology Bombay Mumbai400076 India Fachgebiet Regelungssysteme Technische Universitat Berlin Berlin10587 Germany Systems and Control Theory Group Max Planck Institute for Dynamics of Complex Technical Systems

We present consensus analysis of systems with single integrator dynamics interacting via time-varying graphs under the event-triggered control paradigm. Event-triggered control sparsifies the control applied, thus reducing the control effort expended. Initially, we consider a multi-agent system with persistently exciting interactions and study the behaviour under the application of event-triggered control with two types of trigger functions-static and dynamic *** show that while in the case of static trigger, the edge-states converge to a ball around the origin, the dynamic trigger function forces the states to reach consensus exponentially. Finally, we extend these results to a more general setting where we consider switching topologies. We show that similar results can be obtained for agents interacting via switching topologies and validate our results by means of simulations. Copyright © 2017, The Authors. All rights reserved.

关键词： Multi agent systems

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Iterative Learning control Applied to a Deformable Mirror

Iterative Learning Control Applied to a Deformable Mirror

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第36届中国控制会议

作者： Blazej Cichy Petr Augusta Krzysztof Galkowski Eric Rogers Institute of Control and Computation Engineering University of Zielona Góra Institute of Information Theory and Automation The Czech Academy of Sciences Department of Electronics and Computer Science University of Southampton

An unconditionally stable finite difference discretization motivated by the well-known Crank-Nicolson method is used to develop an iterative learning control design for systems whose dynamics are described by a fourth-order partial differential equation.A discrete in time and space model of a deformable rectangular mirror is derived in this setting and forms the basi s for the new design,where a model for the actuator dynamics is also included.A numerical case study is given to demonstrate the properties of the new design.

关键词： Crank-Nicolson Discretization Method Iterative Learning control Thin Plates

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Stabilization of Distributed Parameter Hopfield Neural Networks Based on Operator Spectral theory 35

Stabilization of Distributed Parameter Hopfield Neural Netwo...

引用

第35届中国控制会议

作者： YIN Hang HUANG Xianlin ZHANG Hongyang GAO Xiao-Zhi Center for Control Theory and Guidance Technology Harbin Institute of Technology Department of Electrical Engineering and Automation Aalto University School of Electrical Engineering

ISBN: (纸本)9781509009107

In this paper, we analyze the stability of distributed Hopfield neural networks. Distributed parameter Hopfield neural networks model is established by PDEs so state space of the controlled system belongs infinity dimensions, which is different from ODEs and DAEs models. Reaction-Diffusion Hopfield neural networks model is a new class of net systems which exist widely in control science, intelligent computation, cells of neurology and biology mathematica. Most of papers about Hopfield neural networks apply average Lyapunov function and M-matrix theory to study stability. Now, we use operator spectral theory to obtain stability of the system, which does not need complex calculation. At last, we make some simulations verify our criterions.

关键词： Stability Operator Spectral theory Reaction-Diffusion System Hopfield Neural Network

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