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  • Data-Driven Distributed Stochastic Model Predictive Control with Closed-Loop Chance Constraint Satisfaction
    arXiv.cs.SY Pub Date : 2020-04-06
    Simon Muntwiler*; Kim P. Wabersich*; Lukas Hewing; Melanie N. Zeilinger

    Distributed model predictive control methods for uncertain systems often suffer from considerable conservatism and can tolerate only small uncertainties, due to the use of robust formulations that are amenable to distributed design and computational methods. In this work, we propose a distributed stochastic model predictive control (DSMPC) scheme for dynamically coupled linear discrete-time systems

    更新日期:2020-04-08
  • Feedforward control for wave disturbance rejection on floating offshore wind turbines
    arXiv.cs.SY Pub Date : 2020-04-06
    Mees Al; Alessandro Fontanella; Daan van der Hoek; Yichao Liu; Marco Belloli; Jan-Willem van Wingerden

    Floating offshore wind turbines allow wind energy to be harvested in deep waters. However, additional dynamics and structural loads may result when the floating platform is being excited by wind and waves. In this work, the conventional wind turbine controller is complemented with a novel linear feedforward controller based on wave measurements. The objective of the feedforward controller is to attenuate

    更新日期:2020-04-08
  • Power systems with high renewable energy sources: A review of inertia and frequency control strategies over time
    arXiv.cs.SY Pub Date : 2020-04-06
    Ana Fernández-Guillamón; Emilio Gómez-Lázaro; Eduard Muljadi; Angel Molina-García

    Traditionally, inertia in power systems has been determined by considering all the rotating masses directly connected to the grid. During the last decade, the integration of renewable energy sources, mainly photovoltaic installations and wind power plants, has led to a significant dynamic characteristic change in power systems. This change is mainly due to the fact that most renewables have power electronics

    更新日期:2020-04-08
  • Successive Eigenvalue Removal for Multi-Soliton Spectral Amplitude Estimation
    arXiv.cs.SY Pub Date : 2020-04-06
    Alexander Span; Vahid Aref; Henning Buelow; Stephan ten Brink

    Optical nonlinear Fourier transform-based communication systems require an accurate estimation of a signal's nonlinear spectrum, computed usually by piecewise approximation methods on the signal samples. We propose an algorithm, named successive eigenvalue removal, to improve the spectrum estimation of a multi-soliton pulse. It exploits a property of the Darboux transform that allows removing eigenvalues

    更新日期:2020-04-08
  • Control of Unknown Nonlinear Systems with Linear Time-Varying MPC
    arXiv.cs.SY Pub Date : 2020-04-06
    Dimitris Papadimitriou; Ugo Rosolia; Francesco Borrelli

    We present a Model Predictive Control (MPC) strategy for unknown input-affine nonlinear dynamical systems. A non-parametric method is used to estimate the nonlinear dynamics from observed data. The estimated nonlinear dynamics are then linearized over time varying regions of the state space to construct an Affine Time Varying (ATV) model. Error bounds arising from the estimation and linearization procedure

    更新日期:2020-04-08
  • The Impact of Message Passing in Agent-Based Submodular Maximization
    arXiv.cs.SY Pub Date : 2020-04-07
    David Grimsman; Matthew R. Kirchner; João P. Hespanha; Jason R. Marden

    Submodular maximization problems are a relevant model set for many real-world applications. Since these problems are generally NP-Hard, many methods have been developed to approximate the optimal solution in polynomial time. One such approach uses an agent-based greedy algorithm, where the goal is for each agent to choose an action from its action set such that the union of all actions chosen is as

    更新日期:2020-04-08
  • Estimation of Stability Regions of Droop Control Slopes for MMC-based MTDC Systems
    arXiv.cs.SY Pub Date : 2020-04-07
    Yuntao Zou; Lei Zhang; Jiangchao Qin

    This paper proposes a computational method to efficiently and quickly estimate stability regions of droop control slopes for modular multilevel converter (MMC)-based multiterminal dc (MTDC) systems. The proposed method is based on a general small-signal model consisting of a dc grid with arbitrary topology and MMCs with dq controllers. The general small-signal model developed by a systematic way can

    更新日期:2020-04-08
  • Adaptive Fuzzy Control for Fractional-Order Interconnected Systems with Unknown\\ Control Directions
    arXiv.cs.SY Pub Date : 2020-04-07
    Bingyun Liang; Shiqi Zheng; Choon Ki Ahn; Feng Liu

    This paper concentrates on the study of the decentralized fuzzy control method for a class of fractional-order interconnected systems with unknown control directions. To overcome the difficulties caused by the multiple unknown control directions in fractional-order systems, a novel fractional-order Nussbaum function technique is proposed. This technique is much more general than those of existing works

    更新日期:2020-04-08
  • Challenges and Opportunities in CPS Security: A Physics-based Perspective
    arXiv.cs.SY Pub Date : 2020-04-07
    Chuadhry Mujeeb Ahmed; Jianying Zhou

    The integration of cyber technologies (computing and communication) with the physical world gives rise to complex systems referred to as Cyber Physical Systems (CPS), for example, manufacturing, transportation, smart grid, and water treatment. Many of those systems are part of the critical infrastructure and need to perform safely, reliably, and securely in real-time. CPS security is challenging as

    更新日期:2020-04-08
  • Distributed Coordination of Deferrable Loads: A Real-time Market with Self-fulfilling Forecasts
    arXiv.cs.SY Pub Date : 2020-04-07
    Hazem A. Abdelghany; Simon H. Tindemans; Mathijs M. de Weerdt; Han la Poutré

    Increased uptake of variable renewable generation and further electrification of energy demand necessitate efficient coordination of flexible demand resources to make most efficient use of power system assets. Flexible electrical loads are typically small, numerous, heterogeneous and owned by self-interested agents. Considering the multi-temporal nature of flexibility and the uncertainty involved,

    更新日期:2020-04-08
  • Combining system identification with reinforcement learning-based MPC
    arXiv.cs.SY Pub Date : 2020-04-07
    Andreas B. Martinsen; Anastasios M. Lekkas; Sebastien Gros

    In this paper we propose and compare methods for combining system identification (SYSID) and reinforcement learning (RL) in the context of data-driven model predictive control (MPC). Assuming a known model structure of the controlled system, and considering a parametric MPC, the proposed approach simultaneously: a) Learns the parameters of the MPC using RL in order to optimize performance, and b) fits

    更新日期:2020-04-08
  • Learning Control Barrier Functions from Expert Demonstrations
    arXiv.cs.SY Pub Date : 2020-04-07
    Alexander Robey; Haimin Hu; Lars Lindemann; Hanwen Zhang; Dimos V. Dimarogonas; Stephen Tu; Nikolai Matni

    Inspired by the success of imitation and inverse reinforcement learning in replicating expert behavior through optimal control, we propose a learning based approach to safe controller synthesis based on control barrier functions (CBFs). We consider the setting of a known nonlinear control affine dynamical system and assume that we have access to safe trajectories generated by an expert - a practical

    更新日期:2020-04-08
  • Man in the middle and current injection attacks against the KLJN key exchanger compromised by DC sources
    arXiv.cs.SY Pub Date : 2020-04-03
    Mutaz Melhem; Laszlo Kish

    This study addresses a new question regarding the security of the Kirchhoff-Law-Johnson-Noise (KLJN) scheme compromised by DC sources at Alice and Bob: What is the impact of these parasitic sources on active attacks, such as the man-in-the-middle (MITM) attack, or the current injection attack? The surprising answer is that the parasitic DC sources actually increase the security of the system because

    更新日期:2020-04-08
  • State Space Advanced Fuzzy Cognitive Map approach for automatic and non Invasive diagnosis of Coronary Artery Disease
    arXiv.cs.SY Pub Date : 2020-04-03
    Ioannis D. Apostolopoulos; Peter P. Groumpos; Dimitris I. Apostolopoulos

    Purpose: In this study, the recently emerged advances in Fuzzy Cognitive Maps (FCM) are investigated and employed, for achieving the automatic and non-invasive diagnosis of Coronary Artery Disease (CAD). Methods: A Computer-Aided Diagnostic model for the acceptable and non-invasive prediction of CAD using the State Space Advanced FCM (AFCM) approach is proposed. Also, a rule-based mechanism is incorporated

    更新日期:2020-04-08
  • Benefiting from Linear Behaviour of a Nonlinear Reset-based Element at Certain Frequencies
    arXiv.cs.SY Pub Date : 2020-04-07
    Nima Karbasizadeh; Ali Ahmadi Dastjerdi; Niranjan Saikumar; Duarte Valerio; S. Hassan HosseinNia

    This paper addresses a phenomenon caused by resetting only one of the two states of a so-called second order "Constant in gain Lead in phase" (CgLp) element. CgLp is a recently introduced reset-based nonlinear element, bound to circumvent the well-known linear control limitation -- the waterbed effect. The ideal behaviour of such a filter in the frequency domain is unity gain while providing a phase

    更新日期:2020-04-08
  • Granular Computing: An Augmented Scheme of Degranulation Through a Modified Partition Matrix
    arXiv.cs.SY Pub Date : 2020-04-03
    Kaijie Xu; Witold Pedrycz; Zhiwu Li; Mengdao Xing

    As an important technology in artificial intelligence Granular Computing (GrC) has emerged as a new multi-disciplinary paradigm and received much attention in recent years. Information granules forming an abstract and efficient characterization of large volumes of numeric data have been considered as the fundamental constructs of GrC. By generating prototypes and partition matrix, fuzzy clustering

    更新日期:2020-04-08
  • Bayesian Optimization with Safety Constraints: Safe and Automatic Parameter Tuning in Robotics
    arXiv.cs.SY Pub Date : 2016-02-14
    Felix Berkenkamp; Andreas Krause; Angela P. Schoellig

    Robotic algorithms typically depend on various parameters, the choice of which significantly affects the robot's performance. While an initial guess for the parameters may be obtained from dynamic models of the robot, parameters are usually tuned manually on the real system to achieve the best performance. Optimization algorithms, such as Bayesian optimization, have been used to automate this process

    更新日期:2020-04-08
  • Combined Robust and Stochastic Model Predictive Control for Models of Different Granularity
    arXiv.cs.SY Pub Date : 2020-03-14
    Tim Brüdigam; Johannes Teutsch; Dirk Wollherr; Marion Leibold

    Long prediction horizons in Model Predictive Control (MPC) often prove to be efficient, however, this comes with increased computational cost. Recently, a Robust Model Predictive Control (RMPC) method has been proposed which exploits models of different granularity. The prediction over the control horizon is split into short-term predictions with a detailed model using MPC and long-term predictions

    更新日期:2020-04-08
  • Controlling Human Utilization of Failure-Prone Systems via Taxes
    arXiv.cs.SY Pub Date : 2018-02-26
    Ashish R. Hota; Shreyas Sundaram

    We consider a game-theoretic model where individuals compete over a shared failure-prone system or resource. We investigate the effectiveness of a taxation mechanism in controlling the utilization of the resource at the Nash equilibrium when the decision-makers have behavioral risk preferences, captured by prospect theory. We first observe that heterogeneous prospect-theoretic risk preferences can

    更新日期:2020-04-08
  • Stealth Attacks on the Smart Grid
    arXiv.cs.SY Pub Date : 2018-08-13
    Ke Sun; Iñaki Esnaola; Samir M. Perlaza; H. Vincent Poor

    Random attacks that jointly minimize the amount of information acquired by the operator about the state of the grid and the probability of attack detection are presented. The attacks minimize the information acquired by the operator by minimizing the mutual information between the observations and the state variables describing the grid. Simultaneously, the attacker aims to minimize the probability

    更新日期:2020-04-08
  • Sigma-3: Integration and Analysis of a 6 DOF Robotic Arm Configuration in a Rescue Robot
    arXiv.cs.SY Pub Date : 2020-02-27
    R. A. Bindu; A. A. Neloy; S. Alam; N. J Moni; S. Siddique

    This paper introduces a rescue robot named Sigma 3 which is developed for potential applications such as helping hands for humans where a human can not reach to have an assessment of the hazardous environment. Also, these kinds of robot can be controlled remotely with an adequate control system. The proposed methodology forces on two issues : 1. Novel mechanism design for measuring rotation, joints

    更新日期:2020-04-08
  • Classical and quantum regression analysis for the optoelectronic performance of NTCDA/p-Si UV photodiode
    arXiv.cs.SY Pub Date : 2020-01-02
    Ahmed M. El-Mahalawy; Kareem H. El-Safty

    Due to the pivotal role of UV photodiodes in many technological applications in tandem with the high efficiency achieved by machine learning techniques in regression and classification problems, different artificial intelligence (AI) techniques are adopted to simulate and model the performance of organic/inorganic heterojunction UV photodiode. Herein, the performance of a fabricated Au/NTCDA/p-Si/Al

    更新日期:2020-04-06
  • Trajectory Optimization for Nonlinear Multi-Agent Systems using Decentralized Learning Model Predictive Control
    arXiv.cs.SY Pub Date : 2020-04-02
    Edward L. Zhu; Yvonne R. Stürz; Ugo Rosolia; Francesco Borrelli

    We present a decentralized trajectory optimization scheme based on learning model predictive control for multi-agent systems with nonlinear decoupled dynamics under separable cost and coupled state constraints. By performing the same task iteratively, data from previous task executions is used to construct and improve local time-varying safe sets and an approximate value function. These are used in

    更新日期:2020-04-06
  • Event-Triggered Distributed Inference
    arXiv.cs.SY Pub Date : 2020-04-02
    Aritra Mitra; Saurabh Bagchi; Shreyas Sundaram

    We study a setting where each agent in a network receives certain private signals generated by an unknown static state that belongs to a finite set of hypotheses. The agents are tasked with collectively identifying the true state. To solve this problem in a communication-efficient manner, we propose an event-triggered distributed learning algorithm that is based on the principle of diffusing low beliefs

    更新日期:2020-04-06
  • Data-Driven Transient Stability Boundary Generation for Online Security Monitoring
    arXiv.cs.SY Pub Date : 2020-04-03
    Rong Yan; Guangchao Geng; Quanyuan Jiang

    Transient stability boundary (TSB) is an important tool in power system online security monitoring, but practically it suffers from high computational burden using state-of-the-art methods, such as time-domain simulation (TDS), with numerous scenarios taken into account (e.g., operating points (OPs) and N-1 contingencies). The purpose of this work is to establish a data-driven framework to generate

    更新日期:2020-04-06
  • FeederGAN: Synthetic Feeder Generation via Deep Graph Adversarial Nets
    arXiv.cs.SY Pub Date : 2020-04-03
    Ming Liang; Yao Meng; Jiyu Wang; David Lubkeman; Ning Lu

    This paper presents a novel, automated, generative adversarial networks (GAN) based synthetic feeder generation mechanism, abbreviated as FeederGAN. FeederGAN digests real feeder models represented by directed graphs via a deep learning framework powered by GAN and graph convolutional networks (GCN). From power system feeder model input files, device connectivity is mapped to the adjacency matrix while

    更新日期:2020-04-06
  • Incremental Affine Abstraction of Nonlinear Systems
    arXiv.cs.SY Pub Date : 2020-04-03
    Syed M. Hassaan; Mohammad Khajenejad; Spencer Jensen; Qiang Shen; Sze Zheng Yong

    In this paper, we propose an incremental abstraction method for dynamically over-approximating nonlinear systems in a bounded domain by solving a sequence of linear programs, resulting in a sequence of affine upper and lower hyperplanes with expanding operating regions. Although the affine abstraction problem can be solved offline using a single linear program, existing approaches suffer from a computation

    更新日期:2020-04-06
  • Reinforcement Learning for Mixed-Integer Problems Based on MPC
    arXiv.cs.SY Pub Date : 2020-04-03
    Sebastien Gros; Mario Zanon

    Model Predictive Control has been recently proposed as policy approximation for Reinforcement Learning, offering a path towards safe and explainable Reinforcement Learning. This approach has been investigated for Q-learning and actor-critic methods, both in the context of nominal Economic MPC and Robust (N)MPC, showing very promising results. In that context, actor-critic methods seem to be the most

    更新日期:2020-04-06
  • Cascade Extended State Observer for ADRC Applications under Measurement Noise
    arXiv.cs.SY Pub Date : 2020-04-03
    Krzysztof Łakomy; Rafal Madonski

    The extended state observer (ESO) plays an important role in the design of feedback control for nonlinear systems. It is also the key component in any active disturbance rejection control (ADRC) scheme. However, its high-gain nature creates a challenge in engineering practice in cases where the output measurement is corrupted by non-negligible, high-frequency noise. The presence of measurement noise

    更新日期:2020-04-06
  • Distributed Optimization using ALADIN for MPC in Smart Grids
    arXiv.cs.SY Pub Date : 2020-04-03
    Yuning Jiang; Philipp Sauerteig; Boris Houska; Karl Worthmann

    This paper presents a distributed optimization algorithm tailored to solve optimization problems arising in smart grids. In detail, we propose a variant of the Augmented Lagrangian based Alternating Direction Inexact Newton (ALADIN) method, which comes along with global convergence guarantees for the considered class of linear-quadratic optimization problems. We establish local quadratic convergence

    更新日期:2020-04-06
  • Characterization of Domain of Fixed-time Stability under Control Input Constraints
    arXiv.cs.SY Pub Date : 2020-04-02
    Kunal Garg; Dimitra Panagou

    In this paper, we study the effect of control input constraints and of the upper bound on the time of convergence on the domain of attraction for systems that exhibit fixed-time stability (FxTS). We first present a new result on FxTS, where we allow a positive term in the time derivative of the Lyapunov function. We provide analytical expressions for the domain of attraction and the time of convergence

    更新日期:2020-04-06
  • Worst-Case Sensitivity of DC Optimal Power Flow Problems
    arXiv.cs.SY Pub Date : 2020-04-03
    James Anderson; Fengyu Zhou; Steven H. Low

    In this paper we consider the problem of analyzing the effect a change in the load vector can have on the optimal power generation in a DC power flow model. The methodology is based upon the recently introduced concept of the $\mathcal{OPF}$ operator. It is shown that for general network topologies computing the worst-case sensitivities is computationally intractable. However, we show that certain

    更新日期:2020-04-06
  • Rollout scheduling and control for disturbed systems via tube MPC
    arXiv.cs.SY Pub Date : 2020-04-03
    Stefan Wildhagen; Frank Allgöwer

    Rollout control is an MPC-based control method, in which a controller is periodically activated to schedule the transmission of sensor or actuator data. Therein, a preassigned traffic specification acts as a constraint on the scheduled transmissions, ensuring that they are triggered at an admissible rate for the underlying communication network. In this paper, we extend the theory of rollout control

    更新日期:2020-04-06
  • Model Predictive Control with Forward-Looking Persistent Excitation
    arXiv.cs.SY Pub Date : 2020-04-03
    Sven Brüggemann; Robert R. Bitmead

    This work deals with the problem of simultaneous regulation and model parameter estimation in adaptive model predictive control. We propose an adaptive model predictive control and conditions which guarantee a persistently exciting closed loop sequence by only looking forward in time into the receding prediction horizon. Earlier works needed to look backwards and preserve prior regressor data. Instead

    更新日期:2020-04-06
  • Uncertain Multi-Agent Systems with Distributed Constrained Optimization Missions and Event-Triggered Communications: Application to Resource Allocation
    arXiv.cs.SY Pub Date : 2020-04-03
    Mohammad Saeed Sarafraz; Mohammad Saleh Tavazoei

    This paper deals with solving distributed optimization problems with equality constraints by a class of uncertain nonlinear heterogeneous dynamic multi-agent systems. It is assumed that each agent with an uncertain dynamic model has limited information about the main problem and limited access to the information of the other agents' states. A distributed algorithm that guarantees cooperative solving

    更新日期:2020-04-06
  • Optimality of the Subgradient Algorithm in the Stochastic Setting
    arXiv.cs.SY Pub Date : 2019-09-10
    Daron Anderson; Douglas Leith

    We show that the Subgradient algorithm is universal for online learning on the simplex in the sense that it simultaneously achieves $O(\sqrt N)$ regret for adversarial costs and $O(1)$ pseudo-regret for i.i.d costs. To the best of our knowledge this is the first demonstration of a universal algorithm on the simplex that is not a variant of Hedge. Since Subgradient is a popular and widely used algorithm

    更新日期:2020-04-06
  • Closed-Loop Two-Stage Stochastic Optimization of Offshore Wind Farm Collection System
    arXiv.cs.SY Pub Date : 2020-03-14
    Juan-Andrés Pérez-Rúa; Sara Lumbreras; Andrés Ramos; Nicolaos A. Cutululis

    A two-stage stochastic optimization model for the design of the closed-loop cable layout of an Offshore Wind Farm (OWF) is presented. The model consists on a Mixed Integer Linear Program (MILP) with scenario numeration incorporation to account for both wind power and cable failure stochasticity. The objective function supports simultaneous optimization of: (i) Initial investment (network topology and

    更新日期:2020-04-06
  • Controllability of a Linear System with Nonnegative Sparse Controls
    arXiv.cs.SY Pub Date : 2020-02-10
    Geethu Joseph

    This paper studies controllability of a discrete-time linear dynamical system using nonnegative and sparse inputs. These constraints on the control input arise naturally in many real-life systems where the external influence on the system is unidirectional, and activating each input node adds to the cost of control. We derive algebraic necessary and sufficient conditions to determine controllability

    更新日期:2020-04-06
  • Bayesian Safe Learning and Control with Sum-of-Squares Analysis and Polynomial Kernels
    arXiv.cs.SY Pub Date : 2020-04-01
    Alex Devonport; He Yin; Murat Arcak

    We propose an iterative method to safely learn the unmodeled dynamics of a nonlinear system using Bayesian Gaussian process (GP) models with polynomial kernel functions. The method maintains safety by ensuring that the system state stays within the region of attraction (ROA) of a stabilizing control policy while collecting data. A quadratic programming based exploration control policy is computed to

    更新日期:2020-04-03
  • Subspace Decomposition for Graphon LQR: Applications to VLSNs of Harmonic Oscillators
    arXiv.cs.SY Pub Date : 2020-04-01
    Shuang Gao; Peter E. Caines

    Graphon control has been proposed and developed in [Gao and Caines CDC 2017, 2018, 2019, TAC 2020) to approximately solve control problems for very large-scale networks of linear dynamical systems. In this paper, linear quadratic regulation (LQR) problems for graphon dynamical systems are studied. Graphon couplings appear in states, controls and cost, and these couplings may be represented by different

    更新日期:2020-04-03
  • LQG Graphon Mean Field Games
    arXiv.cs.SY Pub Date : 2020-04-01
    Shuang Gao; Peter E. Caines; Minyi Huang

    This paper formulates infinite dimensional graphon dynamical systems to study the limit problem of linear quadratic Gaussian graphon mean field game (LQG-GMFG). The limit problem is characterized by forward and backward graphon dynamical system equations. Based on this representation, sufficient conditions on the existence of a unique fixed point are established. Furthermore, under the finite rank

    更新日期:2020-04-03
  • Safe Zero-Shot Model-Based Learning and Control: A Wasserstein Distributionally Robust Approach
    arXiv.cs.SY Pub Date : 2020-04-02
    Aaron Kandel; Scott J. Moura

    This paper explores distributionally robust zero-shot model-based learning and control using Wasserstein ambiguity sets. Conventional model-based reinforcement learning algorithms struggle to guarantee feasibility throughout the online learning process. We address this open challenge with the following approach. Using a stochastic model-predictive control (MPC) strategy, we augment safety constraints

    更新日期:2020-04-03
  • Community Resilience Optimization Subject to Power Flow Constraints in Cyber-Physical-Social Systems in Power Engineering
    arXiv.cs.SY Pub Date : 2020-04-02
    Jaber Valinejad; Lamine Mili

    This paper develops a community resilience optimization method subject to power flow constraints in the Cyber-Physical-Social Systems in Power Engineering, which is solved using a multi-agent-based algorithm. The tool that makes the nexus between electricity generation on the physical side and the consumers and the critical loads on the social side is the power flow algorithm. Specifically, the levels

    更新日期:2020-04-03
  • A Literature Review on Mobile Charging Station Technology for Electric Vehicles
    arXiv.cs.SY Pub Date : 2020-04-02
    Shahab Afshar; Pablo Macedo; Farog Mohamed; Vahid Disfani

    While Electric vehicles (EVs) adoption is accelerating in an unprecedented way, lacking EV charging infrastructure hinders the development of the EV market. To compensate for these shortcomings, Mobile Charging Stations (MCS) could play a prominent role to accelerate EV penetration by providing charging services with no restrictions on the location and time of the charging process. This paper disseminates

    更新日期:2020-04-03
  • Radial Coverage Strength for Optimization of Multi-Camera Deployment
    arXiv.cs.SY Pub Date : 2020-04-02
    Zike Lei; Xi Chen; Xiang Chen; Li Chai

    In this paper, a new concept, radial coverage strength, is first proposed to characterize the visual sensing performance when the orientation of the target pose is considered. In particular, the elevation angle of the optical pose of the visual sensor is taken to decompose the visual coverage strength into effective and ineffective components, motivated by the imaging intuition. An optimization problem

    更新日期:2020-04-03
  • Identification of Critical Clusters in Inverter-based Microgrids
    arXiv.cs.SY Pub Date : 2020-04-02
    Andrey Gorbunov; Petr Vorobev; Jimmy Chih-Hsien Peng

    In this paper, we investigate the stability properties of inverter-based microgrids by establishing the possible presence of the so-called critical clusters - groups of inverters with their control settings being close to the stability boundary. For this, we consider the spectrum of the weighted admittance matrix of the network and show that its distinct eigenvalues correspond to inverter clusters

    更新日期:2020-04-03
  • Chattering analysis of Lipschitz continuous sliding-mode controllers
    arXiv.cs.SY Pub Date : 2020-04-02
    C. Arturo Martínez-Fuentes; Ulises Pérez Ventura; Leonid Fridman

    Lipschitz continuous sliding-mode controllers (LCSMC) are developed as the integral of discontinuous SMC, producing control signals of finite slope. Nevertheless, LCSMC still generate chattering in the presence of fast parasitic dynamics. In this paper, an analysis of chattering in systems driven by LCSMC is performed using the Harmonic Balance (HB) approach. Two kinds of LCSMC are considered: the

    更新日期:2020-04-03
  • Equivariant Filter Design for Kinematic Systems on Lie Groups
    arXiv.cs.SY Pub Date : 2020-04-02
    Robert Mahony; Jochen Trumpf

    It is known that invariance and equivariance properties for systems on Lie groups can be exploited in the design of high performance and robust observers and filters for real-world robotic systems. This paper proposes an analysis framework that allows any kinematic system on a Lie group to be embedded in a natural manner into an equivariant kinematic system. This framework allows us to characterise

    更新日期:2020-04-03
  • Learning control for polynomial systems using sum of squares
    arXiv.cs.SY Pub Date : 2020-04-02
    Meichen Guo; Claudio De Persis; Pietro Tesi

    This paper considers the problem of learning control laws for nonlinear polynomial systems directly from data, which are input-output measurements collected in an experiment over a finite time period. Without explicitly identifying the system dynamics, stabilizing laws are directly designed for nonlinear polynomial systems by solving sum of square problems that depend on the experimental data alone

    更新日期:2020-04-03
  • Sampled-Data Control Based Consensus of Fractional-Order Multi-Agent Systems
    arXiv.cs.SY Pub Date : 2020-04-02
    Xinyao Li; Changyun Wen; Xiao-Kang Liu

    In this paper, we investigate consensus control of fractional-order multi-agent systems with order in (0,1) via sampled-data control. A new scheme to design distributed controllers with rigorous analysis is presented by utilizing the unique properties of fractional-order calculus, namely hereditary and infinite memory. It is established that global boundedness of all closed-loop signals is ensured

    更新日期:2020-04-03
  • Safe Reinforcement Learning via Projection on a Safe Set: How to Achieve Optimality?
    arXiv.cs.SY Pub Date : 2020-04-02
    Sebastien Gros; Mario Zanon; Alberto Bemporad

    For all its successes, Reinforcement Learning (RL) still struggles to deliver formal guarantees on the closed-loop behavior of the learned policy. Among other things, guaranteeing the safety of RL with respect to safety-critical systems is a very active research topic. Some recent contributions propose to rely on projections of the inputs delivered by the learned policy into a safe set, ensuring that

    更新日期:2020-04-03
  • Near Optimality and Tractability in Stochastic Nonlinear Control
    arXiv.cs.SY Pub Date : 2020-04-01
    Mohamed Naveed Gul Mohamed; Suman Chakravorty

    We consider the problem of nonlinear stochastic optimal control. This is fundamentally intractable owing to Bellman's infamous "curse of dimensionality". We present a "decoupling principle" for the tractable feedback design for such problems, wherein, first, a nominal open-loop problem is solved, followed by a suitable linear feedback design around the open-loop. The performance of the resulting feedback

    更新日期:2020-04-03
  • Distributed Robust Control Synthesis for Safety and Fixed-Time Stability in Multi-Agent Systems
    arXiv.cs.SY Pub Date : 2020-04-02
    Kunal Garg; Dimitra Panagou

    This paper presents a control synthesis approach for multi-agent systems modeled as a general class of nonlinear, control-affine dynamics under spatiotemporal constraints. We consider the problem of designing distributed controllers such that each agent reaches their respective goal set within a given fixed time, while always remaining in their respective safe set, which also encodes the maintenance

    更新日期:2020-04-03
  • Optical Characterization of Ultra-Low latency Visible Light Communication System for Intelligent Transportation Systems
    arXiv.cs.SY Pub Date : 2020-03-31
    M. Seminara; T. Nawaz; S. Caputo; L. Mucchi; J. Catani

    This paper reports a detailed experimental characterization of optical performances of Visible Light Communication (VLC) system using a real traffic light for ultra-low latency, infrastructure-to-vehicle (I2V) communications for intelligent transportation systems (ITS) protocols. Despite the implementation of long sought ITS protocols poses the crucial need to detail how the features of optical stages

    更新日期:2020-04-03
  • Safe Feedback Motion Planning: A Contraction Theory and $\mathcal{L}_1$-Adaptive Control Based Approach
    arXiv.cs.SY Pub Date : 2020-04-02
    Arun Lakshmanan; Aditya Gahlawat; Naira Hovakimyan

    Autonomous robots that are capable of operating safely in the presence of imperfect model knowledge or external disturbances are vital in safety-critical applications. In this paper, we present a planner-agnostic framework to design and certify safe tubes around desired trajectories that the robot is always guaranteed to remain inside of. By leveraging recent results in contraction analysis and $\

    更新日期:2020-04-03
  • Lateral oscillation and body compliance help snakes and snake robots stably traverse large, smooth obstacles
    arXiv.cs.SY Pub Date : 2020-03-30
    Qiyuan Fu; Sean W. Gart; Thomas W. Mitchel; Jin Seob Kim; Gregory S. Chirikjian; Chen Li

    Snakes can move through almost any terrain. Similarly, snake robots hold the promise as a versatile platform to traverse complex environments like earthquake rubble. Unlike snake locomotion on flat surfaces which is inherently stable, when snakes traverse complex terrain by deforming their body out of plane, it becomes challenging to maintain stability. Here, we review our recent progress in understanding

    更新日期:2020-04-01
  • D-DistADMM: A $O(1/k)$ Distributed ADMM for Distributed Optimization in Directed Graph Topologies
    arXiv.cs.SY Pub Date : 2020-03-30
    Vivek Khatana; Murti V. Salapaka

    We focus on the problem of minimizing a finite sum $f(x) = \sum_{i=1}^n f_i(x)$ of functions of $n$ functions $f_i$, where $f_i$ are convex and available only locally to an agent $i$. The $n$ agents are connected in a directed network $\mathcal{G}(\mathbf{V},\mathbf{E})$, where each agent $i$ can only communicate with agents in its neighborhood determined by $\mathcal{G}(V,E)$. In this article, we

    更新日期:2020-04-01
  • A feedback linearisation algorithm for single-track models with structural stability properties
    arXiv.cs.SY Pub Date : 2020-03-30
    Luca Bascetta; Marcello Farina; Alessandro Gabrielli; Matteo Matteucci

    This paper proposes a feedback linearizing law for single-track dynamic models, allowing the design of a trajectory tracking controller exploiting linear control theory. The main characteristics of this algorithm are its simplicity, its independence from any vehicle model parameter, apart from the position of the center of mass, and its robustness. In particular, a numerical bifurcation analysis demonstrates

    更新日期:2020-04-01
  • H2 Optimized PID Control of Quad-Copter Platform with Wind Disturbance
    arXiv.cs.SY Pub Date : 2020-03-30
    Sunsoo Kim; Vedang Deshpande; Raktim Bhattacharya

    Proportional-Integral-Derivative (PID) scheme is the most commonly used algorithm for designing the controllers for unmanned aerial vehicles (UAVs). However, tuning PID gains is a non trivial task. A number of methods have been developed for tuning the PID gains for UAV systems. However, these methods do not handle wind disturbances, which is a major concern for small UAVs. In this paper, we propose

    更新日期:2020-04-01
  • Nonlinear Attitude Estimation for Small UAVs with Low Power Microprocessors
    arXiv.cs.SY Pub Date : 2020-03-30
    Sunsoo Kim; Vaishnav Tadiparthi; Raktim Bhattacharya

    Among algorithms used for sensor fusion for attitude estimation in unmanned aerial vehicles, the Extended Kalman Filter (EKF) is the most commonly used for estimation. In this paper, we propose a new version of H2 estimation called extended H2 estimation that can overcome the limitations of the extended Kalman Filter, specifically with respect to computational speed, memory usage, and root mean squared

    更新日期:2020-04-01
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