627 research outputs found

    Cooperative Adaptive Control for Cloud-Based Robotics

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    This paper studies collaboration through the cloud in the context of cooperative adaptive control for robot manipulators. We first consider the case of multiple robots manipulating a common object through synchronous centralized update laws to identify unknown inertial parameters. Through this development, we introduce a notion of Collective Sufficient Richness, wherein parameter convergence can be enabled through teamwork in the group. The introduction of this property and the analysis of stable adaptive controllers that benefit from it constitute the main new contributions of this work. Building on this original example, we then consider decentralized update laws, time-varying network topologies, and the influence of communication delays on this process. Perhaps surprisingly, these nonidealized networked conditions inherit the same benefits of convergence being determined through collective effects for the group. Simple simulations of a planar manipulator identifying an unknown load are provided to illustrate the central idea and benefits of Collective Sufficient Richness.Comment: ICRA 201

    Effects of Delay on the Functionality of Large-scale Networks

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    Networked systems are common across engineering and the physical sciences. Examples include the Internet, coordinated motion of multi-agent systems, synchronization phenomena in nature etc. Their robust functionality is important to ensure smooth operation in the presence of uncertainty and unmodelled dynamics. Many such networked systems can be viewed under a unified optimization framework and several approaches to assess their nominal behaviour have been developed. In this paper, we consider what effect multiple, non-commensurate (heterogeneous) communication delays can have on the functionality of large-scale networked systems with nonlinear dynamics. We show that for some networked systems, the structure of the delayed dynamics allows functionality to be retained for arbitrary communication delays, even for switching topologies under certain connectivity conditions; whereas in other cases the loop gains have to be compensated for by the delay size, in order to render functionality delay-independent for arbitrary network sizes. Consensus reaching in multi-agent systems and stability of network congestion control for the Internet are used as examples. The differences and similarities of the two cases are explained in detail, and the application of the methodology to other technological and physical networks is discussed

    Distributed Delay-Tolerant Strategies for Equality-Constraint Sum-Preserving Resource Allocation

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    This paper proposes two nonlinear dynamics to solve constrained distributed optimization problem for resource allocation over a multi-agent network. In this setup, coupling constraint refers to resource-demand balance which is preserved at all-times. The proposed solutions can address various model nonlinearities, for example, due to quantization and/or saturation. Further, it allows to reach faster convergence or to robustify the solution against impulsive noise or uncertainties. We prove convergence over weakly connected networks using convex analysis and Lyapunov theory. Our findings show that convergence can be reached for general sign-preserving odd nonlinearity. We further propose delay-tolerant mechanisms to handle general bounded heterogeneous time-varying delays over the communication network of agents while preserving all-time feasibility. This work finds application in CPU scheduling and coverage control among others. This paper advances the state-of-the-art by addressing (i) possible nonlinearity on the agents/links, meanwhile handling (ii) resource-demand feasibility at all times, (iii) uniform-connectivity instead of all-time connectivity, and (iv) possible heterogeneous and time-varying delays. To our best knowledge, no existing work addresses contributions (i)-(iv) altogether. Simulations and comparative analysis are provided to corroborate our contributions

    Coordination of passive systems under quantized measurements

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    In this paper we investigate a passivity approach to collective coordination and synchronization problems in the presence of quantized measurements and show that coordination tasks can be achieved in a practical sense for a large class of passive systems.Comment: 40 pages, 1 figure, submitted to journal, second round of revie

    Distributed Energy Resource Management: All-Time Resource-Demand Feasibility, Delay-Tolerance, Nonlinearity, and Beyond

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    In this work, we propose distributed and networked energy management scenarios to optimize the production and reservation of energy among a set of distributed energy nodes. In other words, the idea is to optimally allocate the generated and reserved powers based on nodes' local cost gradient information while meeting the demand energy. One main concern is the all-time (or anytime) resource-demand feasibility, implying that at all iterations of the scheduling algorithm, the balance between the produced power and demand plus reserved power must hold. The other concern is to design algorithms to tolerate communication time-delays and changes in the network. Further, one can incorporate possible model nonlinearity in the algorithm to address both inherent (e.g., saturation and quantization) and purposefully-added (e.g., signum-based) nonlinearities in the model. The proposed optimal allocation algorithm addresses all the above concerns, while it benefits from possible features of the distributed (or networked) solutions such as no-single-node-of-failure and distributed information processing. We show both the all-time feasibility of the proposed scheme and its convergence under certain bound on the step-rate using Lyapunov-type proofs.Comment: IEEE LCSS 202

    Resilient Cooperative Control of Networked Multi-Agent Systems

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    Distributed Control Methods for Integrating Renewable Generations and ICT Systems

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    With increased energy demand and decreased fossil fuels usages, the penetration of distributed generators (DGs) attracts more and more attention. Currently centralized control approaches can no longer meet real-time requirements for future power system. A proper decentralized control strategy needs to be proposed in order to enhance system voltage stability, reduce system power loss and increase operational security. This thesis has three key contributions: Firstly, a decentralized coordinated reactive power control strategy is proposed to tackle voltage fluctuation issues due to the uncertainty of output of DG. Case study shows results of coordinated control methods which can regulate the voltage level effectively whilst also enlarging the total reactive power capability to reduce the possibility of active power curtailment. Subsequently, the communication system time-delay is considered when analyzing the impact of voltage regulation. Secondly, a consensus distributed alternating direction multiplier method (ADMM) algorithm is improved to solve the optimal power ow (OPF) problem. Both synchronous and asynchronous algorithms are proposed to study the performance of convergence rate. Four different strategies are proposed to mitigate the impact of time-delay. Simulation results show that the optimization of reactive power allocation can minimize system power loss effectively and the proposed weighted autoregressive (AR) strategies can achieve an effective convergence result. Thirdly, a neighboring monitoring scheme based on the reputation rating is proposed to detect and mitigate the potential false data injection attack. The simulation results show that the predictive value can effectively replace the manipulated data. The convergence results based on the predictive value can be very close to the results of normal case without cyber attack

    Decentralized optimization approach for power distribution network and microgrid controls

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    The smart grid vision has led to the development of advanced control and management frameworks using distributed generation (DG) and storage resources, commonly referred to together as distributed energy resources (DERs). Albeit environment-friendly, these DERs in distribution networks including microgrids (MGs) could greatly challenge the operational goal of maintaining adequate power system reliability standards because of their high intermittency, uncertainty, and lack of physical inertia. Meanwhile, these networks are inherently unbalanced and lack high-quality communications to a centralized entity as compared to the bulk transmission grid. Both aspects contribute to the challenge of designing voltage and frequency control frameworks therein. To tackle these problems, we propose decentralized control strategies, which account for cyber-physical network interactions automatically and dynamically while being either cognizant of various communication scenarios or resilient to malicious cyber intrusions. By treating the transmission grid as an infinity bus, voltage stability is the main concern in distribution networks where more DERs are being installed in the near future. Thanks to advances in power electronics, DERs can also be excellent sources of reactive power (VAR), a quantity that is known to have a significant impact on the network voltage level. Accordingly, we first formulate the local VAR-based voltage control design by minimizing a weighted quadratic voltage mismatch error objective using gradient-projection (GP) updates. The step-size design under both static and dynamic settings is further analyzed for practical implementation purposes. Nonetheless, such local design suffers degraded performance due to lack of information exchanges, especially under limited VAR resources. To address this issue, we develop the distributed voltage control (DVC) design based on the alternating direction method of multipliers (ADMM) algorithm. The DVC design has simple node-to-node communication architecture while seamlessly adapting to dynamically varying system operating conditions and being robust against random communication link failures. To further reduce communication complexity and enhance robustness to imperfect communications, especially under the worst-case scenarios of a total communication outage, we integrate both local and distributed control designs to a hybrid voltage control (HVC) scheme that can achieve the dual objectives in terms of flexible adaptivity to variable rate of communications and global optimality of voltage regulation performance. Such an innovative design aims to unify the separated framework of either local or distributed control design. Numerical tests using realistic feeders and real time-series data have been demonstrated for the voltage control designs. The aforementioned decentralized voltage control designs can improve the power system stability while distribution feeders are interconnecting to the bulk transmission grids. With a high penetration of DERs in the networks, it is possible to build a discrete energy system, namely, a microgrid (MG), that is capable of operating in parallel with, or independently from, the transmission grids. Henceforth, MGs are likely to emerge as a means to advance power and cyber physical resiliency in future grid systems. As MGs may operate independently, these mostly power electronics-interfaced DERs exhibiting low-inertia characteristic have raised significant concern over the frequency stability issues. To tackle this problem, we introduce the concept of virtual inertia of DERs and cast the secondary frequency control design for isolated MGs as a consensus optimization problem. We solve it distributively by adopting the partial primal-dual (PPD) algorithm. Interestingly, parts of our specially designed control algorithm turn out to mimic the dynamics of network power flow and virtual synchronous generator-based inverter. Thus, such dynamics is seamlessly governed by the physical system itself. Given a proper control parameter choice, the convergence of the consensus is guaranteed without assuming the time-scale separation of the hierarchical control design methodologies. By extending this work to a practical industrial MG network that follows the IEC 61850 communication protocol, similar frequency regulation objective is introduced and solved by a decentralized ADMM-based algorithm. The countermeasures for malicious attacks on the communication network for both PPD- and ADMM-based control designs are also investigated. Specifically, we analyze two types of malicious attacks on the communication network, namely, the link and node attacks. Meanwhile, anomaly detection and localization strategies are developed based on the metrics of optimization-related variables. We showcase the microgrid frequency regulation operation to demonstrate the effectiveness of the proposed frequency control designs under a real-time simulation environment
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