83 research outputs found

    A Near-Optimal Decentralized Servomechanism Controller for Hierarchical Interconnected Systems

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    This paper is concerned with decentralized output regulation of hierarchical systems subject to input and output disturbances. It is assumed that the disturbance can be represented as the output of an autonomous LTI system with unknown initial state. The primary objective is to design a decentralized controller with the property that not only does it reject the degrading effect of the disturbance on the output (for a satisfactory steady-state performance), it also results in a small LQ cost function (implying a good transient behavior). To this end, the underlying problem is treated in two phases. In the first step, a number of modified systems are defined in terms of the original system. The problem of designing a LQ centralized controller which stabilizes all the modified systems and rejects the disturbance in the original system is considered, and it is shown that this centralized controller can be efficiently found by solving a LMI problem. In the second step, a method recently presented in the literature is exploited to decentralize the designed centralized controller. It is proved that the obtained controller satisfies the pre-determined design specifications including disturbance rejection. Simulation results elucidate the efficacy of the proposed control law

    Decentralized control of uncertain interconnected time-delay systems

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    In this thesis, novel stability analysis and control synthesis methodologies are proposed for uncertain interconnected time-delay systems. It is known that numerous real-world systems such as multi-vehicle flight formation, automated highway systems, communication networks and power systems can be modeled as the interconnection of a number of subsystems. Due to the complex and distributed structure of this type of systems, they are subject to propagation and processing delays, which cannot be ignored in the modeling process. On the other hand, in a practical environment the parameters of the system are not known exactly, and usually the nominal model is used for controller design. It is important, however, to ensure that robust stability and performance are achieved, that is, the overall closed-loop system remains stable and performs satisfactorily in the presence of uncertainty. To address the underlying problem, the notion of decentralized fixed modes is extended to the class of linear time-invariant (LTI) time-delay systems, and a necessary and sufficient condition is proposed for stabilizability of this type of systems by means of a finite-dimensional decentralized LTI output feedback controller. A near-optimal decentralized servomechanism control design method and a cooperative predictive control scheme are then presented for uncertain LTI hierarchical interconnected systems. A H {592} decentralized overlapping control design technique is provided consequently which guarantees closed-loop stability and disturbance attenuation in the presence of delay. In particular, for the case of highly uncertain time-delay systems, an adaptive switching control methodology is proposed to achieve output tracking and disturbance rejection. Simulation results are provided throughout the thesis to support the theoretical finding

    Modeling and Control of High-Voltage Direct-Current Transmission Systems: From Theory to Practice and Back

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    The problem of modeling and control of multi-terminal high-voltage direct-current transmission systems is addressed in this paper, which contains five main contributions. First, to propose a unified, physically motivated, modeling framework - based on port-Hamiltonian representations - of the various network topologies used in this application. Second, to prove that the system can be globally asymptotically stabilized with a decentralized PI control, that exploits its passivity properties. Close connections between the proposed PI and the popular Akagi's PQ instantaneous power method are also established. Third, to reveal the transient performance limitations of the proposed controller that, interestingly, is shown to be intrinsic to PI passivity-based control. Fourth, motivated by the latter, an outer-loop that overcomes the aforementioned limitations is proposed. The performance limitation of the PI, and its drastic improvement using outer-loop controls, are verified via simulations on a three-terminals benchmark example. A final contribution is a novel formulation of the power flow equations for the centralized references calculation

    Distributed Control of Autonomous Microgrids

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    H2, fixed architecture, control design for large scale systems

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    Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 1990.Includes bibliographical references (p. 227-234).by Mathieu Mercadal.Ph.D

    Optimized state feedback regulation of 3DOF helicopter system via extremum seeking

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    In this paper, an optimized state feedback regulation of a 3 degree of freedom (DOF) helicopter is designed via extremum seeking (ES) technique. Multi-parameter ES is applied to optimize the tracking performance via tuning State Vector Feedback with Integration of the Control Error (SVFBICE). Discrete multivariable version of ES is developed to minimize a cost function that measures the performance of the controller. The cost function is a function of the error between the actual and desired axis positions. The controller parameters are updated online as the optimization takes place. This method significantly decreases the time in obtaining optimal controller parameters. Simulations were conducted for the online optimization under both fixed and varying operating conditions. The results demonstrate the usefulness of using ES for preserving the maximum attainable performance

    Advances in Reinforcement Learning

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    Reinforcement Learning (RL) is a very dynamic area in terms of theory and application. This book brings together many different aspects of the current research on several fields associated to RL which has been growing rapidly, producing a wide variety of learning algorithms for different applications. Based on 24 Chapters, it covers a very broad variety of topics in RL and their application in autonomous systems. A set of chapters in this book provide a general overview of RL while other chapters focus mostly on the applications of RL paradigms: Game Theory, Multi-Agent Theory, Robotic, Networking Technologies, Vehicular Navigation, Medicine and Industrial Logistic

    Hierarchical Coordinated Fast Frequency Control using Inverter-Based Resources for Next-Generation Power Grids

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    The proportion of inverter-connected renewable energy resources (RES) in the grid is expanding, primarily displacing conventional synchronous generators. This shift significantly impacts the objective of maintaining grid stability and reliable operations. The increased penetration of RESs contributes to the variability of active power supply and a decrease in the rotational inertia of the grid, resulting in faster system dynamics and larger, more frequent frequency events. These emerging challenges could make traditional centralized frequency control strategies ineffective, necessitating the adoption of modern, high-bandwidth control schemes. In this thesis, we propose a novel hierarchical and coordinated real-time frequency control scheme. It leverages advancements in grid monitoring and communication infrastructure to employ local, flexible inverter-based resources for promptly correcting power imbalances in the system. We solve two research problems that, when combined, yield a practical, real-time, next-generation frequency control scheme. This scheme blends localized control with high-bandwidth wide-area coordination. For the first problem, we propose a layered architecture where control, estimation, and optimization tasks are efficiently aggregated and decentralized across the system. This layered control structure, comprising decentralized, distributed, and centralized assets, enables fast, localized control responses to local power imbalances, integrated with wide- area coordination. For the second problem, we propose a data-driven extension to the framework to enhance model flexibility. Achieving high accuracy in system models used for control design is a considerable challenge due to the increasing scale, complexity, and evolving dynamics of the power system. In our proposed approach, we leverage collected data to provide direct data-driven controller designs for fast frequency regulation. The devised scheme ensures swift and effective frequency control for the bulk grid by accurately re-dispatching inverter-based resources (IBRs) to compensate for unmeasured net-load changes. These changes are computed in real-time using frequency and area tie power flow measurements, alongside collected historical data, thus eliminating reliance on proprietary power system models. Validated through detailed simulations under various scenarios such as load increase, generation trips, and three-phase faults, the scheme is practical, provides rapid, localized frequency control, safeguards data privacy, and eliminates the need for system models of the increasingly complex power system

    Control and Coordination in Hierarchical Systems

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    This book presents the applied theory of control and cooordination in hierarchical systems which are those where decision making has been divided in a certain way. It concentrates on various aspects of optimal control in large scale systems and covers a range of topics from multilevel methods for optimizing by interactive feedback procedures to methods for sequential, hierarchical control in large dynamic systems
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