Control theory (sociology)
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Model Predictive Control for Power Converters and Drives: Advances and Trends Open
Model predictive control (MPC) is a very attractive solution for controlling power electronic converters. The aim of this paper is to present and discuss the latest developments in MPC for power converters and drives, describing the curren…
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Harmonic Stability in Power Electronic-Based Power Systems: Concept, Modeling, and Analysis Open
The large-scale integration of power electronic based systems poses new challenges to the stability and power quality of modern power grids. The wide timescale and frequency-coupling dynamics of electronic power converters tend to bring in…
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Dynamic Mode Decomposition with Control Open
We develop a new method which extends dynamic mode decomposition (DMD) to incorporate the effect of control to extract low-order models from high-dimensional, complex systems. DMD finds spatial-temporal coherent modes, connects local-linea…
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Definition and Classification of Power System Stability – Revisited & Extended Open
Since the publication of the original paper on power \nsystem stability definitions in 2004, the dynamic behavior of power \nsystems has gradually changed due to the increasing penetration \nof converter interfaced generation technologies,…
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Stochastic Model Predictive Control: An Overview and Perspectives for Future Research Open
© 1991-2012 IEEE. Model predictive control (MPC) has demonstrated exceptional success for the high-performance control of complex systems [1], [2]. The conceptual simplicity of MPC as well as its ability to effectively cope with the compl…
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An introduction to inertial navigation Open
Until recently the weight and size of inertial sensors has prohibited their use in domains such as human motion capture. Recent improvements in the performance of small and lightweight micro-machined electromechanical systems (MEMS) inerti…
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Model Reduction for Flow Analysis and Control Open
Advances in experimental techniques and the ever-increasing fidelity of numerical simulations have led to an abundance of data describing fluid flows. This review discusses a range of techniques for analyzing such data, with the aim of ext…
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Fixed-Time Consensus Tracking for Multiagent Systems With High-Order Integrator Dynamics Open
This paper addresses the fixed-time leader-follower consensus problem for high-order integrator multi-agent systems subject to matched external disturbances. A new cascade control structure, based on a fixed time distributed observer, is d…
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Dynamic Locomotion in the MIT Cheetah 3 Through Convex Model-Predictive Control Open
© 2018 IEEE. This paper presents an implementation of model predictive control (MPC) to determine ground reaction forces for a torque-controlled quadruped robot. The robot dynamics are simplified to formulate the problem as convex optimiza…
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Quantifying and reducing leakage errors in the JPL RL05M GRACE mascon solution Open
Recent advances in processing data from the Gravity Recovery and Climate Experiment (GRACE) have led to a new generation of gravity solutions constrained within a Bayesian framework to remove correlated errors rather than relying on empiri…
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Data-Driven Model Predictive Control With Stability and Robustness Guarantees Open
We propose a robust data-driven model predictive control (MPC) scheme to control linear time-invariant (LTI) systems. The scheme uses an implicit model description based on behavioral systems theory and past measured trajectories. In parti…
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Reconfigurable Intelligent Surface Assisted UAV Communication: Joint Trajectory Design and Passive Beamforming Open
International audience
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A Novel Adaptive Kalman Filter With Inaccurate Process and Measurement Noise Covariance Matrices Open
In this paper, a novel variational Bayesian (VB)-based adaptive Kalman filter (VBAKF) for linear Gaussian state-space models with inaccurate process and measurement noise covariance matrices is proposed. By choosing inverse Wishart priors,…
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Disturbance/Uncertainty Estimation and Attenuation Techniques in PMSM Drives—A Survey Open
Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new col…
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Magnetic control of tokamak plasmas through deep reinforcement learning Open
Nuclear fusion using magnetic confinement, in particular in the tokamak configuration, is a promising path towards sustainable energy. A core challenge is to shape and maintain a high-temperature plasma within the tokamak vessel. This requ…
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Transient Stability of Voltage-Source Converters With Grid-Forming Control: A Design-Oriented Study Open
Driven by the large-scale integration of distributed power resources, grid-connected voltage-source converters (VSCs) are increasingly required to operate as grid-forming units to regulate the system voltage/frequency and emulate the inert…
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Using machine learning to replicate chaotic attractors and calculate Lyapunov exponents from data Open
We use recent advances in the machine learning area known as “reservoir computing” to formulate a method for model-free estimation from data of the Lyapunov exponents of a chaotic process. The technique uses a limited time series of measur…
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The Invariant Extended Kalman Filter as a Stable Observer Open
International audience
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Frequency Selective Hybrid Precoding for Limited Feedback Millimeter Wave Systems Open
Hybrid analog/digital precoding offers a compromise between hardware\ncomplexity and system performance in millimeter wave (mmWave) systems. This\ntype of precoding allows mmWave systems to leverage large antenna array gains\nthat are nece…
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High-order fully actuated system approaches: Part I. Models and basic procedure Open
The state-space approaches have stayed in an absolutely dominant position in the field of systems and control for over a half century. Although a state-space representation is more suitable for deriving the state-response solution and obse…
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A Framework of Robust Transmission Design for IRS-Aided MISO Communications With Imperfect Cascaded Channels Open
Intelligent reflection surface (IRS) has recently been recognized as a\npromising technique to enhance the performance of wireless systems due to its\nability of reconfiguring the signal propagation environment. However, the\nperfect chann…
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A soft, bistable valve for autonomous control of soft actuators Open
An entirely soft valve uses a snap-through instability to integrate autonomous control functions into soft actuators.
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Overview and Comparison of Modulation and Control Strategies for a Nonresonant Single-Phase Dual-Active-Bridge DC–DC Converter Open
The nonresonant single-phase dual-active-bridge (NSDAB) dc-dc converter has been increasingly adopted for isolated dc-dc power conversion systems. Over the past few years, significant research has been carried out to address the technical …
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A Modified Sequence-Domain Impedance Definition and Its Equivalence to the dq-Domain Impedance Definition for the Stability Analysis of AC Power Electronic Systems Open
Representation of ac power systems by frequency-dependent impedance equivalents is an emerging technique in the dynamic analysis of power systems including power electronic converters. The technique has been applied for decades in dc-power…
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Review on Control of DC Microgrids Open
This paper performs an extensive review on control schemes and architectures applied to dc microgrids (MGs). It covers multilayer hierarchical control schemes, coordinated control strategies, plug-and-play operations, stability and active …
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Security Control for Discrete-Time Stochastic Nonlinear Systems Subject to Deception Attacks Open
This paper is concerned with the security control problem with quadratic cost criterion for a class of discrete-time stochastic nonlinear systems subject to deception attacks. A definition of security in probability is adopted to account f…
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Artificial neural networks trained through deep reinforcement learning discover control strategies for active flow control Open
We present the first application of an artificial neural network trained through a deep reinforcement learning agent to perform active flow control. It is shown that, in a two-dimensional simulation of the Kármán vortex street at moderate …
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Finite-Time Event-Triggered $\mathcal{H}_{\infty }$ Control for T–S Fuzzy Markov Jump Systems Open
This paper investigates the finite-time event-triggered H-infinity control problem for Takagi-Sugeno Markov jump fuzzy systems. Because of the sampling behaviors and the effect of network environment, the premise variables considered in th…
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A Review of Mutual Coupling in MIMO Systems Open
This paper provides a systematic review of the mutual coupling in multiple-input multiple-output (MIMO) systems, including effects on performances of MIMO systems and various decoupling techniques. The mutual coupling changes the antenna c…
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Model Predictive Control of Power Electronic Systems: Methods, Results, and Challenges Open
Model predictive control (MPC) has established itself as a promising control methodology in power electronics. This survey paper highlights the most relevant MPC techniques for power electronic systems. These can be classified into two maj…