Book ChapterDOI
System Identification I
Biao Huang,Yutong Qi,Akm Monjur Murshed +2 more
- pp 31-56
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The article was published on 2012-12-11. It has received 1704 citations till now. The article focuses on the topics: Nonlinear system identification & System identification.read more
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Proceedings ArticleDOI
Linearisation of electrically stimulated muscles by feedback control of the muscular recruitment measured by evoked EMG
TL;DR: A novel feedback control method for neuro-prosthetic systems is presented which linearises the static input non-linearity of muscles that are artificially activated by Functional Electrical Stimulation (FES).
Journal ArticleDOI
Parametric Modeling for Damped Sinusoids From Multiple Channels
TL;DR: Simulations are performed to show the performance advantages of the proposed multi-channel sinusoidal modeling methodology compared with existing methods.
Proceedings ArticleDOI
Model and Economic Uncertainties in Balancing Short-Term and Long-Term Objectives in Water-Flooding Optimization
TL;DR: This work addresses the question whether through an explicit handling of model and economic uncertainties in NPV (robust) optimization, an appropriate balance between these economic objectives is naturally obtained.
Posted Content
Data-Enabled Predictive Control for Grid-Connected Power Converters
TL;DR: In this paper, a data-enabled predictive control (DeePC) algorithm was proposed for grid-connected power converters to perform safe and optimal control, where the DeePC algorithm solely needs input/output data measured from the unknown system to predict future trajectories.
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Adaptive Control and Regret Minimization in Linear Quadratic Gaussian (LQG) Setting
TL;DR: This work proposes LQGOPT, a novel adaptive control algorithm based on the principle of optimism in the face of uncertainty, to effectively minimize the overall control cost, and proves the first Õ regret upper bound for adaptive control of linear quadratic Gaussian systems with convex cost.
References
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Book
System Identification: Theory for the User
TL;DR: Das Buch behandelt die Systemidentifizierung in dem theoretischen Bereich, der direkte Auswirkungen auf Verstaendnis and praktische Anwendung der verschiedenen Verfahren zur IdentifIZierung hat.
Journal ArticleDOI
Deep learning in neural networks
TL;DR: This historical survey compactly summarizes relevant work, much of it from the previous millennium, review deep supervised learning, unsupervised learning, reinforcement learning & evolutionary computation, and indirect search for short programs encoding deep and large networks.
Journal ArticleDOI
Linear predictors for nonlinear dynamical systems: Koopman operator meets model predictive control
Milan Korda,Igor Mezic +1 more
TL;DR: This work extends the Koopman operator to controlled dynamical systems and applies the Extended Dynamic Mode Decomposition (EDMD) to compute a finite-dimensional approximation of the operator in such a way that this approximation has the form of a linearcontrolled dynamical system.
Journal ArticleDOI
A Tour of Reinforcement Learning: The View from Continuous Control
TL;DR: The authors surveys reinforcement learning from the perspective of optimization and control, with a focus on continuous control applications, and reviews the general formulation, terminology, and techniques for reinforcement learning for continuous control.
Journal ArticleDOI
SPICE: A Sparse Covariance-Based Estimation Method for Array Processing
Petre Stoica,Prabhu Babu,Jian Li +2 more
TL;DR: This paper presents a novel SParse Iterative Covariance-based Estimation approach, abbreviated as SPICE, to array processing, obtained by the minimization of a covariance matrix fitting criterion and is particularly useful in many- snapshot cases but can be used even in single-snapshot situations.