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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Bayesian Nonparametric Reward Learning From Demonstration
TL;DR: A Bayesian nonparametric reward-learning framework is presented that infers multiple subgoals and reward functions within a single unsegmented demonstration and is shown to have both performance and computational advantages over existing inverse reinforcement learning methods.
Journal ArticleDOI
A Test Method for Damage Diagnosis of Suspension Bridge Suspender Cables
TL;DR: Numerical results for single and multiple damage cases indicate that both procedures can be effective for damage diagnosis of suspender cables and small damage can be more easily diagnosed in long Suspender cables than short ones.
Journal ArticleDOI
Virtual Sensor for Failure Detection, Identification and Recovery in the Transition Phase of a Morphing Aircraft
Guillermo Heredia,Anibal Ollero +1 more
TL;DR: A virtual sensor based Fault Detection, Identification and Recovery (FDIR) system is proposed to increase the reliability of the HADA aircraft and is able to capture the nonlinear interaction between the folding/unfolding wings aerodynamics and the H ADA airframe using the navigation sensor measurements.
Journal ArticleDOI
Robust learning-based MPC for nonlinear constrained systems
TL;DR: This paper presents a robust learning-based predictive control strategy for nonlinear systems subject to both input and output constraints, under the assumption that the model function is not known a priori and only input–output data are available.
Journal ArticleDOI
Analysis of the Exponential Signal by the Interpolated DFT Algorithm
Rong-Ching Wu,Ching-Tai Chiang +1 more
TL;DR: In this paper, exponential signals in the frequency domain are accurately analyzed by an algorithm, and the peaks of the discrete Fourier transform result are adopted to obtain parameters that include amplitudes, frequencies, dampings, and phases.
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.