Book ChapterDOI
System Identification I
Biao Huang,Yutong Qi,Akm Monjur Murshed +2 more
- pp 31-56
Reads0
Chats0
About:
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
Citations
More filters
Journal ArticleDOI
High-Level Synthesis for Accelerating the FPGA Implementation of Computationally Demanding Control Algorithms for Power Converters
TL;DR: The Xilinx Vivado HLS tool is evaluated for the design of a computationally demanding application, the real-time load estimation for resonant power converters using parametric identification methods, and shows a significant design complexity reduction.
Proceedings ArticleDOI
Local Koopman Operators for Data-Driven Control of Robotic Systems
TL;DR: The authors exploit the Koopman operator to develop a systematic, data-driven approach for constructing a linear representation in terms of higher order derivatives of the underlying nonlinear dynamics, which enables fast control synthesis of nonlinear systems.
Posted Content
Derivative-Free Methods for Policy Optimization: Guarantees for Linear Quadratic Systems
Dhruv Malik,Ashwin Pananjady,Kush Bhatia,Koulik Khamaru,Peter L. Bartlett,Martin J. Wainwright +5 more
TL;DR: In this paper, the convergence rate of derivative-free methods for policy optimization over the class of linear policies was studied. But the convergence rates were not characterized for linear-quadratic systems, and they were not shown to converge to within any pre-specified tolerance of the optimal policy.
Journal ArticleDOI
Force Modeling, Identification, and Feedback Control of Robot-Assisted Needle Insertion: A Survey of the Literature
TL;DR: The goal of this review is to summarize the key components surrounding the force feedback and control during robot-assisted needle insertion, such as force modeling, measurement, the factors that influence the interaction force, parameter identification, and force control algorithms.
Journal ArticleDOI
Adaptive step goals and rewards: a longitudinal growth model of daily steps for a smartphone-based walking intervention
Elizabeth V. Korinek,Sayali S. Phatak,Cesar A. Martin,Mohammad T. Freigoun,Daniel E. Rivera,Marc A. Adams,Pedja Klasnja,Matthew P. Buman,Eric B. Hekler +8 more
TL;DR: An adaptive step goal-+-reward intervention using a smartphone app appears to be a feasible approach for increasing walking behavior in overweight adults and future mHealth studies should consider the use of adaptive step goals + rewards in conjunction with other intervention components for increasing physical activity.
References
More filters
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.