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Online Learning Robust Control of Nonlinear Dynamical Systems
[article]
2021
arXiv
pre-print
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In this work we address the problem of the online robust control of nonlinear dynamical systems perturbed by disturbance. ...
Our goal is to design a controller that can learn and adapt to achieve a certain level of attenuation. We analyse two cases (i) when the system is known and (ii) when the system is unknown. ...
Algorithm 1 Online Learning Robust Control (Known System with Disturbance Preview) 1: Input: M 2: for t = 1,... ...
arXiv:2106.04092v1
fatcat:eswglw6apvbvvdf3zswoden7bq
Adaptive Position Tracking System and Force Control Strategy for Mobile Robot Manipulators Using Fuzzy Wavelet Neural Networks
2014
Journal of Intelligent and Robotic Systems
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To solve this problem, an adaptive FWNNs control scheme with the online learning ability is utilized to approximate the unknown dynamics without the requirement of prior system information. ...
The design of adaptive online learning algorithms is derived using M. T. Long ( ) · Lyapunov stability theorem. ...
The main advantage of these learning laws is the stable guarantee of the control systems. ...
doi:10.1007/s10846-013-0006-5
fatcat:wsmmq35k5bblfjkzgneoxwkgwu
Adaptive Robust Model Predictive Control with Matched and Unmatched Uncertainty
[article]
2021
arXiv
pre-print
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We propose a learning-based robust predictive control algorithm that compensates for significant uncertainty in the dynamics for a class of discrete-time systems that are nominally linear with an additive ...
In contrast to previous work in robust adaptive MPC, our approach allows us to take advantage of structure (i.e., the numerical predictions) in the a priori unknown dynamics learned online through function ...
This article solely reflects our own opinions and conclusions, and not those of any NSF, NASA, or NSERC entity. ...
arXiv:2104.08261v3
fatcat:xryhcaxbzjfsdim7ik7hcoam6a
Wavelet Adaptive Backstepping Control for a Class of Nonlinear Systems
2006
IEEE Transactions on Neural Networks
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This paper proposes a wavelet adaptive backstepping control (WABC) system for a class of second-order nonlinear systems. The WABC comprises a neural backstepping controller and a robust controller. ...
Index Terms-Adaptive control, backstepping control, chaotic system, robust control, wavelet neural network (WNN), wing-rock system. ...
In the neural backstepping controller, a WNN identifier is utilized to online estimate the system dynamic function. ...
doi:10.1109/tnn.2006.878122
pmid:17001979
fatcat:pgn2n4vdkrchdaij6dupnsmlea
Index
[chapter]
2017
Robust Adaptive Dynamic Programming
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robust policy iteration, 101 AlphaGo, 2 approximate dynamic programming, see The focus of this series is to introduce the advances in theory and applications of systems science and engineering to industrial ...
INDEX action, 1-6 adaptive dynamic programming, see ADP adaptive optimal control, 29-30 admissible, 50, 55 control policy, 36, 39, 67 ADP, 2 affine nonlinear system, 5, 35, 46 after-effects, 156-157, 168 ...
41-46, 64
reinforcement learning, 1, 2, 11, 14, 30, 46,
170, 172
relaxation, 52, 81
relaxed HJB, 52, 81
relaxed optimal control problem, 52
reward, 1
robust adaptive dynamic programming, see
RADP ...
doi:10.1002/9781119132677.index
fatcat:eoyhxre6fbbbzhrcsmdmald3ru
Intelligent second-order sliding-mode control for chaotic tracking problem
2014
2014 Proceedings of the SICE Annual Conference (SICE)
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In this paper, a recurrent fuzzy neural network (RFNN) is used to online approximate the unknown nonlinear term of chaotic system dynamics with a good accuracy. ...
A neural controller and a robust compensator are designed in the proposed ISSMC system. ...
ACKNOWLEDGMENT The authors appreciate the partial financial support from the National Science Council of Republic of China under grant NSC 102-2221-E-032-052. ...
doi:10.1109/sice.2014.6935181
fatcat:kvafvnvrxbeg7g2zq2ymwvqzny
Robust Optimal Navigation Using Nonlinear Model Predictive Control Method Combined with Recurrent Fuzzy Neural Network
2018
Mathematical Problems in Engineering
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A novel iterative online learning method is also proposed to estimate intrinsic error of system using online data that makes system adaptive. ...
Robustness and optimization of proposed navigation method can be guaranteed in dynamic environment. ...
It is simulation experiment result that describes robot's motion in dynamic environment and reflects effectiveness of the navigation method. ...
doi:10.1155/2018/8014019
fatcat:rurs6ybwuvhf7gsgqug4nq2tni
Issue Information
2021
International Journal of Robust and Nonlinear Control
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The International Journal of Robust and Nonlinear Control aims to encourage the development of analysis and design techniques for uncertain linear and nonlinear systems. ...
The development of nonlinear compensation and design methods using feedback linearization, back-stepping, Lyapunov based techniques, learning control, cooperative control and agent based systems are all ...
, China
(adaptive critic, adaptive dynamic programming,
reinforcement learning, optimal control, robust control,
nonlinear control, learning systems, intelligent control,
and also with their industrial ...
doi:10.1002/rnc.5070
fatcat:wnmufkrs6vhd7bmuxelvygsmhi
Issue Information
2021
International Journal of Robust and Nonlinear Control
Preserved Fulltext
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The file type is application/pdf.
The International Journal of Robust and Nonlinear Control aims to encourage the development of analysis and design techniques for uncertain linear and nonlinear systems. ...
The development of nonlinear compensation and design methods using feedback linearization, back-stepping, Lyapunov based techniques, learning control, cooperative control and agent based systems are all ...
, China
(adaptive critic, adaptive dynamic programming,
reinforcement learning, optimal control, robust control,
nonlinear control, learning systems, intelligent control,
and also with their industrial ...
doi:10.1002/rnc.5071
fatcat:rwjmajo66bfc7an7ucryxai6xu
Issue Information
2021
International Journal of Robust and Nonlinear Control
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
The International Journal of Robust and Nonlinear Control aims to encourage the development of analysis and design techniques for uncertain linear and nonlinear systems. ...
The development of nonlinear compensation and design methods using feedback linearization, back-stepping, Lyapunov based techniques, learning control, cooperative control and agent based systems are all ...
, China
(adaptive critic, adaptive dynamic programming,
reinforcement learning, optimal control, robust control,
nonlinear control, learning systems, intelligent control,
and also with their industrial ...
doi:10.1002/rnc.5072
fatcat:i5d6nhi5gfgddijapckfzxefge
Issue Information
2021
International Journal of Robust and Nonlinear Control
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
The International Journal of Robust and Nonlinear Control aims to encourage the development of analysis and design techniques for uncertain linear and nonlinear systems. ...
The development of nonlinear compensation and design methods using feedback linearization, back-stepping, Lyapunov based techniques, learning control, cooperative control and agent based systems are all ...
systems)
Ding Wang
Beijing University of Technology, China
(adaptive critic, adaptive dynamic programming,
reinforcement learning, optimal control, robust control,
nonlinear control, learning systems ...
doi:10.1002/rnc.5067
fatcat:3dflz6tc3narpk6y7vusb7zhoe
2014 Index IEEE Transactions on Neural Networks and Learning Systems Vol. 25
2014
IEEE Transactions on Neural Networks and Learning Systems
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., +, TNNLS Aug. 2014
1508-1519
Dynamic Learning From Adaptive Neural Network Control of a Class of
Nonaffine Nonlinear Systems. Dai, S. ...
., +, TNNLS Mar. 2014 621-634 Robust Adaptive Dynamic Programming and Feedback Stabilization of Nonlinear Systems. ...
The Field of Values of a Matrix and Neural Networks. Georgiou, G.M., TNNLS Sep. 2014 ...
doi:10.1109/tnnls.2015.2396731
fatcat:ztnfcozrejhhfdwg7t2f5xlype
Guest Editorial Introduction to the Special Issue of the IEEE L-CSS on Learning and Control
2020
IEEE Control Systems Letters
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Control of the Learning Rate in Deep Neural Networks: "Event-Based Control for Online Training of Neural Networks": Zhao, Cerf, Robu, and Marchand propose two event-based control strategies to dynamically ...
to the infinite-horizon optimal control problem for nonlinear systems with system safety using barrier certificates. ...
doi:10.1109/lcsys.2020.2986590
fatcat:wx42r4h6ond3dkjntcwsdrmojy
A model based fault detection and accommodation scheme for nonlinear discrete-time systems with asymptotic stability guarantee
2009
2009 American Control Conference
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The asymptotic stability of the closed-loop system due to the FDA algorithm is demonstrated in the presence of online approximator reconstruction errors and bounded system uncertainties by using a robust ...
The changes in the system dynamics due to the faults are modeled as a nonlinear function of state and input variables while the time profile of the fault is assumed to be exponentially developing. ...
Then the OLAD scheme is tuned online for learning the unknown fault dynamics. ...
doi:10.1109/acc.2009.5160700
dblp:conf/amcc/ThumatiJ09a
fatcat:jfzq3p4nzzgwtc7to6ljl6eu4q
ONLINE ADAPTIVE FUZZY NEURAL IDENTIFICATION AND CONTROL OF A CLASS OF MIMO NONLINEAR SYSTEMS
2002
IFAC Proceedings Volumes
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uncertain MIMO nonlinear systems; (3) Fast learning speed; (4) Adaptive control; (5) Robust control, where global stability of the system is established using the Lyapunov approach. ...
This paper presents a robust Adaptive Fuzzy Neural Controller (AFNC) suitable for identification and control of a class of uncertain MIMO nonlinear systems. ...
INTRODUCTION Design of robust adaptive controllers suitable for real-time control of MIMO nonlinear systems is one of the most challenging tasks for many control engineers, especially when the nonlinear ...
doi:10.3182/20020721-6-es-1901.00703
fatcat:ek4eeark5vhq5hq54diishsdfe
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