Filters








32,508 Hits in 3.9 sec

Online Learning Robust Control of Nonlinear Dynamical Systems [article]

Deepan Muthirayan, Pramod P. Khargonekar
2021 arXiv   pre-print
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

Mai Thang Long, Wang Yao Nan
2014 Journal of Intelligent and Robotic Systems  
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]

Rohan Sinha, James Harrison, Spencer M. Richards, Marco Pavone
2021 arXiv   pre-print
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

Chun-Fei Hsu, Chih-Min Lin, Tsu-Tian Lee
2006 IEEE Transactions on Neural Networks  
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  
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

Chun-Fei Hsu, Tsu-Tian Lee, Chun-Wei Chang
2014 2014 Proceedings of the SICE Annual Conference (SICE)  
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

Qidan Zhu, Yu Han, Chengtao Cai, Yao Xiao
2018 Mathematical Problems in Engineering  
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  
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  
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  
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  
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  
., +, 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

Giovanni Cherubini, Martin Guay, Sophie Tarbouriech, Kartik Ariyur, Mireille E. Broucke, Subhrakanti Dey, Christian Ebenbauer, Paolo Frasca, Bahman Gharesifard, Antoine Girard, Joao Manoel Gomes da Silva, Lars Grune (+5 others)
2020 IEEE Control Systems Letters  
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

Balaje T. Thumati, S. Jagannathan
2009 2009 American Control Conference  
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

Yang Gao, Meng Joo Er
2002 IFAC Proceedings Volumes  
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
« Previous Showing results 1 — 15 out of 32,508 results