Neural H2 Control Using Reinforcement Learning for Unknown Nonlinear Systems
暂无分享,去创建一个
[1] Derong Liu,et al. Adaptive Dynamic Programming for Control , 2012 .
[2] Warren E. Dixon,et al. Model-based reinforcement learning for approximate optimal regulation , 2016, Autom..
[3] Xiaoou Li,et al. Impedance Control without Environment Model by Reinforcement Learning , 2019, 2019 Tenth International Conference on Intelligent Control and Information Processing (ICICIP).
[4] Frank L. Lewis,et al. Discrete-Time Nonlinear HJB Solution Using Approximate Dynamic Programming: Convergence Proof , 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[5] Wen Yu,et al. Position/force control of robot manipulators using reinforcement learning , 2019, Ind. Robot.
[6] Frank L. Lewis,et al. Online learning algorithm for zero-sum games with integral reinforcement learning , 2011 .
[7] Alexander S. Poznyak,et al. Indirect adaptive control via parallel dynamic neural networks , 1999 .
[8] Robert Babuska,et al. Efficient Model Learning Methods for Actor–Critic Control , 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[9] Wen Yu,et al. Multiple recurrent neural networks for stable adaptive control , 2006, Neurocomputing.
[10] Adolfo Perrusquía,et al. Robust control under worst‐case uncertainty for unknown nonlinear systems using modified reinforcement learning , 2020, International Journal of Robust and Nonlinear Control.
[11] Frank L. Lewis,et al. Optimal Adaptive Control and Differential Games by Reinforcement Learning Principles , 2012 .
[12] Frank L. Lewis,et al. Optimal and Autonomous Control Using Reinforcement Learning: A Survey , 2018, IEEE Transactions on Neural Networks and Learning Systems.
[13] Robert Babuska,et al. Model learning actor-critic algorithms: Performance evaluation in a motion control task , 2012, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC).
[14] Frank L. Lewis,et al. Actor–Critic-Based Optimal Tracking for Partially Unknown Nonlinear Discrete-Time Systems , 2015, IEEE Transactions on Neural Networks and Learning Systems.
[15] Wen Yu,et al. Nonlinear system identification using discrete-time recurrent neural networks with stable learning algorithms , 2004, Inf. Sci..
[16] Avimanyu Sahoo,et al. Near Optimal Event-Triggered Control of Nonlinear Discrete-Time Systems Using Neurodynamic Programming , 2016, IEEE Transactions on Neural Networks and Learning Systems.
[17] Frank L. Lewis,et al. Online actor critic algorithm to solve the continuous-time infinite horizon optimal control problem , 2009, 2009 International Joint Conference on Neural Networks.
[18] Frank L. Lewis,et al. Linear Quadratic Tracking Control of Partially-Unknown Continuous-Time Systems Using Reinforcement Learning , 2014, IEEE Transactions on Automatic Control.
[19] Insoo Lee,et al. Neural network indirect adaptive control with fast learning algorithm , 1996, Neurocomputing.
[20] Frank L. Lewis,et al. Optimal tracking control of nonlinear partially-unknown constrained-input systems using integral reinforcement learning , 2014, Autom..
[21] Wen Yu,et al. Large space dimension Reinforcement Learning for Robot Position/Force Discrete Control , 2019, 2019 6th International Conference on Control, Decision and Information Technologies (CoDIT).
[22] Robert Babuska,et al. Actor-Critic Control with Reference Model Learning , 2011, IFAC Proceedings Volumes.
[23] Frank L. Lewis,et al. $ {H}_{ {\infty }}$ Tracking Control of Completely Unknown Continuous-Time Systems via Off-Policy Reinforcement Learning , 2015, IEEE Transactions on Neural Networks and Learning Systems.
[24] Frank L. Lewis,et al. 2009 Special Issue: Neural network approach to continuous-time direct adaptive optimal control for partially unknown nonlinear systems , 2009 .
[25] Victor M. Becerra,et al. Optimal control , 2008, Scholarpedia.
[26] Hazem N. Nounou,et al. Stable auto-tuning of adaptive fuzzy/neural controllers for nonlinear discrete-time systems , 2004, IEEE Transactions on Fuzzy Systems.
[27] Xiaoou Li,et al. Recurrent fuzzy neural networks for nonlinear system identification , 2007, 2007 IEEE 22nd International Symposium on Intelligent Control.
[28] Richard S. Sutton,et al. Reinforcement Learning: An Introduction , 1998, IEEE Trans. Neural Networks.
[29] Zhong-Ping Jiang,et al. Input-to-state stability for discrete-time nonlinear systems , 1999 .
[30] Xiaoou Li,et al. Discrete-time nonlinear system identification using recurrent neural networks , 2003, 42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475).
[31] Fuxiao Tan,et al. Discrete-time LQR optimal tracking control problems using Approximate Dynamic Programming algorithm with disturbance , 2013, 2013 Fourth International Conference on Intelligent Control and Information Processing (ICICIP).
[32] F. Lewis,et al. Reinforcement Learning and Feedback Control: Using Natural Decision Methods to Design Optimal Adaptive Controllers , 2012, IEEE Control Systems.
[33] Shuzhi Sam Ge,et al. Optimal Critic Learning for Robot Control in Time-Varying Environments , 2015, IEEE Transactions on Neural Networks and Learning Systems.
[34] Haibo He,et al. Adaptive Event-Triggered Control Based on Heuristic Dynamic Programming for Nonlinear Discrete-Time Systems , 2017, IEEE Transactions on Neural Networks and Learning Systems.