Neural-Network-Based Near-Optimal Control for a Class of Discrete-Time Affine Nonlinear Systems With Control Constraints

By Huaguang Zhang, Yanhong Luo, Derong Liu. IEEE Transactions on Neural Networks, 2009

633 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/cde66ff34b934d0eb6a33263a036a410a89159bc

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Derong Liu
2. Ding Wang
3. Mou Chen
4. Haibo He
5. Yanhong Luo
6. Huaguang Zhang
7. Wei He
8. He Jiang

In Computational Theory and Mathematics

1. Derong Liu
2. Ding Wang
3. Haibo He
4. Huaguang Zhang
5. Yanhong Luo
6. Wei He
7. He Jiang
8. Geyang Xiao

In Control and Systems Engineering

1. Mou Chen
2. Wei He
3. Derong Liu
4. Shaocheng Tong
5. Ding Wang
6. Shuzhi Sam Ge
7. Haibo He
8. Gang Tao

Citations in the corpus

• Decentralized Stabilization for a Class of Continuous-Time Nonlinear Interconnected Systems Using Online Learning Optimal Control Approach (2014, neutral): “Al-Tamimi et al. [18], Zhang et al. [23], and Liu et al. [26] 2162-237X © 2013 IEEE.”
• Adaptive Critic Nonlinear Robust Control: A Survey (2017, methodology): “ative ADP algorithm based on value iteration is important to the self-learning optimal control design of discrete-time systems [27], [47], [52], [55], [59], while the policy iteration is significant to the adaptive optimal control design of”
• Dynamic Surface Control Using Neural Networks for a Class of Uncertain Nonlinear Systems With Input Saturation (2015, background): “Neural network (NN)-based near-optimal control was developed for a class of discretetime affine nonlinear systems with control constraints in [4].”
• Adaptive Neural Network Control of a Robotic Manipulator With Time-Varying Output Constraints (2017, background): “[30] devised a control scheme based on NN for affine nonlinear systems which are discrete-time and subjected to constraints.”
• Direct Adaptive Neural Control for a Class of Uncertain Nonaffine Nonlinear Systems Based on Disturbance Observer (2013, background): “NN near-optimal control was proposed for a class of discrete-time affine nonlinear systems with control constraints in [72].”
• A Clustering-Based Graph Laplacian Framework for Value Function Approximation in Reinforcement Learning (2014, background): “[28] proposed a novel nonquadratic function to deal with saturation con-”
• Data-Driven Optimal Consensus Control for Discrete-Time Multi-Agent Systems With Unknown Dynamics Using Reinforcement Learning Method (2017, background): “Definition 1 (Admissible Control [18]): The control policies ui(k) for ∀i are said to be admissible if they do not only stabilize the systems (5) but also guarantee performance indices (7) finite.”
• Adaptive Dynamic Programming: An Introduction (2009, background): “In addition, practical applications of ADP with significant economic impact are of great demand.”